An Overview of the Latest Research in Software Radio

VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP An Overview of the Latest Research in Software Radio Dr. Jeffrey H. Reed Bradley Dept. of Electrical and Computer Engineering Virginia Tech reedjh@vt.edu (540) 231 2972 Dr. Jeff Smith Mercury Computer jesmith@mc.com Virginia 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Acknowledgements MOBILE & PORTABLE RADIO RESEARCH GROUP o Virginia Tech Current and Recent Sponsors and Affiliates in SDR and Smart Antennas ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ 2 ■ ■ Analog Devices ARO Booz-Allen Hamilton CIA DARPA DRS Technologies DRT General Dynamics Huawei Magnolia Broadband Mercury Computer MPRG Affiliates ONR NSF Motorola Qualcomm SBC Laboratories SAIC Samsung Tektronix Texas Instruments VA Tech Bradley Foundation o VA Tech and Other Researchers* oDr. Annamalai Annamalai oDr. Brian Agee oDr. Charles Bostian oDr. Michael Buehrer oDr. Seungwon Choi * oDr. Luiz DaSilva, oDr. Carl Dietrich (assembled presentation) oDr. Steve Ellingston oDr. Robert Gilles oDr. Dong Ha oDr. James Hicks oDr. Allen MacKenzi oDr. Raqib Mostafa oDr. David Murotake * oDr. Jeff Reed,Virginia Tech 1872 VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Acknowledgements (the guys who really did the work) MOBILE & PORTABLE RADIO RESEARCH GROUP oStudents oCarlos Aguayo, James Hicks, Ramesh Chembil Palat, Jong-Han Kim, Youping Zhao, Jody Neel, Albrecht Fehske, Ramakant Komali, Rekha Menon,Vivek Srivastava, Kevin Lau, Samir Ginde, Tom Rondeau, Bin Le, David Maldonado, Philip Balister, Tom Tsou, Chris Anderson, Jina Kim, Lizdabel Morales, Michael Hoseman, kyouwoong Kim, Craig Neely, Christopher Vander Valk, Shereef Sayed And many others…. Virginia 3 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Overview of Presentation MOBILE & PORTABLE RADIO RESEARCH GROUP o Broad Overview of Research Needed and Key Developing Technologies ■ Key Enabling Technologies Needing Further Development ■ Some Developments Worth Noting o Example Research Results from Virginia Tech ■ Smart antennas realization ■ Reconfigurable computing ■ New open source SCA core framework developed and supported at Virginia Tech ■ Power optimizing software radio framework ■ Smart antenna API efforts ■ Development of game theory to analyze cognitive radio networks ■ Cooperative radios ■ Quantifying networking performance of smart antennas implemented with software radio o Concluding Thoughts about the Future Virginia 4 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG A Disclaimer and Request MOBILE & PORTABLE RADIO RESEARCH GROUP o There are many more research areas and excellent researchers doing SDR work not mentioned. o Subsampled research presented here is indicative of what we tend to be more familiar with. (Presentation will be a “mile wide and an inch deep.” o This presentation will be subsampled due to time, but feel free to discuss these issues with me during the conference o Feel free to volunteer information about useful research not mentioned here. Virginia 5 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP Key Enabling Technologies Needed for SDR Virginia 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Key Enabling Technologies 1/3 MOBILE & PORTABLE RADIO RESEARCH GROUP o Antenna Technologies ■ Multi-band/multimode antenna technology ■ Antenna Switching: efficient switching techniques to optimize use of all platform antennas; freedom from oneradio/one-antenna paradigm ■ Co-Site and Electromagnetic Interference Mitigation o Radio Circuits and Power Amplifiers ■ ■ ■ ■ Develop Same Flexibility in Power Amplifiers Antenna-amplifier Arrays Flexible RF and predistortion Efficiency o Software-base Communications Capabilities 7 ■ ■ ■ ■ ■ Portable Waveforms Integrations of FPGAs/DSPs/GPPs/CCM Rapid prototyping Non-waveform Specific Services Middleware Enhancements Virginia 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Key Enabling Technologies 2/3 MOBILE & PORTABLE RADIO RESEARCH GROUP o Network/Spectrum management ■ Totally automated mobile network and spectrum management using adaptive, self-forming, self-healing approaches ■ Shared Use Spectrum ■ MANET Services ■ Network Management o Transceivers ■ Advanced technology to combine transceiver channels into a multi-channel module o Power and Cooling ■ Power reduction/management technologies for handheld and other small form factor sets ■ Cooling technologies to permit high density electronic component use ■ High capacity battery technology Virginia 8 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Key Areas 3/3 MOBILE & PORTABLE RADIO RESEARCH GROUP o Security/Information Assurance (IA) ■ Multi-Level Security Architectures ■ Combination of INFOSEC and Key Management functions into a single element; advanced Cryptographic solutions to integrate these functions in a single chip ■ IA Methodologies and applications and Internet Protocol Encryption (HAIPE) ■ High-data-rate Encryption o High Speed and Low Power Processors and Digital Components ■ Faster Processing for High Speed Waveforms and Cryptography ■ Custom Computing Machines ■ Low Power FPGAs ■ Superconducting Components ■ Use of Common Components/Modules Across Platforms Virginia 9 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP Software Radio Software Research Topics Overview of internal research topics to promote info sharing and discussion of common interests: ■ ■ ■ ■ ■ ■ ■ Dynamic resource utilization Improved test Security Waveform building blocks Components for heterogeneous programming Research to increase levels of commerciality DIF Virginia 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG 1. Dynamic Resource Utilization MOBILE & PORTABLE RADIO RESEARCH GROUP o Deployment and Configuration of Components update ■ Incremental planning pattern for deployment on the fly  Query/acknowledge to identify and quantify resources on shared nodes ■ Existence proof of COTS SCA adaptation o High availability persistent waveforms o Partially reconfigurable heterogeneous components Virginia 11 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY Dynamic Resource Utilization for Increased Reprogrammability MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP Today’s Technology The Future… Cluster A Waveform/ Waveform/ Prog. Modem Modem Waveform/ Prog. Receiver Waveform/ Reconfig Channel Waveforms Within Fabric Up/down Conversion within Fabric Waveform Air prog. Static Config & Plan Virginia 12 1872 Dynamic Deployment, Plan & Reconfig Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG 2. Improved SDR Validation MOBILE & PORTABLE RADIO RESEARCH GROUP o Secure test (see next page) o Improved JTAP for behavioral portability o System and complex waveform test ■ Co-site/channel interference ■ Scaleable to 35GHz wideband waveforms ■ Scaleable to multiple waveforms ■… Virginia 13 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG 3. Security-related research MOBILE & PORTABLE RADIO RESEARCH GROUP o Resolution of NSA/JTRS Security Supplement update and version community is working towards o Completion of OMG/SBC Security spec suite and resolution with JTRS plans o The form of future JTeL secure API and waveform test o Novel “hacking” protection schemes o Unification of MILS/programmable crypto and OTS fabric/backplane solutions o “Softer”, more flexible crypto approaches Virginia 14 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG OMG/SBC Security Suite MOBILE & PORTABLE RADIO RESEARCH GROUP Virginia 15 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY 4. “Softer” Waveform Specification and (Re)Generation MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP • Characteristics can be realized in 7 OSI layers • Layers of characteristic realized as SCA components • Layer parts gathered from multiple waveforms & reused to compose a waveform protocol stack • Layering of components transparent to the SCA CF • Deal with only the Waveform channel but extendable to info proc and IO channels C h a r a c t e r i s t i c p a r a m SDR equipment Session Transport Network Link Physical Software Software Software Software Presentation Software Software Session Software Presentation Transport Software Software Network Software Application Link Software Application Application Application Physical Software Symbol streams Antenna From École de technologie supérieure, Jean Belzile Hardware Hardware Hardware Hardware Hardware Hardware Hardware Hardware Hardware Hardware Hardware Hardware 16 J. Smith, J. Kulp, M. Bicer, T. Demirbilek , "SDR – "Do You Care to Buy the Softest?", Mobile Communications and Military Transformation, March 2003, Washington, DC. Symbol streams Hardware IO channels OS Characteristic type Protocol stack Software Protocol stack r ye a IL Info proc channels Waveform channels Virginia 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP 5. Components for Heterogeneous Processing o Treat FPGA/DSP as GPP-based SCA component ■ Component portability implementation/existence proof – SCA 3.1 ■ Resolution of above with extensions of SCA 3.0 o Addressing portability in the face of SoC and highly integrated ASICs ■ Exploitation of larger granule waveform HW o Hierarchical waveform design (see #4) exploitation Virginia 17 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG 6. Research to Increase Level of Commercialization (and reduce test) MOBILE & PORTABLE RADIO RESEARCH GROUP o Applicability of defense waveforms to defense requirements ■ Incorporation/unification with OBSAI, CPRI and 3GPP, 3GPP2 framework, modeling, security, component and network standards o Research to increase level of COTS ■ Improved CORBA  Zero-copy, high performance transport, streaming support, LwCCM, data-parallel, … ■ COTS component model underlying SCA component model  LwCCM, Compare, DANCE, Component Portability spec, … ■ D&C common denominator between platforms, frameworks and tool providers Virginia 18 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP COTS Component Shared-Radio Infrastructure Current view of many defense non-radio applications Applications Domain specific framework SCA-friendly architecture coexistence with multiple domains - multimission SDR and non-SDR Applications (incl. SCA compliant ones) Lighter-weight* Next Generation SCA CF DS Infrastructure D&C layer HW Platform HW Platform Virginia 19 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG 7. Improved Modeling and Simulation Requirements MOBILE & PORTABLE RADIO RESEARCH GROUP Other Alternatives Waveform Specification Automated Process Formally Validatable Other Alternatives Waveform Implementation Automated Process o Portable behavioral and HW models/test ■ EUML, unification of signal flow and UML CASE tools, … o Composable waveform parts o MDA approach for SDR specs ■ HW abstraction ■ Compare ■ OMG/SDRF/JTRS unification 20 Virginia 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP 8. Expand Interface Portability into Digital IF Realm o Standard interface and data fusion for high bandwidth streams o Unification of Vita 49 and upcoming OMG submittal o Anticipate WB Digital trend Synthesizer Digital IF Interfaces (a) Synch (b) Control, Status (c) Rx DATA + Status (d) Tx DATA + Control VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY (e) Control, Status Virginia 21 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP Noteworthy Research Results (non-Virginia Tech) o RF and Antennas – Dumb and Smart o Processor Technology o Software o Adaptive Networks o Cognitive Radio Virginia 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Reconfigurable Antennas MOBILE & PORTABLE RADIO RESEARCH GROUP o Antennas are usually fixed for specific bandwidth and carrier frequency  Needs Reconfigurable Antenna for flexibility o Reconfigurable Antennas ■ Multiple antenna-RF chain : Simple but Large Form Factor ■ Single wideband antenna-RF chain : Fail to provide adequate performance due to its low-Q design ■ Reconfigurable antenna-RF chain with MEMS Virginia 23 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP RF and Antennas – Dumb and Smart Virginia 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MEMS Designs for RF Front Ends MOBILE & PORTABLE RADIO RESEARCH GROUP E-tenna’s Reconfigurable Antenna o Tunable antenna with narrow fixed bandwidth o Patch antenna connected by RF switches Idealized MEMs RF Front-end for a Software Radio o Use MEMS filter banks to create tunable RF filters Virginia 25 J.H. Reed, Software Radio: A Modern Approach to Radio Design, Prentice-Hall 2002. 