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Optimal channel access for TCP performance improvement in cognitive radio networks

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Abstract

Cognitive radio (CR) is a promising technology to improve spectrum utilization. Most of previous work on CR networks concentrates on maximizing transmission rate in the physical layer. However, the end-to-end transmission control protocol (TCP) performance perceived by secondary users is also a very important factor in CR networks. In this paper, we propose a novel multi-channel access scheme in CR networks, where the channel access is based on the TCP throughput in the transport layer. Specifically, we formulate the channel access process in CR network as a restless bandit system. With this stochastic optimization formulation, the optimal channel access policy is indexable, meaning that the channels with highest indices should be selected to transmit TCP traffic. In addition, we exploit cross-layer design methodology to improve TCP throughput, where modulation and coding at the physical layer and frame size at the data-link layer are considered together with TCP throughput in the transport layer to improve TCP performance. Simulation results show the effectiveness of the proposed scheme.

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References

  1. FCC. (2002). Spectrum policy task force. http://www.fcc.gov/sprf/reports.html, Tech. Rep.

  2. Mitola, J. (2000). Cognitive radio: An integrated agent architecture for software defined radio. PhD thesis, Royal Inst. Technol., Stockholm, Sweden.

  3. Zhao, Q., & Sadler, B. M. (2007). A survey of dynamic spectrum access. IEEE Signal Processing Magazine, 24, 79–89.

    Article  Google Scholar 

  4. Ghasemi, A., & Sousa, E. S. (2008). Spectrum sensing in cognitive radio networks: Requirements, challenges and design trade-offs. IEEE Communications Magazine, 46, 32–39.

    Article  Google Scholar 

  5. Liu, K., & Zhao, Q. (2008). A restless bandit formulation of opportunistic access: Indexablity and index policy. In Proceedings of the of 5th Sensor, Mesh and Ad Hoc Communication and Networks (SECON) Workshops. CA, USA.

  6. Wang, F., Krunz, M., & Cui, S. (2008). Spectrum sharing in cognitive radio networks. In Proceedings of the IEEE INFOCOM’08. Phoenix, AZ, USA.

  7. Liang, Y., Zeng, Y., Peh, E., & Hoang, A. (2008) Sensing-throughput tradeoff for cognitive radio networks. IEEE Transactions on Wireless Communications, 7, 1326–1337.

    Article  Google Scholar 

  8. Zhao, Q., Tong, L., Swami, A., & Chen, Y. (2007). Decentralized cognitive MAC for opportunistic spectrum access in ad hoc networks: A POMDP framework. IEEE Journal of Selected Areas in Communication, 25, 589–600.

    Article  Google Scholar 

  9. Zhao, Q., Krishnamachari, B., & Liu, K. (2008). On myopic sensing for multi-channel opportunistic access: Structure, optimality, and performance. IEEE Transactions on Wireless Communications, 7, 5431–5440.

    Article  Google Scholar 

  10. Jiang, H., Lai, L., Fan, R., & Poor, V. (2009) Optimal selection of channel sensing order in cognitive radio. IEEE Transactions on Wireless Communications, 8, 297–307.

    Article  Google Scholar 

  11. Slingerland, A., Pawelczak, P., Prasad, R., Lo, A., & Hekmat, R. (2007). Performance of transport control protocol over dynamic spectrum access links. In Proceedings of the IEEE DySPAN’07. Dublin, Ireland.

  12. Chowdhury, K., Felice, M., & Akyildiz, I. (2009). TP-CRAHN: A transport protocol for cognitive radio ad-hoc networks. In Proceedings of IEEE INFOCOM’09. Rio de Janeiro, Brazil.

  13. Karn, P., et al. (2004). Advice for Internet Subnetwork Designers. RFC 3819, IETF, July.

  14. Ghaderi, M., Sridharan, A., Zang, H., Towsley, D., & Cruz, R. (2009). TCP-aware channel allocation in CDMA networks. IEEE Transactions on Mobile Computing, 8, 14–28.

    Article  Google Scholar 

  15. Singh, J., Li, Y., Bambos, N., Bahai, A., Xu, B., & Zimmermann, G. (2007). TCP performance dynamics and link-layer adaptation based optimization methods for wireless networks. IEEE Transactions Wireless Communications, 6.

  16. Toledo, A. L., Wang, X., & Lu, B. (2006). A cross-layer TCP modelling framework for MIMO wireless systems. IEEE Transactions Wireless Communications, 5(4), 920–929.

    Article  Google Scholar 

  17. Tian, K. X. Y., & Ansari, N. (2005). TCP in wireless environments: Problems and solutions. IEEE Communications Magazine, 43(3), s27–s32.

