1. Spectrum Sharing MAC-layer Protocols Sang-Yoon Chang ECE 439 Spring 2010

2. 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

3. FCC Spectrum Allocation Chart

4. Spectrum Utilization A snapshot of spectrum utilization up to 6 GHz in an urban area at mid-day [1]

5. 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

6. Project Overview Random access protocol without coordination [2] Centralized channel allocation algorithm [3] Distributed channel allocation algorithm [4],[5] Single radio per user [6],[7] Sensing overhead / limitations [7],[8] Diverging from traditional slotted channelization [7],[10],[11],[12] Selfish users [14] MMAC [6], HMAC [7] SWIFT [10]

7. Hidden-Terminal Problem In single-channel environment, IEEE 802.11 DCF, busy-tone Assumed single radio per user IEEE 802.11 DCF in multi- channel 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

8. 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

9. Beacon Interval

10. MMAC Performance Compared to DCA [9] and IEEE 802.11 WLAN (above) and multi- hop (below) environment Also observed packet delay CBR traffic Packet size = 512 Bytes Beacon interval = 100 ms ATIM window size = 20 ms 3 channels

11. 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

12. HC-MAC: Sensing Decisions B = Transmission Rate, T = Packet Duration, t = Sensing Time * *

13. 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

14. 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)

15. SWIFT: Adaptive Sensing (sec)

16. SWIFT Bin Sync. Problem

17. 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

18. 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

19. 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.