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP MEMS for Reconfigurable Antennas and RF - I o Advantages of MEMS ■ Low phase noise Voltage Controlled Oscillators (VCO) by using MEMS-based high Q resonators ■ Wideband varactors and phase shifters by using MEMSbased variable capacitors and switch-capacitor networks ■ Tunable filters by employing MEMS-based variable reactive elements and switches Virginia 26 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP Reconfigurable Antennas with MEMS - II o Reconfiguring Antenna with MEMS (A) (B) Application of MEMS switch for reconfigurable antenna (A)f_ant = fc (B) f_ant = 2*fc Virginia 27 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Antenna Array - I MOBILE & PORTABLE RADIO RESEARCH GROUP o Antenna Array Processing ■ Antenna array processing can achieve higher data rate and more capacity ■ Allows diversity techniques, MIMO, Distributed MIMO and beamforming algorithms  Smart Antenna ■ Software radio and Smart antennas complement each other well SDR provides the flexibility needed for effective smart antenna, and smart antennas provide the benefits that motivate the adoption of SDR Virginia 28 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Antenna Array - II MOBILE & PORTABLE RADIO RESEARCH GROUP o Switching waveforms in Adaptive beamforming ■ Switching waveforms in “SDR” adaptive beamforming requires significant dataflow changes  arise interconnection problem  Increase complexity  switched fabric CAN solve problems Data flow implementation of a subtractive co-site interference management systems is typically of complexity [i x j] for a system with i transmitters and j receivers. Use of a single 8-port crossbar switch (right) can reduce the “fan-out” to complexity [i + j], reducing both pin and wire counts [Source:SCA Technica Inc] Virginia 29 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG RF and Analog - I MOBILE & PORTABLE RADIO RESEARCH GROUP o Superconducting components for SDR ■ Enable wide BW, high linearity, and high dynamic range ■ Microelectronic device can operate up to 100GHz  Permit direct AD/DA conversion at RF level  Increase flexibility by putting whole system under SW control ■ Possible RF level predistortion  Remove delays in Mod/Demod to use BB level predistortion  Fast enough to correct instantaneous fluctuation ■ Superconducting circuits require operation at cryogenic temperatures, typically at 4 K (-269 °C)  Need Cryogenic Cooler (CryCooler)  Now Crycooler commercially available ■ Much of this effort by Hypress, Inc. Virginia 30 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG RF and Analog - II MOBILE & PORTABLE RADIO RESEARCH GROUP o Amplifiers ■ SDR has to support multi-mode radio subsystem.  If the radio subsystem is common for various radio standards, then SDR will be more simplified. ■ Polar modulator has almost same structure for FDMA, CDMA, and TDMA  Possible single transmitter for various modulations  Adequate for SDR ■ Exploits AM-AM and AM-PM characteristics of PA ■ Converts quadrature into polar signal using CORDIC algorithm (COrdinate Rotation DIgital Computer) ■ Apply Separated predistortion for AM and PM  Go through Amplitude modulation and Phase modulation  They are recombined before PA ■ Several different wireless standards of different bandwidths and modulations on a single amplifier while achieving acceptable performance. Virginia 31 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY RF and Analog - II MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP I Data DATA Generator (Filter) Q Rc Rectangular to Polar CORDIC Converter c AM to AM R PreDistortion Amplitude Modulator  Phase Modulator AM to PM PreDistortion Power Drive PA VCO RF Simplified Polar Modulator Block Diagram [Source : Wendell B. Sander, Stephan V. Schell, Brian L. Sander, “Polar Modulator for Multi-mode Cell Phones”. Tropian, Inc.] Virginia 32 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY RF and Analog - III MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP VCO RF buffer C-PA T/R switch VCO RF buffer C-PA duplexer I I polar Mod. polar Mod. Q Q RF reference (A) to RX RF reference to RX (B) A) A polar transmitter block diagram for half-duplexsystems (e.g. GSM, TDMA) radio systems B) A polar transmitter design for full duplex radio systems, with extended PA dynamic range for CDMA operation [Source : Earl McCune , “SDR RADIO SUBSYSTEMS USING POLAR MODULATION”. Tropian Inc.] Virginia 33 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP Techniques for Improving RF Device - I o Zero-IF and Near-Zero-IF Quadrature Receivers ■ Zero IF : Achieves low cost and small size solutions ■ Near Zero IF : can avoid the DC offset and mixer self-mixing problems while achieve high integration level and low cost implementation ■ They are suitable to multi-band/multi-mode communications devices and are favorable options for a practical implementation of Software Defined Radio. Problem of ZIF and NZIF ■ Problem : Sensitive IQ imbalance due to many amplification and filtering stages in both I and Q ■ IQ balancing technique is required  With the IQB technology, ZIF and NZIF quadrature receivers will no longer suffer from I-Q imbalance  become more favorable and feasible solutions to low-cost radio front-end for SDR Virginia 34 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP Techniques for Improving RF Device - II o Central Processing / Remote RF ■ Developments in optical technology allow the conversion of RF signals to light and their transport via fiber optics with very low loss and distortion, and by the expansion of fiber networks in urban areas.  Called RF-on-Fiber (RoF) technology. ■ Provides significant flexibility in upgrading functionality, and implementing various wireless standards and air interfaces  Consistent with goal of SDR approach Virginia 35 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY Techniques for Improving RF Device - RoF MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP Laser Fiber Photodiode RF in/out Diplexer Diplexer Photodiode Laser Fiber Central Office Access Point Typical RoF Link [Source: Emanuel Kahana, Mike Baker, Alek Tziortzis , “CENTRAL PROCESSING / REMOTE RF” FOR CELLULAR NETWORKS, USING OPTICAL MICROCELLS: CONCEPT AND PERFORMANCE”. Motorola] Virginia 36 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP Processor Technology Virginia 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Objective MOBILE & PORTABLE RADIO RESEARCH GROUP o Look at existing reconfigurable architectures for wireless communication (mobile and base station) o Discuss advantages and disadvantages of each architecture o Draw conclusions to aid RM design o Architectures reviewed: ■ PactXPP ■ Quicksilver ■ Morphosys ■ Elixent ■ Intel ■ Montium (University of Twente) 38 ■ DRAW (Ohio Univeristy) Virginia 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Different Types of Reconfigurable Designs MOBILE & PORTABLE RADIO RESEARCH GROUP o Reconfigurable logic: ■ Variable logic and variable data routing  Eg. combination of CLBs in FPGA o Reconfigurable datapath: ■ fixed logic and variable data routing  Eg. MUXs and Registers o Reconfigurable arithmetic: ■ Limited choice of arithmetic operations and fixed data routing  Eg. ADD, SUB, ACC, as in CPU design o Reconfigurable control: ■ variable control signals, limited choice of data routing  Eg. Instruction decoder and datapath controller Virginia 39 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Characteristics of reconfigurable architectures MOBILE & PORTABLE RADIO RESEARCH GROUP Reconfigurable Fabric Datapath Reconfiguration Control Datapath Data Flow PactXPP Dynamic From MPU Configurable Buffer Quicksilver Dynamic Decentralized Configurable Buffer MorphoSys Dynamic From a MPU Configurable Buffer Intel N.A. Reconfigurable fixed Buffer Elixent Dynamic From MPU Configurable Buffer Montium Dynamic From MPU Configurable Stream DRAW Dynamic Hierarchical Configurable Buffer Stallion Dynamic Packet based Configurable Stream Virginia 40 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Guidelines for Reconfigurable Modem (RM) design (1/3) MOBILE & PORTABLE RADIO RESEARCH GROUP o Reconfiguration: ■ Datapath based  Static reconfiguration – datapath does not change at run time – RF works like an ASIC with hardwired interconnection – RM design will require large amount of computational resources – Less flexibility  Dynamic reconfiguration – datapath changes during run time – More resource reuse – Control and data routing become complex – More operations in temporal domain results in higher flexibility o Dynamic reconfiguration more suitable for RM mobile solution Virginia 41 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Guidelines for RM design (2/3) MOBILE & PORTABLE RADIO RESEARCH GROUP o Processing Element structures ■ Chip rate Ops  ALU based PE designs not efficient with respect to speed, power, resource utilization and cost ■ Viterbi / Turbo for data application  Need special units for ACS and traceback operating at higher frequency ■ Fine grain     increases flexibility Efficient logic implementation Routing and control difficult More reconfiguration time ■ Coarse grain:     use ALUs routing and control easier lesser flexibility Requires more power o RM design will need a combination of fine grain and coarse grain PEs Virginia Tech 42 1872 VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Guidelines for RM design (3/3) MOBILE & PORTABLE RADIO RESEARCH GROUP o Control: ■ FSM node based decentralized  Routing width proportional to complexity and flexibility  Compiler design can become complex ■ DSP / CPU based  Generation of control signals easy  Can execute some generic code on DSP o Data transfer: ■ Using buffer  eases multiple clock requirements  Can have multiple modules running at a higher synchronous clock rate with variable buffer depth  Suitable for multiple data rate systems Virginia 43 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP Software Virginia 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG CRC SCA Implementation MOBILE & PORTABLE RADIO RESEARCH GROUP o CRC (Communications Research Centre) o Technical scope ■ SCA v 2.1 (2.2 under SDR Forum sponsorship) ■ Java ■ 60000 LOC, 300 pages of documentation o Highly successful reference implementation ■ 7000+ downloads (2003) ■ 34000+ hits on web site (2003) o Check it out 45 Virginia http://www.crc.ca/en/html/crc/home/home Tech 1872 VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Creating a Lightweight SCA MOBILE & PORTABLE RADIO RESEARCH GROUP o SCA is a widely accepted architectural framework that is rapidly evolving with each new version o SCA is comprehensive and includes all the operating domains of SDRs  o Problem where resources are limited in mobile devices Lightweight implementations of the SCA is required Virginia 46 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Lightweight SCA MOBILE & PORTABLE RADIO RESEARCH GROUP o Focuses on two primary aspects ■ Lightweight services  Logging, Naming, Event ■ Lightweight CCM (CORBA component model) o Other approaches have been suggested ■ Transform application metadata for COTS deployment (Mercury Computer) Virginia 47 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Lightweight SCA Concerns MOBILE & PORTABLE RADIO RESEARCH GROUP o Unclear what the relative benefits of such approaches will be ■ Reduced memory footprint  Attempt to minimize HW aspect that is consistently less pressing ■ Reduce computational load  Relevant only for waveform transitions – Affects boot-up and load times o Is power consumption a better metric for determining “lightweight”? Virginia 48 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Software Download - I MOBILE & PORTABLE RADIO RESEARCH GROUP o Over-the-air-programming: SDR system can reconfigure itself by downloading applications and protocols o Security of downloaded SW ■ The security of downloading SW is key issue ■ Standard download procedures: initiation mutual authentication  capability exchange  testing  nonrepudiation exchange o Download channel issues ■ Download channel can increase interference level  Problem in interference limited system ■ Common Channel : Broadcasting channel  Good for group of mobile  Fast power control is not possible ■ Dedicated Channel: Good for fewer mobile  Fast power control is possible o Status of SDR Forum efforts Virginia 49 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Software Download - II MOBILE & PORTABLE RADIO RESEARCH GROUP [Source: General Dynamics Decision Systems] Virginia 50 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Software Download - III MOBILE & PORTABLE RADIO RESEARCH GROUP [Source: General Dynamics Decision Systems] Virginia 51 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP Adaptive Networks Virginia 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Adaptive Networks - I MOBILE & PORTABLE RADIO RESEARCH GROUP o The capability to alter its behavior is one of the attractive