    Article  Google Scholar 

  18. Chockalingam, A., Zorzi, M., & Tralli, V. (1999). Wireless TCP performance with link layer FEC/ARQ. In Proceedings of IEEE ICC’99. Vancouver, BC.

  19. Chapin, J. M., & Lehr, W. H. (2007). The path to market success for dynamic spectrum access technology. IEEE Communications Magazine, 45, 96–103.

    Article  Google Scholar 

  20. Whittle, P. (1988). Restless bandits: Activity allocation in a changing world. In J. Gani (Ed.), A celebration of applied probability (Vol. 25, pp. 287–298) of J. Appl. Probab., Applied Probability Trust.

  21. Berstimas, D., & Niño-Mora, J. (2000). Restless bandits, linear programming relaxations, and a primal dual index heuristic. Operations Research, 48(1), 80–90.

    Article  MathSciNet  Google Scholar 

  22. Ny, J. L., & Feron, E. (2006). Restless bandits with switching costs: Linear programming relaxations, performance bounds and limited lookahead policies. In Proceedings of the 2006 American Control Conference (pp. 1587–1592). Minneapolis, Minnesota.

  23. Jacobson, V. (1988). Congestion avoidance and control. In Proceedings of ACM SIGCOM’88. CA, USA.

  24. Anjum, F., & Tassiulas, L. (2003). Comparative study of various TCP versions over a wireless link with correlated losses. IEEE/ACM Transactions on Networking, 11, 370–383.

    Article  Google Scholar 

  25. Padhye, J., Firoiu,V., Towsley, D. F., & Kurose, J. F. (2000). Modeling TCP Reno performance: A simple model and its empirical validation. IEEE/ACM Transactions on Networking, 8(2), 133–145.

    Article  Google Scholar 

  26. Wang, X., Giannakis, G., & Marques, A. (2007). A unified apporach to QoS-guaranteed scheduling for channel-adaptive wireless networks. Proceedings of IEEE, 95, 2410–2431.

    Article  Google Scholar 

  27. Lien, S.-Y., Tseng, C.-C., & Chen, K.-C. (2008). Carrier sensing based multiple access protocols fro cognitive radio networks. In Proceedings of ICC’08. Beijing, China.

  28. Wang, H. S., & Moayeri, N. (1995). Finite-state Markov channel—A useful model for radio communication channels. IEEE Transactions on Vehicular Technology, 44, 163–171.

    Article  Google Scholar 

  29. Robbins, H. (1952). Some aspects of the sequential design of experiments. Bulletin of the American Mathematical Society, 55, 527–535.

    Article  MathSciNet  Google Scholar 

  30. Gittins, J. (1979). Bandit processes and dynamic allocation indices. Journal of the Royal Statistical Society B, 41(2), 148–177.

    MATH  MathSciNet  Google Scholar 

  31. Nino-Mora, J. (2001). Restless bandits, partial conservation laws and indexability. Advances in Applied Probability, 33(1), 79–98.

    MathSciNet  Google Scholar 

  32. Papadimitriou, C., & Tsitsiklis, J. (1999). The complexity of optimal queueing network control. Mathematical Operations Research, 24(2), 293–305.

    Article  MATH  MathSciNet  Google Scholar 

  33. Puterman, M. (1994). Markov decision processes: Discrete stochastic dynamic programming. New York: Wiley.

    MATH  Google Scholar 

  34. Goldsmith, A. (2005). Wireless communications. London: Cambridge University Press.

    Google Scholar 

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Acknowledgments

We thank the reviewers for their detailed reviews and constructive comments, which have helped to improve the quality of this paper.

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Authors and Affiliations

  1. Key Laboratory of Universal Wireless Communication, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing, China

    Changqing Luo & Hong Ji

  2. Department of Systems and Computer Engineering, Carleton University, Ottawa, ON, Canada

    F. Richard Yu

  3. Department of Electrical and Computer Engineering, The University of British Columbia, Vancouver, BC, Canada

    Victor C. M. Leung

Authors
  1. Changqing Luo
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  2. F. Richard Yu
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  3. Hong Ji
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  4. Victor C. M. Leung
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Corresponding author

Correspondence to Changqing Luo.

Additional information

This work is supported by the Natural Science and Engineering Research Council of Canada, National Science Foundation of China under Grant 60832009, Beijing National Science Foundation under Grant 4102044, the Hi-Tech Research and Development Program (National 863 Program) under Grant 2009AA01Z246, and 2009AA01Z211.

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Luo, C., Yu, F.R., Ji, H. et al. Optimal channel access for TCP performance improvement in cognitive radio networks. Wireless Netw 17, 479–492 (2011). https://doi.org/10.1007/s11276-010-0292-9

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