Spectrum Sharing
MAC-layer Protocols
Sang-Yoon Chang
ECE 439 Spring 2010
Motivation
• Bandwidth becoming scarcer and more valuable
– Increased demands on wireless applications
– Users demand higher performance
• Dynamically accessing multiple channels can
increase spectrum efficiency
• Our goal is to support multiple transmissions and
increase performance by mitigating interference
FCC Spectrum Allocation Chart
Spectrum Utilization
A snapshot of spectrum utilization up to 6 GHz in an urban area at mid-day [1]
Background
• Cognitive radio
– Secondary users operating on licensed Band
– Required to detect primary users’ signals
(physical-layer)
– Avoid and yield the channel use to primary users
(MAC-layer)
• In addition, coordination with other secondary users
• Other Spectrum Sharing Techniques
– Ultra WideBand (UWB) Communication
– Unlicensed Band, e.g., ISM band
Project Overview
•
•
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•
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Random access protocol without coordination [2]
Centralized channel allocation algorithm [3]
Distributed channel allocation algorithm [4],[5]
Single radio per user [6],[7]
MMAC [6], HMAC [7]
Sensing overhead / limitations [7],[8]
Diverging from traditional slotted channelization
SWIFT [10]
[7],[10],[11],[12]
• Selfish users [14]
Hidden-Terminal Problem
• In single-channel environment,
IEEE 802.11 DCF, busy-tone
• Assumed single radio per user
• IEEE 802.11 DCF in multichannel environment
• C does not hear the CTS(2)
from B, and thus collision
• If multiple radios per user,
Dynamic Channel
Assignment (DCA) by Wu [9]
– Needs complex hardware
MMAC Protocol
• Multi-Channel MAC (MMAC) by So and Vaidya [6]
• Single radio per user
• Build on IEEE 802.11 PSM protocol (beacon interval,
ATIM)
• Requires global synchronization
• In ATIM window,
– Agree on a channel according to Preferable
Channel List (High, Medium, Low)
– ATIM-RES to notify the channel reservation
Beacon Interval
MMAC Performance
• Compared to DCA [9]
and IEEE 802.11
• WLAN (above) and multihop (below) environment
• Also observed packet delay
• CBR traffic
• Packet size = 512 Bytes
• Beacon interval = 100 ms
• ATIM window size = 20 ms
• 3 channels
HC-MAC Protocol
• Hardware-Constrained Cognitive MAC (HC-MAC)
by Jia et al. [7]
• Single radio, partial spectrum sensing, spectrum
aggregation limit
• Construct a stopping problem to decide whether or
not to sense further channels
• Robust to multi-channel hidden terminal problem
HC-MAC: Sensing Decisions
BT
T  3t
2 BT
Rb 
T  3t
Rc 
Rc 
*
BT
T  3t
B = Transmission Rate, T = Packet Duration, t = Sensing Time
*
HC-MAC: Control Packets
• Contention (C-RTS / C-CTS)
– Competing for common control channel access
• Sensing (S-RTS / S-CTS)
– Exchange channel availability and agree on data channel
• Transmission (T-RTS / T-CTS)
– Notify neighboring nodes the completion of transmission
SWIFT Protocol
• Split Wideband Interferer Friendly Technology (SWIFT), Rahul
[10]
• Unlike UWB, no need to sacrifice transmission power, rate
• Cognitive aggregation of non-contiguous frequency band
• Adaptive sensing (probe the spectrum and observe reaction)
SWIFT: Adaptive Sensing
(sec)
SWIFT Bin Sync. Problem
SWIFT: Bin Synchronization
• SWIFT users independently decide which bands
that they can use.
i) If drastic disagreement on usable bands, or boot up
– Sends usable bins in all frequency bins
– Txer and Rxer agrees at least on one of the bins
ii) If limited disagreement,
– Stripes data across the previously agreed bins,
but transmits only in the subset that is still usable
– Transform the potential disagreement to bit errors
– Error correcting codes
Discussion and Conclusion
• Security issues arise, e.g., Denial-of-Services
(primary user emulation, jamming, etc.)
– Analyzed correctness and performance of
schemes assuming rational users (who care for
their performances)
• With smart radio becoming reality, burgeoning
interest in MAC protocols that are designed for
multi-channel environment
References
[1] R. W. Brodersen, A. Wolisz, D. Cabric, and S. M. Mishra, “CORVUS: A Cognitive Radio Approach for
Usage of Virtual Unlicensed Spectrum,” 2004.
[2] S. Huang, X. Liu, and Z. Ding, “Opportunistic Spectrum Access in Cognitive Radio Networks,” IEEE
Infocom, 2008.
[3] T. Shu and M. Krunz, “Coordinated Channel Access in Cognitive Radio Networks: A Multi-Level Spectrum
Opportunity Perspective,” IEEE Infocom, 2009.
[4] J. Zhao, H. Zheng, and G.-H. Yang, “Distributed Coordination in Dynamic Spectrum Allocation Networks,”
IEEE DySPAN, 2005.
[5] L. Cao, H. Zheng, and G.-H. Yang, “Distributed Coordination in Dynamic Spectrum Allocation Networks,”
IEEE CrownCom, 2007.
[6] J. So and N. Vaidya, “Multi-Channel MAC for Ad Hoc Networks: Handling Multi-Channel Hidden Terminals
Using a Single Transceiver,” ACM MobiHoc, 2004.
[7] J. Jia, Q. Zhang, and X. Shen, “HC-MAC: A Hardware-Constrained Cognitive MAC for Efficient Spectrum
Management,” IEEE Journal on Selected Areas in Communications, vol. 26, no. 1, pp. 106-117, 2008.
[8] S. Shetty, M. Song, C. Xin, and E. K. Park, “A Learning-Based Multiuser Opportunistic Spectrum Access
Approach in Unslotted Primary Networks,” IEEE Infocom, 2009.
[9] S.-L. Wu, C.-Y. Lin, Y.-C. Tseng, and J.-P. Sheu, “A New Multi-Channel MAC Protocol with On-Demand
Channel Assignment for Multi-Hop Networks,” ISPAN, 2000.
[10] H. Rahul, N. Kushman, D. Katabi, C. Sodini, and F. Edalat, “Learning to Share: Narrowband-Friendly
Wideband Networks”, ACM Sigcomm, 2008
[11] Y. Yuan, P. Bahl, and R. Chandra, “KNOWS: Kogitiv Networking Over White Spaces,” IEEE DySPAND,
2007.
[12] P. Bahl, R. Chandra, T. Moscibroda, R. Murty, and M. Welsh, “White Space Networking with Wi-Fi Like
Connectivity,” Sigcomm, 2009.
[14] R. Etkin, A. Parekh, and D. Tse, “Spectrum Sharing for Unlicensed Bands,” IEEE Journal on Selected
Areas in Communications, vol. 25, no. 3, p. 517, 2007.