features of software radio  possible to adapt networks to changing conditions in a way that optimized performance o Requires two steps for realization ■ Development integration of link adaptive algorithms ■ Development network adaptive algorithms o DARPA xG project ■ A new spectrum access behavioral regime consisting of technologies that sense, characterize, and utilize spectrum opportunities in an interference-limiting manner. ■ A new regulatory control regime consisting of methods and technologies for controlling such opportunisticspectrum access behaviors in a highly flexible, traceable manner using machine understandable policies. Virginia 53 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY xG Project MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP TRANS TRANS NET NET XG MAC PHY XG MAC PHY Freq. Assign. Spectral Occupancy Legacy MAC to MAC Figure 2 XG Layer Network Interaction o Physical Layer detects MAC request related XG layer  MAC request is pending  XG layers exchanges spectrum utilization  Coordinate frequency assignments  Pended MAC request is exchanged. Virginia 54 o http://www.darpa.mil/ato/programs/xg/rfc_vision.pdf 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Adaptive Networks - II MOBILE & PORTABLE RADIO RESEARCH GROUP o Requires extra signaling to support adaptation as shown xG o Modulation Identification can eliminate extra signaling ■ Use multi-mode PLL : All known modulation types are simultaneously demodulated with the output symbol being determined by the demodulated signal with the lowest error metric. ■ Use all possible Viterbi decoders simultaneously, and choose maximum likelihood output symbols based on the decoding result. ■ Polyphase channelizer: To help identification of which band a signal is present and compares received signals to a known subset of signals with differing carriers and pulse shaping. After picking out the right format, the receiver adjusts its operation appropriately. Virginia 55 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY Adaptive Networks - III MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP o European project OverDRiVE on Dynamic Spectrum Allocation (DSA) RAN 3 RAN 1 RAN 3 RAN 2 RAN 1 RAN 2 RAN 2 RAN 1 RAN 3 RAN 3 RAN 3 RAN 2 RAN 1 RAN 2 RAN 2 RAN 1 RAN 2 RAN 1 RAN 1 RAN 2 RAN 2 RAN 1 RAN 2 RAN 1 RAN 1 RAN 2 RAN 2 RAN 1 RAN 2 RAN 1 RAN 1 Spectrum Allocation ■ Their basic approach : network architecture consisting of functions, entities, components and interfaces objects with DSA requirements are supported by reconfigurable functions. Functions are implemented on entities, which may reflect actual devices or be virtual entities. Time/Region FSA DRiVE DSA OverDRiVEV DSA irginia Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY http://www.comnets.rwth-aachen.de/~o_drive/publications/DSA_and_Reconfigurability.pdf 56 1872 VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP Cognitive Radios Virginia 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Cognitive Radios MOBILE & PORTABLE RADIO RESEARCH GROUP o Cognitive Radio is: ■ Aware of its environment, ■ Aware of its capabilities, ■ Aware of its operating context.  Empowered to adapt its behavior in a way that improves its performance o Key benefit ■ Can cognitive radio enable a system designer to squeeze every Hz out the spectrum  Efficient Spectrum pooling o Major challenges ■ Figuring out how to provide the radio the etiquette ■ Translating the observations into actions ■ How to analyze cognitive radios Virginia 58 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Approach to provide awareness - I MOBILE & PORTABLE RADIO RESEARCH GROUP o Complex Organic Distributed Architecture (CODA) ■ CODA is based on cognitive psychology work performed as part of the CAST (Configurable radio with Advanced Software Technology) project. [Source: Tereska Karran ,”Adaptation in Software Radio using a Complex Organic Distributed Architecture (CODA)”. University of Westminster, London] The CODA intelligence cycle Virginia 59 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY Approach to provide awareness MPRG II MOBILE & PORTABLE RADIO RESEARCH GROUP o Cognition Ontology : specifications of conceptualizations for providing awareness for cognitive radios ■ Provides : A means of obtaining “meaningful” information by defining a language and algorithms for handling queries like, “how many multipaths does the channel have.” Virginia 60 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP Rich Cognitive Radio set of Research Topics o Resilience to network impairments ■ Ad-hoc routing, extreme error conditions, link blockage o Incorporation of knowledge based planning with interoperable knowledge representations and situation assessment o Assessment and validation of situation-aware protocols o Smart agent to build waveform building blocks on fly o … Virginia 61 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP Research at Virginia Tech Virginia 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP Example Research Results from Virginia Tech o SCA core framework ■ ■ ■ ■ ■ Open source effort Role of DSPs Power Management Integration of testing into the framework Rapid prototyping o Smart antennas ■ ■ ■ ■ Overloaded array processing Networking performance Smart antenna API Experimental MIMO systems o Cooperative radios ■ Distributed MIMO ■ Distributed Applications o Reconfigurable computing ■ Early work in steam processing ■ Communications oriented processors o Cognitive radio networks ■ Game theory analysis of cognitive networks ■ Learning Techniques ■ Test Bed Virginia 63 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP SCA Core Framework Virginia 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG SCA Core Framework MOBILE & PORTABLE RADIO RESEARCH GROUP o Open Source Effort o Role of DSPs o Power Management o Integration of Testing into the Framework o Rapid Prototyping Virginia 65 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY Open-Source SCA MPRG Implementation::Embedded(OSSIE) MOBILE & PORTABLE RADIO RESEARCH GROUP o Traditional wireless education focuses on aspects such as circuit design, coding theory, and DSP ■ Graduating engineer is likely to have a limited software background  This is crucial for SDR design o SCA offers powerful architecture for essentials in SDR design o Open Source approach adopted o OSSIE can be downloaded at: http://mprg.org/research/ossie (over 3800 site visits, 800 downloads to date) Virginia 66 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG SCA and Education MOBILE & PORTABLE RADIO RESEARCH GROUP o Two principal problems for use of SCA in universities ■ Relatively complex specifications  Simple sample code is crucial to help in understanding ■ No simple-to-use CF is available in C++  Most EE’s software background is limited to C++ o These problems are shared by entities other than universities o OSSIE (Open Source SCA Implementation::Embedded) was developed to address these problems Virginia 67 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG OSSIE: Development Philosophy MOBILE & PORTABLE RADIO RESEARCH GROUP o Target user is entry-level Electrical Engineering Master’s student ■ Limited time available to reach reasonable level of understanding  Requires relatively simple code ■ Limited knowledge of middleware  CORBA can be overwhelming ■ Research needs require easy access to different pieces of the implementation ■ Must be inexpensive (preferably free) Virginia 68 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG OSSIE: Implementation Overview MOBILE & PORTABLE RADIO RESEARCH GROUP o Attempt to follow SCA 2.2 specifications ■ All relevant classes to support a variety of waveforms are implemented o First version written for Windows XP/2000 using Visual C++ 6.0 ■ Second version for Windows XP/2000 using Visual C++ 6.0 or .NET and Linux o TAO (The ACE ORB) CORBA ■ Use of ACE simplifies OS portability o Xerces C++ XML parser ■ Released under Apache Software License Virginia 69 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG OSSIE: Release Structure MOBILE & PORTABLE RADIO RESEARCH GROUP o Two libraries comprise CF release ■ XML parsing library  Configuration file-specific parsers ■ CF classes  Implementation to some extent of all classes except Aggregate Device  Core application services and non-core applications – Common pieces for non-core application selected • I.e.: UUID provided by constructor or from configuration file Virginia Tech 70 1872 VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG OSSIE: Shared Libraries MOBILE & PORTABLE RADIO RESEARCH GROUP o Important to minimize visible code developer needs to manage ■ Shared libraries reduce the amount of visible code  Simplify the amount of code the developer needs to directly interact with ■ Different approaches can also reduce the amount of needed program memory  Leverage use of dynamic library Virginia 71 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP OSSIE: Coding Structure and Shortcuts o ORB wrapper used to reduce the amount of visible code ■ Minimize the exposure of the developer to the CORBA interface  Can be overwhelming but not directly needed ■ Common calls are simplified  Lookup  Bindobj  getNamingContext ■ Approach based on the use of single static ORB Virginia 72 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG OSSIE: Limits on Implementation MOBILE & PORTABLE RADIO RESEARCH GROUP o Implementation based on simplicity and readability ■ Missing pieces considered important in commercial implementations  Exception handling  Aggregate Device (not necessary for target implementations) ■ Missing exception handling can be an asset  Forces developer to explore CF implementation – XML debugging  Implementation is likely to operate in controlled environment 73  Exception handling can be added with relatively low Virginia Tech effort 1872 VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG OSSIE: Development Path MOBILE & PORTABLE RADIO RESEARCH GROUP o OSSIE useful in basic R&D ■ Inside and outside University environment o VT committed to open-source C++ release philosophy ■ Download available: www.mprg.org/research/ossie o Several planned improvements ■ More complete framework ■ Advanced waveforms ■ Research-related contributions  Power management  SCA 3.0 o Eventual goal is to achieve JTEL certification Virginia 74 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG OSSIE: Vision MOBILE & PORTABLE RADIO RESEARCH GROUP Industry Contributed Code Accelerated Research Virginia Tech Academy Accelerated Research, Education Code OSSIE Improved Architectures Government Accelerated Research Improved Standards Contributed Code Improved Design Techniques Research Results Tools MPRG SDR Research Education Graduate Undergraduate Component Libraries (e.g., MIMO, FEC) Accelerated Research Networking Cognitive Radio SDR Hardware UWB MIMO Propagation Future Research Directions Virginia 75 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG OSSIE: Acknowledgements MOBILE & PORTABLE RADIO RESEARCH GROUP o Largely unpaid volunteer effort by a group of dedicated graduate and undergraduate students o Sources of direct or indirect funding ■ DCI Postdoctoral Research Fellowship ■ Office of Naval Research ■ Science Applications International Corporation (SAIC) ■ Tektronix ■ Texas Instruments ■ MPRG Affiliates Program o CRC’s reference implementation Virginia 76 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Example OSSIE Waveform MOBILE & PORTABLE RADIO RESEARCH GROUP o o o o o o o Simultaneous demodulation of 16 DRM channels One PC dedicated to high speed data acquistion Three PC's dedicated to DRM decoding All processing in software Homemade HF RF front ends Complete radio made in less then six months Cycles bound in DRM decoding, not CF Virginia 77 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Role of DSPs -- Project Goals MOBILE & PORTABLE RADIO RESEARCH GROUP o Study ways of using TI DSPs, to implement light, power-efficient SDR based on the SCA o Demonstrate that a SDR implemented using a multi DSP platform can utilize the great power/cost/performance characteristics of DSPs o Gain insight into the compatibility of TI DSPs with the SCA architecture o Identify non-framework factors that might impact these tradeoffs Virginia 78 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Project Description MOBILE & PORTABLE RADIO RESEARCH GROUP o Develop a Wideband Code Division Multiple Access (WCDMA) waveform for a Multiprocessor C64x platform (fine details of WCDMA not implemented) o When Mercury’s new platform becomes available, the same waveform will be ported to it and its performance will be evaluated Virginia 79 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Power Management