Radio Resource Allocation for Multi-radio Coexistence IEEE 802.16 Presentation Submission Template (Rev. 9) Document Number: IEEE C802.16m-08/882r1 Date Submitted: 2008-09-05 Source: Feng Seng Chu National Taiwan University E-mail: b8901009@ee.ntu.edu.tw Kwang Cheng Chen National Taiwan University E-mail: chenkc@cc.ee.ntu.edu.tw Neeli Prasad Aalborg University E-mail: np@es.aau.dk Ramjee Prasad Aalborg University E-mail: prasad@kom.aau.dk Kanchei (Ken) Loa Institute for Information Industry E-mail: loa@iii.org.tw Venue: IEEE 802.16 Interim, Session #57, Kobe, Japan PHY aspects of Multi-Radio Coexistence; in response to the TGm Call for Contributions and Comments 802.16m-08/033 for Session 57 Purpose: Propose radio resource allocation as collaborative and non-collaborative coexistence mechanism. Notice: This document does not represent the agreed views of the IEEE 802.16 Working Group or any of its subgroups. 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Patent Policy: The contributor is familiar with the IEEE-SA Patent Policy and Procedures: <http://standards.ieee.org/guides/bylaws/sect6-7.html#6> and <http://standards.ieee.org/guides/opman/sect6.html#6.3>. Further information is located at <http://standards.ieee.org/board/pat/pat-material.html> and <http://standards.ieee.org/board/pat >. Outline • Multi-radio Coexistence • Classification of Multi-radio Coexistence – Collaborative/Non- collaborative – Collocation/Non- collocation • • • • Proposed Solution Realization based 16m SDD Example Algorithms in Function Block Proposed Text Multi-radio Coexistence • In 802.16m SRD, Section “Co-deployment with other networks” [1] – It is anticipated that IEEE 802.16m is to be deployed in the same (on a co-channel and nonco-channel basis) or adjacent RF bands as non IEEE 802.16m legacy networks. – The 802.16m standard shall provide a method to avoid generate or suffer interference to/from other coexisting systems. Classification of Multi-radio Coexistence • Collaborative/Non-collaborative [2] – There is information exchange among coexisting systems. • Collocation/Non-collocation [2] – When two devices’ antennas are positioned less than 0.5 meters apart. • In this contribution we focus on – 1. Non-collaborative non-collocation coexistence. – 2. Collaborative non-collocation coexistence. Proposed Solution • 16m and non 16m systems may be deployed in the same licensed band [section 9.3, 1], however, interference among systems should be avoid. • 16m shall enable the advanced RRM for efficient utilization of radio resources [section 6.4, 1]. • Radio resource management/allocation (RRM and RRA) can satisfy both requirements. – Avoid interference among systems. – Significant capacity improvement to achieve reliable communications by efficient resource utilization. Non-collaborative Non-collocation Coexistence • General operations Feedback CSI of available sub-carriers Spectrum Sensing BS MS 1. Identify available subcarriers. RRA Optimal allocation or Low-complexity 2. Estimate CSI of available subcarriers. Data Traffic 3. Predict available subcarriers and their CSI in next frame. 16m Protocol Structure Processing Flow Radio Resource Management System Configuration Management Multi-Carrier RRCM MAC Scheduling and Resource Multiplexing PHY Control - interference and CQI measurement Control Signaling Key Operations • PHY control – interference and CQI measurement – Identify available subcarriers. – Estimate CSI of available subcarriers. – Predict available subcarriers in next frame. – Predict CSI of next frame available subcarriers. • Radio resource management, Scheduling and Resource Multiplexing – Properly allocating system resource among user to maximize system capacity while avoiding interference Example Algorithm to Identification of Subcarrier Status • Generalized Likelihood Ratio test Pp H1 p is received power. l p , Pp H 0 H1 and H 0 represent availabili ty. Other Example Algorithms in PHY • To estimate CSI of available subcarriers – Least-square or LMMSE [3] • To predict available subcarriers in next frame – Based on HMM [4] • To predict CSI – Linear prediction [5] Properly Allocating System Resource c c c c User 1 c c User 2 User 3 :un-available subcarrier :available subcarrier After collecting above information of all user by PHY control function block, do RRM and SRM. Example Algorithm for Radio resource allocation Power allocated to subcarrier k in time slot t T max ωu ,t,k,p t,k U T K ω u 1 t 1 k 1 u,t,k log 2 1 pt,k CNR Channel to noise ratio Subcarrier allocation index for user u, time slot t and subcarrier k Subject to i Total Power Constraint (ii) Non - negative Constraint iii Availabili ty Constraint iv Fairness Constraint Such a multi-variable non-linear optimization is hard to be Solved, low-complexity algorithm may be preferred. Another Choice: Low-complexity Algorithm • We can divide the optimal allocation into – 1. time-frequency subcarrier allocation. – 2.Power allocation. Uniformly distribute power T max ωu,t,k,p t,k U T K ω u,t,k u 1 t 1 k 1 log 2 1 pt,k CNR Allocate subcarriers Allocate power among subcarriers T max ωu,t,k,p t,k U T K ω u 1 t 1 k 1 u,t,k log 2 1 pt,k CNR By subcarriers allocation resulted in prior step. Numerical Result (1) System Capacity 14 Optimal Low Complexity Algorithm, Step 1 Low Complexity Algorithm, Step 2 Low Complexity Algorithm, Step 3 Normalized Capacity 12 10 8 6 4 2 0 0 5 10 15 20 OSNR (dB) 25 30 35 40 Numerical Result (2) System Capacity 16 Low Complexity Algorithm, Step 1 OFDM based FDMA OFDMA-Subcarrier-Interleaved 14 Normalized Capacity 12 10 8 6 4 2 0 0 5 10 15 20 OSNR (dB) 25 30 35 40 Numerical Result (3) System Capacity With/Without Fairness Normalization, (OSNR,P 11) = (20 dB,0.8) 9 8 Normalized Capacity 7 6 5 4 3 Low Complexity Step 1, Without Fairness Normalization FDMA, Without Fairness Normalization Interleaved, Without Fairness Normalization Low Complexity Step 1, With Fairness Normalization FDMA, With Fairness Normalization Interleaved, With Fairness Normalization 2 1 0 0 0.1 0.2 0.3 0.4 0.5 Probability (P 00) 0.6 0.7 0.8 0.9 Collaborative Non-collocation Coexistence • Since there are information exchange among coexisting systems, we can consider a more aggressive scheme – Cross-Three-Layer Radio Resource Allocation by including frequency allocation among cells. • Inter-BS coordination function are included. Processing Flow based on 16m SDD Inter-BS coordination Radio Resource Management System Configuration Management Multi-Carrier RRCM MAC Scheduling and Resource Multiplexing PHY Control - CQI measurement Control Signaling Resource Management/Allocation If we represent the total network capacity as CT , total capacity of each cell as Ci , and total capacity of each system is Ci . The maximizati on of network capacity by dynamic allocating spectrum among cells can be formulated as N N i CT max Ci max Ci Bi i 1 Spectrum allocated to cell i Bi i 1 1 N : Number of cells. X i : Numer of coexisting systems in cell i. Resource Management/Allocation • Furthermore, with different assumptions the resulted capacity of each systems are different. • For example, if we assume MIMO-OFDMA systems, the system capacity can be Depend on decoding scheme and channel assumption 1 Ci TNT K i U i T N T K i Bi Δf u 1 t 1 1 i , i , ,u ,t i , log 1 SNR p u ,t , ,k ,k t , , k k 1 U i : Number of users in system. u : user index NT : Numer of Tx antenna in system . : Antenna index Numerical Result Network Capacity Normalized Network Capacity 15 Cross-Three-Layer Cross-Two-Layer Fixed Resource Allocation 10 5 0 0 5 10 15 20 SNR (dB) 25 30 35 40 Note • Resource should be allocated to users according to resource allocation unit defined in SDD [6]. • The proposed RRA algorithm can be slight modified to fit 16m system PHY configuration. Contributions • We propose RRA as critical mechanism for multi-radio coexistence. • Both non-collaborative / collaborative noncollocation scenario were considered. • Processing flow based on 16m SDD. • Example algorithms for each function block. Proposed Text • 17.x Solutions for Co-deployment and Co-existence – For avoiding interference to/from coexisting systems, flexibly adjusting system usage spectrum is a critical characteristic of coexistence mechanism. Furthermore, to achieve reliable communication under such scenario, efficiently utilizing system resource is also essential. Radio resource management/allocation is a well-known approach satisfying both the two requirements. By properly integrating the capability of existing function blocks in 16m protocol structure, the proposed mechanism can be realized effectively. • 17.x.1 RRA for Non-Collaborative Non-collocation Multi-Radio Coexistence – Since there is no information exchange among coexisting systems for this scenario, the function block “PHY Control - interference measurement” is required. – There should be at least two step in this function, (i) identify each subcarrier status of each user. (ii) Predict each subcarrier status in next frame of each user. – For resource allocation, the function block “PHY Control – CQI measurement/feedback” is required. – According to RRA algorithm adopted, the required CSI or CQI should be estimated and predicted in this function block. – Both the two function blocks “Radio resource management” and “Scheduling and resource multiplexing” are required to properly avoid interference and optimize system performance by information mentioned above. – In order to dynamic adjust system spectrum, both the “Multi-carrier” and “system configuration management” function blocks are required. • 17.x.2 RRA for Collaborative Non-collocation Multi-Radio Coexistence – Since there is information exchange among coexisting systems for this scenario, interference measurement is not necessary and we can further improve system performance by integrating frequency allocation among cells into resource allocation to formulate an aggressive Cross-Three-Layer scheme. – To realize this idea, inter-BS function block should be considered. Reference [1] “Project 802.16m System Requirements Document (SRD),” August, 2008. http://www.wirelessman.org/tgm/docs/80216m-07_002r5.pdf. [2] IEEE 802.15.2/D09, March 2003, http://myurl.com.tw/6gus. [3] Morelli M, Mengali U, “A comparison of pilot-aided channel estimation methods for OFDM systems,” Signal Processing, IEEE Transactions on, Volume 49, Issue 12, page(s): 3065-3073. [4] Akbar, I.A.; Tranter, W.H., “Dynamic spectrum allocation in cognitive radio using hidden Markov models: Poisson distributed case,” SoutheastCon, IEEE, March 2007 Page(s):196 – 201. [5] Akhtman J., Hanzo L., “Channel Impulse Response Tap Prediction for Time-Varying Wireless Channels,” IEEE Trans. on Vehicular Technology, Vol. 56, Issue 5, Part 1, 2007 Page(s):2767 – 2769. [6] “Draft IEEE 802.16m System Description Document ,” July, 2008, http://wirelessman.org/tgm/docs/80216m-08_003r4.zip