For SDR MOBILE & PORTABLE RADIO RESEARCH GROUP o SDR places challenges different from classic communications system ■ Can support waveform swapping ■ Needs to support wide set of devices  Variety of needs and states – Difficult to narrow to small, well-defined set of states o Requires sophisticated power control structures ■ Applications can be more predicable than PC  Possible to determine “fast enough” speed – Blind throttle for the waveform may not be enough Virginia 80 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY Power Management: State Support MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP o Advanced Configuration and Power Interface (ACPI) is the current standard for PC power management ■ ACPI supports mesh state machine  Assumes basic device states can be throttled S1 S2 Sn  Linear transitions (throttle) are a subset of the mesh state machine S1 S2 Sn Virginia 81 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP Power Management: Problems with Mesh SM o Assumes that all transitions are fundamentally “equal” ■ Does not take into account QoS for power management issues related with state change o Example: ■ Voltage and frequency are fundamentally linked  Increased voltage will allow a higher set of frequency settings to be supported – Throttle transitions based on the assumption that lowest possible voltage is supported for the desired frequency – If a change in voltage incurs a higher time delay in switching state than a change in frequency, could lead to unplanned additional latencies Virginia 82 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY Power Management: Rate-Change Support in Communications MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP o Example (802.11b): ■ Support alternate processing speeds for different sections of received frame PLCP Prefix PLCP Payload 11Mbps PSDU 1Mbps (Preamble+Header) CW typically ~400us Transition Transition Processing 192us Fast Slow ■ Benefits 83 Decision point: discard frame?  Minimizes required computing power  Provides ability to discard frame before high-speed processing is necessary Virginia Tech 1872 VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP Power Management: Rate Change and SDR o Waveform takes place of “user” in SDR ■ Latencies associated with change of state need to be taken into account  State switching needs to be in order of microseconds – Millisecond-level switches may be too slow for some waveforms  Ideally, should cluster state changes into transition state o Example: ■ Crusoe TM5400 automatically controls voltage and frequency settings  Slow ramp in voltage for up-frequency changes followed by fast frequency change  Fast down frequency change followed by slow voltage change  Changes performed automatically – Possible for some equipment to leave change requests up to the application ■ Voltage regulator can have a significant impact on the transition speeds in core operating voltage  May be too slow (ms+) for some waveforms Virginia 84 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP Power Management: State Machine Description o Break down state machine into slow-change states and related fast-change states ■ Provides application with ability to change states quickly during waveform operation F1,1 F1,2 F1,3 V1 F2,1 F2,2 F2,3 V2 F3,1 F3,2 F3,3 V3  Also supports sleep or standby operation Virginia 85 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP Power Management: Sample Operation o Fast operation ■ Can cycle between 500 and 700 MHz 500 600 700 1.8V 300 400 500 1.5V 100 200 300 1.2V  500 MHz may be more efficient at 1.5V – May choose not to transition, since change to 600 or 700 MHz expected soon o Can still transition to lower powers ■ Support significantly lower power consumption levels o Same concept can apply to other devices ■ FPGAs, ASICs, CCMs, DSPs Virginia 86 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP Power Management: Common Interface o Design of common interface will have to wait until conceptual framework is finalized ■ Will rely on ACPI to determine appropriate interfaces  Will also rely heavily on SCA 3.0 interface specifications – SCA 3.0 concentrates on non-CORBA interface descriptions ■ Challenging task  Generic nature of hardware makes static definition of interfaces unlikely – Will most likely require a generic structure • May be able to leverage AML Virginia 87 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Application-Level Power Management MOBILE & PORTABLE RADIO RESEARCH GROUP o Algorithm development ■ Field of research currently has large number of contributions  Primarily concentrating on PC-based systems – ACPI/OSPM ■ Clear from Operating Environment Power Management (OEPM) that SDR will have some unique characteristics  Optimization strategies will be based on the permutations possible by conceptual framework  This research venue cannot proceed until conceptual framework is complete Virginia 88 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Power Management Summary MOBILE & PORTABLE RADIO RESEARCH GROUP o Some concepts in power management are fairly mature ■ PC power management ■ Voltage and frequency scaling ■ Policies and algorithms o Current state-of-the-art does not cover all needs of SDR ■ Unique issues related to nature of SDR o Actively developing techniques to resolve these issues Virginia 89 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Acknowledgement MOBILE & PORTABLE RADIO RESEARCH GROUP o This work is funded by the DCI Postdoctoral Research Fellowship and the MPRG Affiliates Program Virginia 90 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP Integrating Test Equipment Into the SCA to Design and Test Software-Radios Dr. Jeffrey H. Reed Dr. P. Max Robert Carlos Aguayo Mobile and Portable Radio Research Group (MPRG) Bradley Dept. of Electrical and Computer Engineering 432 Durham Hall, MS #350 Virginia Tech Work made Blacksburg, VA 24061 (540) 231 2958 gift from mprg@vt.edu http://www.mprg.org possible by a Tektronix Virginia 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Test and Validation of SDR MOBILE & PORTABLE RADIO RESEARCH GROUP o SDR is a relatively new technology ■ The term SDR was coined in 1992 ■ The first user-led field evaluation for any JTRS production representative hardware was held on Sept. 17, 2004 (Cluster 2 Handheld EOA) o The same hardware platform must support multiple bands and modes ■ JR GVR (Ground vehicular, rotary wing, TACP) (Formerly Cluster 1) will provide capability to store up to 10 waveforms ■ Each waveform has to be tested/validated Virginia 92 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Integrating Test Equipment MOBILE & PORTABLE RADIO RESEARCH GROUP o Test equipment can be leveraged to provide an integrated solution for SDR test and validation by integrating it into the SCA o Provides an embedded resource to analyze and verify the correct operation of SDR Waveform Component Waveform Component Waveform Component Wrapper Logical Software Bus via CORBA ORB & CF OS Network Stack Bus Layer Virginia 93 Hardware Bus 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP Advantages of Integrating Test Equipment o Allows for a modular design strategy (seamless transition from simulation to deployment) ■ Simulated components -> Test equipment implementation -> Final version o Allows better isolation of HW and SW components to pinpoint bugs and error sources o Facilitates production-line validation of SDR o Provides a new dimension of built-in tests by expanding the capabilities of the TestableObject interface Virginia 94 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MPRG Approach MOBILE & PORTABLE RADIO RESEARCH GROUP o Create wrappers around Tektronix test equipment (Arbitrary Waveform Generator & Real-Time Spectrum Analyzer) to integrate them into OSSIE o LoadableDevice interface was used for the adapters o Successfully integrated AWG430 & RSA3308A into a sample waveform o For more details refer to: http://www.tek.com/Measurement/App_Notes/37_18369/eng/37W_1 8369_0.pdf Virginia 95 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Future Test and Validation of SDR MOBILE & PORTABLE RADIO RESEARCH GROUP o There is still debate about correct implementation and validation approaches for SDR o As more SDR implementations start emerging, the advantages of integrating test equipment into the SCA will be more evident. o In future cognitive radio scenarios, where radios are allowed to ‘learn’, having integrated test equipment will be almost a necessity Virginia 96 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Project Hierarchical Structure MOBILE & PORTABLE RADIO RESEARCH GROUP WCDMA Components at MPRG Other TI Code WCDMA Waveform New Components OSSIE TEXAS INSTRUMENTS C64 C64 C64 C64 Compare Performance Mercury’s Platform Virginia 97 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY Waveform Development is not so Easy MPRG and Rapid Prototyping Tools are Needed MOBILE & PORTABLE RADIO RESEARCH GROUP o Multi-domain systems, analog-digital design o Wide and Multiband systems (ADCs, VCOs, Power Amplifiers) o Complex filters (configurable, tunable, efficient) o Increasingly complex algorithms o 30-40 military standards. 20-30 commercial standards o Code has to be developed for efficient, hybrid platforms ■ Simple, computationally intensive algorithms => FPGAs ■ Mathematically-intensive portion of the system => DSPs Virginia 98 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Traditional Development Approach MOBILE & PORTABLE RADIO RESEARCH GROUP o The traditional design approach uses separate tools for the DSP and FPGA ■ IDE with JTAG support for the DSP ■ VHDL tool suite for the FPGA. o Implementation is typically performed by separate engineering teams o Full evaluation of the system cannot be performed until a custom prototype is built late in the process Virginia 99 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Importance of Development Tools MOBILE & PORTABLE RADIO RESEARCH GROUP o Development time can be reduced by reusing simulation code to generate working code o In SDR, source code often outlives platform ■ New FPGA Architecture every 12-18 months o Platform for initial design may not be the same for deployment o The use of the right tools can improve waveform reusability and lead to rapid prototyping and faster time-to-market Virginia 100 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Existing Tools MOBILE & PORTABLE RADIO RESEARCH GROUP o There are not many tools to develop SDR at this time o Mathworks’ SimulinkTM is a platform for modelbased design and multidomain simulation o It is integrated with MATLABTM. The leading software tool for DSP algorithm development www.mathworks.com Virginia 101 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Simulink Features 1/2 MOBILE & PORTABLE RADIO RESEARCH GROUP o Interactive block diagram simulation tool o Graphic, intuitive design and simulation of the system o Extensive and expandable libraries of predefined blocks o Fills the gap between Waveform Requirements Specification and Platform-Specific Model Virginia 102 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Simulink Features 2/2 MOBILE & PORTABLE RADIO RESEARCH GROUP o C code generation using Real-Time WorkshopTM ■ Embedded target for TI C6000 o VHDL code generation for FPGA using Xilinx System GeneratorTM for DSP o Companies such as Lyrtech are using this set of tools to rapid prototype their designs MATLAB Simulink RTW TI Code Composer Studio TM Hardware V Platform irginia Tech 103 www.lyrtech.com 1872 VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG There is Still Work to Do MOBILE & PORTABLE RADIO RESEARCH GROUP o The code and components generated by these tools are not complete from an SCA stand point o If SCA compliance is desired, the actual code for deployment and configuration still has to be performed manually, o Even when all components are ready and functional there is still work to do with the Domain Profile (XML configuration files) o Developing the Domain Profile without the appropriate tools can be a painful experience and an important source of waveform errors o There are no existing tools to automatically generate profiles for SDR Virginia 104 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP By Leveraging the Appropriate Tools, It is Possible To: o Create a uniform framework for rapid prototyping SDR and exploring new algorithms and concepts o Perform a seamless design from simulation to hardware realization o Rapidly prototype FPGA and DSP subsystems o Minimize initial and recurring cost for design system o Leverage commercial tools, but with proprietary advantage Virginia 105 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP SCA Rapid Prototyping Approach o Leverage Virginia Tech’s Open Source Software Communication Architecture (SCA) o Leverage Mathworks SimulinkTM o Create “wrappers” around DSP and FPGA code created with Real-Time Workshop and System Generator for DSP o Design and implement tools for automating XML configuration files o Create tools for benchmarking implementation Virginia 106 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY SCA Rapid Prototyping MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP MATLAB Simulink System Behavior Modeling and simulation RTW SCA Compliance “Wrappers” Automatic XML Profile Generator 107 Code Generation Hardware Platform Comp y TI Code Composer Studio TM Comp x SCA Software Radio SCA Waveform OSSIE Virginia 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP Differences from traditional Development Approach o Allows early testing of the design and faster iterations o Does not require expertise in the target system o Lets developers pinpoint sources of error even in complex hybrid systems o Gives the flexibility to vary system parameters and verify the effects produced on the system in real-time Virginia 108 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP Advantages of an SCA Rapid Prototyping Approach o Seamless transition from simulation to SCA compliant implementation o Expanded lifespan of source code o Increased reusability and portability of components o Easier test and debugging o Powerful tool to validate new algorithms and technology concepts Virginia 109 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Rapid Prototyping MOBILE & PORTABLE RADIO RESEARCH GROUP o Provide a structure for the integration of rapid prototyping with current SCA architecture ■ Allow integration of additional computing HW  DSP, FPGA ■ Reduce development cycle for new systems ■ Increase code reuse o Several aspects must be resolved ■ Simulation to development path ■ Development tools Virginia 110 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG SCA Rapid Prototyping Benefits MOBILE & PORTABLE RADIO RESEARCH GROUP o Uniform framework for rapid prototyping SCA systems o Support a seamless design path from simulation to hardware realization o Rapidly prototype FPGA and DSP subsystems o Minimize initial and recurring cost for design system o Leverage commercial tools to create custom solutions Virginia 111 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Existing Rapid Prototyping Tools MOBILE & PORTABLE RADIO RESEARCH GROUP o There are not many tools to develop SDR at this time o MathWorks Simulink® is a platform for model-based design and multidomain simulation o Integrated with MATLAB, the leading software tool for DSP algorithm development www.mathworks.com Virginia 112 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Existing Rapid Prototyping Environment MOBILE & PORTABLE RADIO RESEARCH GROUP o C code generation using Real-Time Workshop® ■ Embedded target for TI C6000 o HDL code generation for FPGA using Xilinx System Generator™ for DSP o Companies such as Lyrtech are using this set of tools to rapid prototype their designs 113 MATLAB Simulink RTW TI Code Composer Studio TM Hardware V Platform irginia Tech www.lyrtech.com 1872 VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG SCA Rapid Prototyping Approach MOBILE & PORTABLE RADIO RESEARCH GROUP o Leverage MathWorks MATLAB and Simulink® o Support commercial tools through software wrappers ■ Real-Time Workshop® for DSP ■ Xilinx System Generator™ for FPGA o Design and implement tools for automated generation of XML configuration files o Develop debugging and benchmark tools Virginia 114 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY SCA Rapid Prototyping MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP MATLAB Simulink System Behavior Modeling and simulation RTW SCA Compliance “Wrappers” Automatic XML Profile Generator 115 Code Generation Hardware Platform Comp y TI Code Composer Studio TM Comp x SCA Software Radio SCA Waveform OSSIE Virginia 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP Smart Antennas Virginia 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Smart Antennas MOBILE & PORTABLE RADIO RESEARCH GROUP o Overloaded array processing o Networking performance o Smart antenna API o Experimental Systems Virginia 117 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Overloaded Signal Environment MOBILE & PORTABLE RADIO RESEARCH GROUP M-element Array Rx. front end x1 (t ) o Overloaded Array: more signals than elements. o Conventional Array Processing breaks down. xd (t ) r0,1 (t ) xDu (t ) r0,M (t ) D  M u Num. Sigs. o Can extract signals from the environment if can exploit known signal properties. o OLAP hardest when all signals are cochannel, have little excess bandwidth (e.g. narrowband) and are nearequal power. Num. Elements. Virginia 118 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY Overloaded Array Scenario MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP  Example: Airborne communication node is under consideration by commercial and military organizations.  Communications in Disaster Relief Scenarios  Military Communications  Developed Spatially Reduced Search Joint Detection (SRSJD) Algorithm capable of OLAP in twice-overloaded environments Airborne communication system employing an antenna array Cellular airborne base-station or a cellular repeater Overloaded array Interfering base stations in the case of an airborne repeater (base station-repeater link) Intra-system CCI Desired LOS component External CCI Interfering base stations 119 Commercial TV / Radio stations desired mobile user Co-channel Interfering Virginia desired mobile user Mobile Subscribers Tech 1872 VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY DDFSE-IR Architecture MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP tk  kTsymb Q0 r0,M (t ) rM(0) [k ] Received array snap-shot augmented by over-sampling factor: can increase the effective degree of freedom of the array. 120 FB-DDFSE: an iterative reduced- Output state sequence sequence estimator estimate for desired user r1(0) [k ] mux. r0,1 (t ) Constrained Length Multi-Input/Multi-Output Whitened Matched Filter (MIMO-WMF) for desired user r [n ] Wd [n] yd [n ] MQ0  1 MQ0  MQ0  Lw MultiChannel MQ0  1 FB-DDFSE sˆd [n] Strategy: Detect signal while rejecting interference by approximating interferers as cyclostationary Gaussian Noise. DDFSE-IR is then a reduced-complexity approximation to Forney’s Maximum Likelihood Sequence Estimation (MLSE). To achieve state reduction requires a synergistic design of the WMF and the reduced-state sequence estimator. Virginia Tech 1872 VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP The Impact of Transmit Smart Antennas at Mobile Handset on the System Level Performances Jong-Han Kim Dr. Jeffrey H. Reed Dr. Annamalai Annamalai Virginia 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Overviews MOBILE & PORTABLE RADIO RESEARCH GROUP o Motivation o Related Work ■ Objective ■ Introduction ■ Analysis Example ■ Conclusions ■ Progress Status o Upcoming Challenges Virginia 122 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Motivation MOBILE & PORTABLE RADIO RESEARCH GROUP o Research topic  The impact of the transmit smart antenna at mobile handset on the system level performances o Why transmit smart antenna at mobile handset  Performance of multiple access communication system is limited by co-channel interference and channel fading, which can be effectively cancelled or reduced by various smart antenna algorithms  Transmit smart antennas at mobile handset is an emerging technology by low power signal processing technology and small RF components Virginia 123 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Motivation (cont’d) MOBILE & PORTABLE RADIO RESEARCH GROUP o Evaluation of the system level performance ■ Smart antenna combining with other techniques can enhance the system performance more pronouncedly ■ The link level performance might not be directly translated into the system level performances  Ex) Performances of space time coding diversity at multi-user diversity network (such as HSDPA, HDR, etc.) is worse than those of single antenna in terms of system throughput ■ System level performance is an important decision metric in employing the smart antennas at the Virginia communication system Tech 124 1872 VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Related Work MOBILE & PORTABLE RADIO RESEARCH GROUP o Current work ■ Analysis of the impact of transmit diversity at handset on the reverse link DS/CDMA system capacity o Objectives ■ Develop a “unified” framework for reverse link CDMA capacity estimation ■ Investigate the effect of fade distribution, multipath diversity, basestation receive diversity, soft-handoff (macro-diversity), for transmit diversity on intercell and intracell interference statistics Virginia 125 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Introduction MOBILE & PORTABLE RADIO RESEARCH GROUP o Contribution ■ Develop a comprehensive analytical model for reverse link CDMA capacity estimates  Transmit diversity at mobile station (open-loop and closedloop diversity)  Spatial diversity with non-identical fading statistics  Multipath fading channel with arbitrary multipath profile  Different user distributions in cells  Maximum transmit power constraint  Soft handoff  Power control (fast and slow power control) o Capacity estimates ■ Outage probability metric based on intracell and intercell interference statistics Virginia 126 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Analysis Example MOBILE & PORTABLE RADIO RESEARCH GROUP 1 o Reverse link DS/CDMA cellular systems Propagation Loss  0th BS Propagation Loss  Perfect Power Control MS Kth BS Virginia 127 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Capacity Estimates MOBILE & PORTABLE RADIO RESEARCH GROUP o Outage probability vs. the number of users ■ Rayleigh pedestrian channel A ■ Uniform user distribution o Key observation Rayleigh Pedestrian A channel ■ Impact of power control (fast vs. slow power control) ■ Impact of transmit diversity at mobile handset in conjunction with receive diversity at base station (M = # of transmit antennas at mobile handset X # of receive antennas at base station) Virginia 128 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Conclusions MOBILE & PORTABLE RADIO RESEARCH GROUP o Efficacy of transmit diversity at mobile handset on the system capacity of DS/CDMA cellular system ■ Capacity enhancement by other-cell interference reduction in terms of mean and variance ■ Fast power control achieves greater capacity improvement than slow power control for similar environments ■ The relative performance gains achieved by adding higher order diversity are greater in systems employing slow power control than those achieved using fast power control Virginia 129 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Progress Status MOBILE & PORTABLE RADIO RESEARCH GROUP o Developed a unified framework for reverse link DS/CDMA capacity estimation, which is extending the previous works by providing unified analysis framework and quantifying the impact of transmit diversity on reverse link DS/CDMA o Developed a link simulator to evaluate the performances of transmit diversity schemes o Developing a system simulator to validate the result of analysis framework Virginia 130 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Upcoming Challenges MOBILE & PORTABLE RADIO RESEARCH GROUP o Developing the analysis frameworks and modeling methodologies for ■ Data networks (cellular-based or mobile ad hoc network) employing the smart antennas ■ Heterogeneous networks (such as mixed voice and data users ) equipped with the smart antennas o Investigating the cross-layer optimization techniques for the smart antenna system combining with other system performance improvement techniques o Suggesting the further improvement solutions ■ Adaptive utilization method of smart antenna algorithms ■ Modified upper layer protocols Virginia 131 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY Factors to Consider in Creating a Smart Antenna API MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP Jeffrey H. Reed, Ramesh Chembil Palat, Raqibul Mostafa Mobile and Portable Radio Research Group Bradley Dept. of Electrical and Computer Engineering Virginia Tech Blacksburg, VA 24060 reedjh@vt.edu Secondary antenna Seungwon Choi HY-SDR Research Center Hanyang University, Seoul, Korea choi@dsplab.hanyang.ac.kr Primary antenna Virginia 132 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG What is a Smart Antenna MOBILE & PORTABLE RADIO RESEARCH GROUP o Definition ■ Antenna array system aided by some “smart” algorithm to combine the signals, designed to adapt to different signal environments ■ The antenna can automatically adjust to a dynamic signal environment o Mechanisms ■ The gain of the antenna for a given direction of arrival is adjustable ■ Take advantage of different channels for different antennas o Some antennas are “smarter” than others Virginia 133 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY Smart Antenna Benefits MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP Intercell Interference Multipath Multipath Uplink Base Station Downlink JAMMER Mobile Smart Handset Signal Fading JAMMER • Co-channel (jamming) and adjacent channel interference reduction ■ Multiple access interference reduction for capacity improvement ■ Robustness against multipath, fading, and noise to improve coverage and range ■ Higher spectral efficiency ■ Reduced power consumption for the handset ■ Lower probability of interception and detection ■ Enhance location estimates ■ Virginia Min. infrastructure changes in transitioning from voice to data systems Tech 134 1872 VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Smart Antennas in Software Radios MOBILE & PORTABLE RADIO RESEARCH GROUP Software radios and smart antennas complement each other ■ Smart antennas provide the benefits that motivate the adoption of software radios ■ Software radios are flexible enough to support smart antenna algorithms and their system overhead Virginia 135 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Smart Antenna Operation MOBILE & PORTABLE RADIO RESEARCH GROUP o Smart antenna operation possible in either direction of signal flow: ■ Receive smart antenna ■ Transmit antenna array o Both modes share the same categories: ■ ■ ■ ■ Beamforming Diversity Space Time Adaptive Processing (STAP) Multiple Input Multiple Output (MIMO) Virginia 136 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Smart Antenna Principle MOBILE & PORTABLE RADIO RESEARCH GROUP Three Interferers Moving Interferer Moving Target 4 element linear array. Constant Modulus Algorithm working in three environments. Virginia Note gain changes as a function of angle. Tech 137 1872 VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY Smart Antenna Implementation: System Level View VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP o Software and hardware boundaries need to be defined o Appropriate interfaces required at the boundaries o Lends itself to SDR implementation Software Hardware RF IF ADC RF IF ADC RF IF DAC RF IF DAC BFN Smart Antenna Algorithms & Baseband Signal Processing Software Control Virginia 138 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Desirable Smart Antenna API Characteristics MOBILE & PORTABLE RADIO RESEARCH GROUP o The various SA algorithms must be applicable to SDR-based wireless communication systems such that SA API does not confine to the evolution of communication standards and system hardware. o Interface between Smart Antenna Base Station (SABS) and SDR network must operate independently of hardware. o SABS should be partitioned into small modules and each of modules should interface independent of various algorithms and communication standards. o Functions and capability of each module must be known to the network controller. Thus, Beam-forming module in SABS should be manageable through SDR network. o Network interface should be independent of system upgrade. Virginia 139 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Example of SDR-based Smart Antenna System Open Architecture MOBILE & PORTABLE RADIO RESEARCH GROUP Application Layer Middleware Layer Physical Layer Virginia 140 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY Hardware Partitioning MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP  SDR-based Channel Card Structure DSP Demodulator Module Micro Processor Beam Former Beam Former Beam Forming Parameter Beam Forming Parameter Beam Former Beam Forming Parameter FPGA Beamformer Interface Beamformer Interface Beamformer Interface Demodulator Demodulator Demodulator DPRAM DPRAM DPRAM Demodulator Controller Demodulator Controller Demodulator Controller DSP 6 ANT, I&Q Other Board Interface Channel Card Controller (6 bits/signal) DPRAM DPRAM SCME Searcher Clock & Data Buffer 4 ANT (6 bits/signal) DPRAM Modulator Module 141 Modulator Tx Data Buffer Virginia FPGA 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Smart Antenna API Logical Functionality MOBILE & PORTABLE RADIO RESEARCH GROUP Commands Asynchronous protocols-to-device primitives for performing immediate, typically non-persistent actions. Variables Persistent antenna state or long-term measurement primitives. Response The synchronous device response to a protocol’s command or variable operation. Signals Asynchronous device-to-protocols primitives for reporting recent, typically non-persistent events. Commands Variables NetWorks /Set /Get /Info Response SABS Signals < Interface between Network and SABS through Network protocol > Virginia 142 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP • Commands Commands Requirements oCmdBeamformerReset Mandatory Qualifiers Description Response oBeamformer Soft Reset oBeamformer Soft Reset OK. oBeamformer Soft Reset Failure. oCmdBeamFormerExec oCmdCalibrationExec oCmdBeamFormerDMExec Mandatory Mandatory Optional oBeamFormer Execution on/off oBeamFormer Execution OK. oCalibration Execution on/off oCalibration Execution OK. oBeamformer Diagnostic oBeamformer Diagnostic monitoring on/off oBeamFormer Execution Failure. oCalibration Execution Failure. monitoring OK. oBeamformer Diagnostic monitoring Failure. • Signals Commands Requirements oSignBeamformer Mandatory oSigBeamformerError Mandatory Qualifiers Description oBeamformer Module loaded oInterrupt oIndicating the Beamformer Error Virginia 143 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP Smart Antenna API: Outstanding Questions o How general can it be in practice? o What is the border between the smart antenna API and the antenna API? o How can it be verified? o Is it possible to use CORBA transport? Virginia 144 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP Cooperative Radio Virginia 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Cooperative Radios MOBILE & PORTABLE RADIO RESEARCH GROUP o Distributed MIMO o Distributed Applications ■ Distributed MIMO ■ Distributed computing ■ Distributed location estimation ■ Distribute spectrum monitoring and control ■ Distributed security Virginia 146 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP Distributed Cooperative Diversity for High Data Rate UAV Links (ONR) BAA 04-001 Researchers: Ramesh Chembil Palat, Dr. A. Annamalai, Dr. Jeffrey H. Reed Virginia 147 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Distributed, Collaborative Inter-Cluster Communication with UAV Assisted Relaying MOBILE & PORTABLE RADIO RESEARCH GROUP Collaborating Node Ground Wireless Cluster UAV Cluster Cluster Head Command Control  Improves end-to-end communication reliability  Can expect very large increase in effective throughput  May have significant ramifications on network layer  need to investigate multiple architectural solutions 148 using D-MIMO Virginia 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Distributed MIMO: Big Picture MOBILE & PORTABLE RADIO RESEARCH GROUP o MIMO technology offers tremendous improvements in a point-to-point link ■ Well acknowledged fact o Can we exploit MIMO advantages in a distributed set up? ■ Limited literature on performance and implementation issues:  Requires study of architecture selection and communication strategies using distributed MIMO  Requires hardware implementation using distributed MIMO set up ■ Ramifications on higher layers not well understood:  Needs investigation of higher layer performance using DMIMO for PHY layer Virginia 149 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Architectural Issues (1/3) MOBILE & PORTABLE RADIO RESEARCH GROUP 1. 2. 3. 4. No Diversity GSC (SC& MRC) EGC Rx Beamforming Relays (DF or AF) GSC EGC Rx Beamforming Signal Processing Signal Processing 1. 2. 3. 1. 2. Tx Beamforming Synthetic Space Time Coding Virginia 150 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Architectural Issues (2/3) MOBILE & PORTABLE RADIO RESEARCH GROUP o Single source-destination node with multiple relay nodes ■ Multiple choice for schemes to select from o Rate/Reliability tradeoff evaluation of each scheme:  ASER/ABER  Implementation complexity – E.g. array calibration for BMF Vs STBC  Bandwidth and/or power efficiency Virginia 151 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Example Scenario MOBILE & PORTABLE RADIO RESEARCH GROUP o Simple DF/AF only scheme ■ Bandwidth efficiency low as multiple bands required ■ Implementation complexity and relay collaboration low o Uplink-GSC; Downlink SSTC ■ ASER performance similar ■ Bandwidth efficiency high ■ Implementation Complexity higher (relay collaboration required) o Uplink GSC; Downlink TxBMF ■ ASER performance better ■ Bandwidth efficiency high ■ Higher implementation complexity (need feedback info about channel) 152 Form a recommendation subset for architecturalirginia tradeoffs V Tech for operational scenarios ! 1872 VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Architectural Issues (3/3) MOBILE & PORTABLE RADIO RESEARCH GROUP o What happens when more than one source/destination nodes are available to collaborate? (Next phase of research) ■ Improved architectural flexibility ■ Scale the problem to address link imbalance issues in multi-hop networks ■ Cross layer ramifications Second Hop First Hop 153 Source Cluster Relay cluster UAVs Virginia DestinationTech Cluster 1872 VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Simulation Setup for UAV Based Communication 15,000 MOBILE & PORTABLE RADIO RESEARCH GROUP 10 Km 60 Km Virginia 154 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP Assumptions about UAV Characteristics o Wing span 3-4 ft and 9-10 ft o Max speed 150Km/Hr (93 Miles/Hr) ([1],[3] other references) o Max range 120-150 Km for UAV Navigation [1],[3] o Max and Min wind speed (22-8 knots) (40.74– 14.82 Km/Hr) [4] ■ At 10 kts max lateral displacement de = 1.7 ft in 3s so at 22 kts ~ 3 ft = 1m max ■ Due to turbulence vertical max average displacement de = 3 ft o Max Transmitted Power 1-2 W (1 W considered) [2] Virginia 155 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Assumptions for simulation MOBILE & PORTABLE RADIO RESEARCH GROUP o Pathloss exponent (ground to air) at VHF: 2.3 (approx worst case) [5] o Land to Sea Pathloss exponent at VHF: 3 (approx) [6] o Uplink Transmit power PTx = 0-30 dBm o UAV Transmit power 1/L*(PTx) ( L is the number of UAVs) o Average noise power level at each receiver (both UL and DL): -100 dBm o Assumed perfect collaboration between UAVs o All simulations and analysis based on BPSK modulation Virginia 156 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY Simulation Result MPRG 0 10 Beamforming and SSTC performance comparison MOBILE & PORTABLE RADIO RESEARCH GROUP -1 10 Effect of Reduced Path loss 6 dB -2 10 8 dB BER Direct link fails under fading but relay scheme works even with single relay Direct Land to Sea 1 UAV 2 UAV BMF 4 UAV BMF 2 UAV G2 STBC 4 UAV G4 STBC -3 10 SSTC • Direct link experiences Rayleigh fading • UAV Relay experiences Ricean fading with LOS component Beamforming -4 10 -5 10 0 5 10 Source 15 Power in dBm Transmit Power 20 25 30 in dBm •At least 35x Range extension compared to direct land to sea link even without fading Virginia •4 UAV SSTC gives 8 dB gain and BMF gives 6 dB at BER of .001 over single Tech 157 relay 1872 VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY Effect of Doppler & Displacement Error MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP Distributed Beamforming with doppler and displacement error of UAVs 0 10 o fc = 145 MHz o BW = 10 KHz T = 100us o Relative velocity due to wind 40 Km/Hr o Displacement due to turbulence modeled as Gaussian RV with mean .3m and variance .01 o The errors transformed to phase error -1 BER 10 -2 10 Direct link land - sea 1 UAV 2 UAV 2 UAV Doppler 2 UAV Displacement error 4 UAV 4 UAV Doppler 4 UAV Displacement error -3 10 5dB 7dB æ5 ö D f = v / c * fc *çç ÷÷÷ çè18 ø D f = 2* p * D f / BW for each symbol l = c / f c = 2.07 m -4 10 0 5 10 15 Transmit Power in dBm 158 20 25 30 D f de æd e ÷ ö ç = 2* p * ç ÷ ÷ çè l ø Virginia Displacement error decreases performance but still better than Tech Land to Sea direct link 1872 VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Distributed MIMO Summary (1/2) MOBILE & PORTABLE RADIO RESEARCH GROUP o At least 35x range extension using UAVs o Drastic power reduction for transmit nodes ■ Better suited for LPI/LPD o Beamforming performs better at low SNRs (1-2 dB) ■ Good candidate for LPI scenarios o Moving platform degrades BMF performance but still better than direct link ■ Lower frequencies (VHF) better resistance ■ Higher frequencies synchronization overhead increases Virginia 159 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP Distributed MIMO Summary (2/2) o Some other observations from simulation: ■ Fading index of weaker link dominates performance  E.g. distance from UAV to ship 50 Km (weaker link) hence changes in fading index in downlink can change ABER performance ■ SSTC performs better than BMF at high SNRs > 25 dB  Does not require feedback about channel compared to BMF ■ AT lower SNRs DF schemes give better ABER performance than AF schemes o Offers operational flexibility ■ Can apply many permutations and combination of schemes ■ Flexibility in terms of number of UAVs used  Effective in dynamic military environment – Switching communication architectures Virginia 160 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP CISCO URP Project Aegis Network-based Interference Characterization and Management for 802.11 WLAN Jeffrey H. Reed, Professor Brian G. Agee, Adjunct Research Professor Youping Zhao, Ph.D. Candidate, Research Assistant Mobile and Portable Radio Group (MPRG) Bradley Department of Electrical and Computer Engineering Virginia Tech Virginia Tech, Blacksburg, VA 1872 VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP Cooperative Radio Perspective for 802.11 WLAN Interference Management o What is cooperative radio? In cooperative wireless communication, we are concerned with a wireless network, where the wireless agents may increase their effective quality of service (measured at the physical layer by bit error rates, block error rates, or outage probability) via cooperation. o How to cooperate among WLAN Access Points for interference management? Interference is to be detected, classified, located, canceled and/or mitigated based on the collected data from multiple WLAN Access Points. o What are the possible applications of Cooperative radio for WLAN? Increased interference detection rate; better location accuracy; Improved QoS and security of WLAN owing to interference detection, cancellation or mitigation. Higher throughput or larger coverage of WLAN Well, many open issues and full of challenges… Virginia 162 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP o o Motivations & Visions of Project Aegis Motivations: ■ WLAN interference management is an indispensable part of the future network ■ Wireless connectivity in the enterprise and home will occur, ready or not! 95% of corporate laptops will ship with Wi-Fi embedded by 2005 (Meta Group). ■ 802.11 WLAN uses unlicensed (virtually unmanaged) radio medium (ISM band), therefore, it must contend with disparate numbers and varieties of interferers, including but not limited to, microwave oven, cordless phones, VoWiFi phones, Radar, Bluetooth devices, adjacent 802.11 networks, and many emerging devices, such as ZigBee (802.15.4) etc ■ The costs of WLAN maintenance keep growing up rapidly. Current WLANs typically have limited interference characterization and management capability, which creates a strong need for developing sophisticated tools to characterize and manage WLAN interference, therefore optimize the WLAN operation in terms of throughput, coverage, QoS, etc. Visions: ■ Develop algorithms and tools for interference detection, classification and geolocation for next generation WLAN management tools ■ Apply macro-diversity, cognitive radio, cooperative radio techniques to intelligent WLAN interference management with the capabilities, such as: network-concentric spectrum analysis, interference sensing, classification, geolocation, automatic interference diagnosis, avoidance or mitigation ■ VirginiaTG k, TG n) Contribute to ongoing IEEE 802.11 standardization efforts (e.g., 802.11 Tech 163 1872 VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP Main Tasks & Challenges of Project Aegis Main Tasks: o Interference characterization, modeling and generation ■ focus on non-802.11 interference first (e.g., Microwave oven leakage, Bluetooth) o Interference detection and classification o Interference emitter geolocation techniques development o May need to refine (or innovate) WLAN Network Architecture & Protocol to support the implementation of the Interference Management algorithms Main challenges: ■ WLAN operates in unlicensed shared spectrum, where various (virtually unpredictable) interference exist with disparate features ■ Complicated indoor radio propagation scenarios make the interferer location difficult ■ Many practical issues to be considered, such as A/D speed, dynamic range, storage limit of AP, synchronization between APs Virginia Tech 164 1872 VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP Example: Enterprise WLAN Networking Scenario (Hospital) Burst 802.11b clients (CCK) Out-of-network 802.11 STA’s (DSS) Wireless VoWiFi, cordless/PTT phones (DSS, FHSS) • Bluetooth Microwave ovens (chirp) High-rate 802.11g OFDM streaming data 165 IEEE 802.15.4 Zigbee devices (upcoming) Virginia 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP DMP Bluetooth signal ON/OFF detection illustration 20 dB 18 dB Detection statistics in dB 16 dB SOI Bluetooth “ON” detected Up-edge a stat Down-edge stati SOI Bluetooth “OFF” detected SNOI Bluetooth “OFF” detected 14 dB 12 dB Threshold_OFF 10 dB 8 dB 6 dB 4 dB 2 dB 0 dB Threshold_ON 50 µs 100 µs 150 µs 200 µs 250 µs ON Statistic Start Time Virginia 166 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP WLAN AP Beacon Exploitation Strategy o Calibration phase ■ Detect and identify beacon periods for each AP ■ Collect data during beacon preamble transmission period ■ Transfer back to central site ■ Use beacons as pilots to calibrate clock offsets between AP’s o Data collection phase (may coincide with Calibration phase) ■ Collect data at coordinated time and frequency (simultaneous with calibration phase if possible) ■ Transfer back to central site o Interference analysis phase ■ Resample data collects onto common clock ■ Remove beacons if needed (simultaneous calibration/analysis) ■ Detect interferers under beacons 167■ Geolocate interferers Virginia 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP Implemented Single-Site Real Data Collection System Virginia 168 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP Processor Technology Dr. Peter Athanas Dr. Jeffrey H. Reed Dr. Srikathyayani Srikanteswara James Neel Virginia 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Configurable Computing MOBILE & PORTABLE RADIO RESEARCH GROUP o Match the programmable hardware to the application. ■ Speed ■ Silicon efficiency ■ Flexibility Virginia 170 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG The Stallion – Stream Processor MOBILE & PORTABLE RADIO RESEARCH GROUP Allocable Resources IFU MESH (computational) Programmable Data Ports Stream I/O “Smart” Crossbar Network 171 Integer Multipliers Virginia Tech (allocable) 1872 VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP Wormhole RTR Stream Format Stream Format Program/Flow Header Data Configuration information Routing information Variable size Possibly removed as stream routs Application data stream  Possibly chained  Variable size Virginia 172 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Stallion Overview MOBILE & PORTABLE RADIO RESEARCH GROUP o 16-bit stream based CCM o 60 Functional Units o 4 Multipliers o Process: 0.25 m o Clock: 50 MHz o Area: 63.2 mm2 o 3.3 volts o Power: 0.7 W o Developed as part of Virginia Tech’s GloMo effort IFU Data Port Multiplier Crossbar Constant FeedBack Local or Skip Bus Input Mux. Local or Skip Bus Left Register Right Register FSout Shifter 1 and shift =1:0 in shift > 1: shift from Right reg. Zsel Fs Value shifted in if shift = 1, Opt. Inv. FsCond Carry ALU Overflow FC 0:No shift, 1: shift, Opt. Inv. Carry in, Opt. Inv. 0: ALU o/p J. Neel, S. Srikanteswara, J. Reed, P. Athanas, “A Comparative Study of the Suitability of a Custom Computing Machine and a VLIW DSP for 173 use in 3G Applications,” SIPS 2004. Conditional CondF 1: Right reg if Fin = 1, else ALU o/p Unit o/p delay Virginia Opt. Delay To Local or Skip Bus 1872 Tech Opt. Delay VIRGINIA POLYTECHNIC INSTITUTE To Skip AND STATE UNIVERSITY Bus VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG WCDMA Mapping Stallion Implementation MOBILE & PORTABLE RADIO RESEARCH GROUP o Stallion more efficient o Stallion requires significant hand coding (development time) C6201 Implementation Stallion Despread Mapping Virginia 174 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP Objectives of Configurable Computing for Software Radio o Identify and Evaluate “Ideal” Custom Computing Machine (CCM) architecture for handsets targeting CDMA2000 and UMTS ■ Method for Evaluating Disparate Chip Architectures ■ Dynamic CCM Simulator ■ Attributes of Optimal CCM for UMTS / CDMA2000 handsets ■ Comparative Evaluation of Developed CCM, TI 6701 DSP, and ASIC ■ High-Level Design of Compiler for Developed CCM _ Virginia 175 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP Cognitive Radio Virginia 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Cognitive radio networks MOBILE & PORTABLE RADIO RESEARCH GROUP o Game theory analysis of cognitive networks o Genetic algorithm cognitive engine o Test bed Virginia 177 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP Game Theory and Software / Cognitive Radio Researchers: Jody Neel, Luiz DaSilva, Robert Gilles, Allen MacKenzie, Jeff Reed, Annamalai Annamalai, R. Michael Buehrer, Albrecht Fehske, Ramakant Komali, Rekha Menon,Vivek Srivastava, Kevin Lau, Samir Ginde, James Hicks Sponsors: Office of Naval Research, Motorola, NSF IREAN Program, MPRG Affiliates Virginia 178 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Analyzing Distributed Dynamic Behavior MOBILE & PORTABLE RADIO RESEARCH GROUP o Dynamic benefits ■ Improved spectrum utilization ■ Improve QoS o Many decisions may have to be localized ■ Distributed behavior o Adaptations of one radio can impact adaptations of others ■ Interactive decisions ■ Difficult to predict performance Virginia 179 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY Games MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP o A game is a model (mathematical representation) of an interactive decision process. o Its purpose is to create a formal framework that captures the process’s relevant information in such a way that is suitable for analysis. o Different situations indicate the use of different game models. Normal Form Game Model 1. A set of 2 or more players, N 2. A set of actions for each player, Ai 3. A set of utility functions, {ui}, that describe the players’ preferences over the outcome space Virginia 180 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG How a Normal Form Game Works MOBILE & PORTABLE RADIO RESEARCH GROUP Player 1 Player 2 Actions Decision Rules Action Space Actions Decision Rules f :AO Outcome Space u1 +1 u2 -1 1 WINS! Virginia 181 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY Cognitive Radio Network as a Game MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP Radio 1 Radio 2 Actions Decision Rules u1 Actions Decision Rules Action Space Informed by Communications Theory u1 ˆ1  f :AO Outcome Space ˆ1, ˆ2  u2 ˆ2  u2 Virginia 182 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Key Issues in Analysis MOBILE & PORTABLE RADIO RESEARCH GROUP 1. 2. 3. 4. 5. Steady state characterization Steady state optimality Convergence Stability Scalability NE3 NE3 a2 NE2 NE1 NE1 a1 a1 a3 Scalability Optimality Stability Convergence Steady State Characterization As Are How these does donumber initial outcomes system of devices variations desirable? impact increases, impact the system thesystem? system? steady state? Is itthe possible toconditions predict behavior in the How Do What these the is processes steady theoutcomes system states willimpacted? maximize lead change? to steady the state conditions? target parameters? many different outcomes are system possible? Do Is How convergence previously long doesoptimal itaffected? take steady to reachstates the steady remainstate? optimal? Virginia Tech 183 1872 VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Ad-hoc Power Control as a Game MOBILE & PORTABLE RADIO RESEARCH GROUP o Utility function 1 5 ■ Target SINR at node of interest 5 o Player Set N ■ Set of decision making radios ■ Individual nodes i, j  N o Actions ■ ■ ■ ■ ■ Pi – power levels available to node i May be continuous or discrete P – power space p – power tuple (vector) pi – power level chosen by player i o Nodes of interest ■ Each node has a node or set of nodes at which it measures performance ■ {i} the set of nodes of interest of node i. 0 2 0 1 3 4 2 4 3 Virginia 184 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY Potential game model MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP  Existence of a potential function V such that ui  bi , ai   ui  ai , ai   V  bi , ai   V  ai , ai  ui  bi , ai   ui  ai , ai   V  bi , ai   V  ai , ai  o Identification  2u j  2ui  , i, j  N , a  A ai a j ai a j o NE properties (assuming compact spaces) ■ ■ NE existence: All potential games have a NE NE identification: Maximizers of V are NE o Convergence ■ Better response algorithms converge. o Stability ■ ■ Game is stable (Lyapunov) V is a Lyapunov function o Design note: ■ If V is designed so that its maximizers are coincident with your design objective function, then NE are also optimal. Virginia 185 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Power Control Application MOBILE & PORTABLE RADIO RESEARCH GROUP Cluster Head o Two cluster ad-hoc network o 11 nodes Gateway o DS-SS N = 63 o Path loss exponent n = 4 o Power levels [-120, 20 dBm] Cluster Head o Step size 0.1 dBm o Synchronous updating o Target SINR  ~ 8.4 dB o Objective Function 0 o Assume  is feasible ui(SINR)   ui  pi , pi     hii pi   h ji p j  n   i  jN \i   186 2 Virginia 1872 Tech i VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Simulation Results MOBILE & PORTABLE RADIO RESEARCH GROUP hii pi (ordinal potential) n  hij p j iN Noiseless Simulation Noisy Simulation V  p      Virginia 187 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY Interference Avoidance by Waveform MPRG Adaptation MOBILE & PORTABLE RADIO RESEARCH GROUP User1 N1 User2 N2 x1  t   x2  t  r1  t  r2  t   Receiver (Projection of rxed signal onto signal space) rn  t   xK  t  UserK NK  Signal at Receiver Multiple Access Channel is considered here Different types of users reside in a network Waveform used by users might reside in different dimensions (represented by signature sequence) Shape the waveform in a way such that interference in the network is minimized Transmitted Signal xk  sk bk K r   H k xk  n k 1 Virginia 188 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Distributed Greedy IA Game MOBILE & PORTABLE RADIO RESEARCH GROUP  Each user chooses sequences to increase its SINR at receiver  Utility function for each user is uk  sk    skT Rk sk where , Rk   si siT ik  Game has potential function given by T 2  V  S   Trace  Rk  sk sk     skT Rk sk  Cons tan    User updates iteratively increase V(S) ~ sum capacity Virginia 189 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Simulation Results: Greedy IA Game MOBILE & PORTABLE RADIO RESEARCH GROUP  Utilities of users shown to converge  Potential function also converges  Sequences converge to Welch Bound Equality Sequences that maximize sum capacity  Users choose waveform that gives minimum interference – best 190 response Virginia 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Game Theory Applied to Cognitive Radio: Future and Ongoing Work MOBILE & PORTABLE RADIO RESEARCH GROUP o Application Areas o Work Areas ■ Power Control ■ Joint adaptations ■ Waveform Adaptation ■ Study of impact of noise on other game models ■ Network Formation ■ Topology Control ■ Node Participation Virginia 191 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP Cognitive Engine based on Genetic Algorithms Charles Bostian (cbostian@vt.edu) Tom Rondeau, Bin Le, David Maldonado Center for Wireless Communications 466 Whittemore Hall Virginia Tech Blacksburg, VA 24061 (540) 231 - 5096 192 Work sponsored by NSF Virginia 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Why Cognitive Radio? MOBILE & PORTABLE RADIO RESEARCH GROUP o SDR is an enabling radio platform ■ Provides adaptive waveforms o Cognitive radio gives autonomous intelligence to the radio to exploit the benefits of SDR o Spectrum is an available resource that needs better management Virginia 193 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY Spectrum-Wide Market Needs MPRG How cognitive radio helps you MOBILE & PORTABLE RADIO RESEARCH GROUP o Need for spectrum ■ Opens availability to under-used spectrum ■ Provides better management of current spectrum use o Need for service ■ Public safety / disaster response ■ Military and public safety coordination o Need for capacity ■ Cellular services reaching maximum capacity, want to offer more and better services without the available resources Virginia 194 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Approach MOBILE & PORTABLE RADIO RESEARCH GROUP o At their most basic, Cognitive Radios are: ■ Aware: it can sense, perceive, and collect information about its environment ■ Intelligent: it can process and learn about the environment and its own behavior ■ Adaptive: it can use what it knows to alter the radio’s behavior to improve communication for itself and the surrounding radios o We use biologically-inspired techniques that combine machine learning with genetic and evolutionary algorithms Virginia 195 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Biological Adaptation MOBILE & PORTABLE RADIO RESEARCH GROUP o Intelligent adaptation is done using genetic algorithms (GAs) o Radio is modeled as a biological system where traits are defined by a chromosome o Each gene of the chromosome corresponds to one adjustable parameter of the radio o The GA optimizes the chromosome to provide the user with a quality of service Virginia 196 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Cognitive Radio Vision MOBILE & PORTABLE RADIO RESEARCH GROUP Awareness Adaptation Intelligence Virginia Tech 197 1872 VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY Intelligence is key MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP o Human-like Learning ■ Studying cognitive sciences to form better learning methods Environment Model Radio Feedback Learn Adapt Cognitive cycle for an intelligence radio Virginia 198 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Building Knowledge MOBILE & PORTABLE RADIO RESEARCH GROUP Using childhood learning theories, the radios will learn from experience and from peers. As knowledge base increases, learning time and computational complexity decreases. Virginia 199 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Distributed Learning and Intelligence MOBILE & PORTABLE RADIO RESEARCH GROUP o Radios can share knowledge ■ Improves performance ■ Reduces computational costs ■ Relaxes individual radio responsibilities Sharing Knowledge Resource Sharing Cooperation Autonomous System Virginia 200 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Details of the Cognitive Engine MOBILE & PORTABLE RADIO RESEARCH GROUP For details contact 201 bostian@vt.edu Virginia 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Some Experimental Results MOBILE & PORTABLE RADIO RESEARCH GROUP FFT for Received RF Bits FFT for Received RF Bits 10 0 -2 0 -6 -8 Play well with others -10 -12 -14 -16 Magnitude (dB) Magnitude (dB) -4 -10 -20 -30 -40 -18 -20 2400 2410 2420 2430 2440 2450 Frequency (Hz) 2460 2470 -50 2400 2480 2410 2420 2430 2440 2450 Frequency (Hz) 2460 2470 2480 FFT for Received RF Bits 10 Signal Interferers Reduce Spectrum Occupancy Magnitude (dB) 0 Maximize Data Rate -10 -20 -30 -40 202 -50 2400 Virginia 2410 2420 2430 2440 2450 Frequency (Hz) 2460 2470 2480 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP Development of a Cognitive Radio Test-bed using Tektronix Components Lizdabel Morales Jeffrey H. Reed Virginia Tech Bradley Dept. of Electrical and Computer Engineering Mobile and Portable Radio Research Group Virginia 203 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Current Spectrum Situation MOBILE & PORTABLE RADIO RESEARCH GROUP Problem Solution Considered o FCC and other regulatory o The amount of users of agencies have had the wireless technologies has task of re-allocating the grown tremendously scarce spectrum. during recent years. (Refarming) o Current available o The primary technology spectrum is scarce and being considered is cannot provide for Cognitive Radio. growth and innovation. Virginia 204 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG What is a Cognitive Radio? MOBILE & PORTABLE RADIO RESEARCH GROUP o Is a Software Defined Radio (SDR) that is aware of its environment and its capabilities, it can alter its physical layer behavior, and is capable of following complex adaptation strategies, as defined by Mitola. o In other words, the radio learns from previous experiences and can adapt to new situations not planned at the radio’s initial design time. Virginia 205 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY How can Cognitive Radio improve MPRG Spectrum Utilization? MOBILE & PORTABLE RADIO RESEARCH GROUP o Allocate the frequency usage in a network. o Assist secondary markets with frequency use, implemented by mutual agreements. o Negotiate frequency use between users. o Provide automated frequency coordination. o Enable unlicensed users when spectrum not in use. o Overcome incompatibilities among existing communication services. Virginia 206 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Proposed Research MOBILE & PORTABLE RADIO RESEARCH GROUP o Development of a Cognitive Radio test-bed using Tektronix off-the-shelf components and MPRG’s open source SCA and test equipment software (“wrappers”). o Initially cognition abilities will comprise of identification of particular frequency bands in use. o Signal identification and other capabilities will be added as research progresses. Virginia 207 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY Cognitive Radio Test-bed MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP PC Management (SCA) Cognitve Waveform Logic Analyzer Data Waveform Ethernet RSA3408A AWG430 Mixer PA ~ RF Front End RF Front End PA Optional and Custom Virginia 208 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Test-bed’s Main Components MOBILE & PORTABLE RADIO RESEARCH GROUP o Arbitrary Waveform Generator AWG430 – used to create a multi-mode transmitter. o Logic Analyzer – used for signal characterization (identifying bit patterns, protocols, etc.) o Real Time Spectrum Analyzer (RSA3408A) – used to perform signal demodulation. o PC with MPRG’s OSSIE (Open Source SCA Implementation Embedded) platform – used to implement the cognitive engine. Virginia 209 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Research Plan (1/2) MOBILE & PORTABLE RADIO RESEARCH GROUP o Provide a solution to test and validate cognitive radio with Tektronix COTS. o Analyze radio etiquettes developed from our game theory research. o Analyze the stability and convergence of cognitive algorithms developed from our research. o Test the performance of genetic learning algorithms developed at VT’s CWT group. o Develop new cognitive algorithms based on Hidden Markov Models. Virginia 210 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Research Plan (2/2) MOBILE & PORTABLE RADIO RESEARCH GROUP o Quantify the impact of fixed versus ad-hoc cognitive infrastructures. o Quantify the impact of the Interference Temperature model proposed by the FCC. o Investigate combinations of modulations that do not interfere with each other. o Investigate how cognitive radios can be used to improve interoperability between systems. o Develop and test applications for cognitive radio technologies such as ad-hoc video conference. Virginia 211 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG Future Goals MOBILE & PORTABLE RADIO RESEARCH GROUP o Create a cognitive radio test-bed with 2 or more nodes. o Analyze the impact of cognitive radios in networks. o Develop cognitive engines using various techniques (HMM, GT, GA, etc.) Virginia 212 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP Concluding Thoughts on Research Directions in SDR Virginia 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MPRG MOBILE & PORTABLE RADIO RESEARCH GROUP Concluding Thoughts about the Future o Software Defined Radio is really a misnomer. Probably should be called Software Defined Networks o Cognitive Radio is quickly gaining momentum as an important research area ■ Probably should be called Cognitive Radio Networks ■ Gut-feel: Probably lot of gain with simple approaches ■ Cognition within existing standards is possible (SDR enabled) o SCA isn’t perfect, but its getting better and researchers are getting smarter o COTS will be coming more viable for easily making the radio o DSP is the easy part --- Flexible analog and antennas are tough o SDR will go commercial, but cost MUST be the driver ■ New applications tilt cost savings to SDR ■ Increasing development costs are favoring SDR Virginia 214 1872 Tech VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY

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