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Intelligent Improvement in Throughput of Cognitive Radio

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Abstract

Under the energy detection scheme based cognitive radio (CR) system, the process of spectrum sensing is of high importance. The sensing performance of CR primarily depends on two important parameters namely, the sensing time τ and the reference threshold λ. In order to achieve a goal where the CR system obtains a high value of throughput and simultaneously ensures a sufficient level of protection to the licensed users, the values of these parameters can neither be too high nor too low, so proper settings of their values is of prime concern. However, under these constraints on choosing a particular value of τ and λ, it is challenging for CR to fulfill this goal. In this paper we propose a CR system which operates under the scheme of double threshold to ensure a sufficient protection required by the licensed users and also makes an efficient utilization of the confusion region to improve its achievable throughput. It is observed that, under the proposed approach, the CR system achieves better throughput than the CR system based on the single threshold and also to the conventional double threshold based CR system where confusion region is used based on the results of sensing performed in the next sensing rounds. We further study the problem of optimizing the sensing duration to maximize the throughput of the proposed CR system. We formulate the sensing-throughput tradeoff problem mathematically and prove that, the formulated problem indeed has an optimal sensing duration where throughput of the CR system is maximized.

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Notes

  1. Transmit with a power which is needed to ensure a sufficient data rate. The transmissions are performed as if SU itself was a licensed user.

References

  1. Federal Communications Commission. (2002). Spectrum policy task force report. In FCC 02-155.

  2. Mitola, J., & Maguire, G. Q. (1999). Cognitive radio: Making software radios more personal. IEEE Personal Communications, 6, 13–18.

    Article  Google Scholar 

  3. Mitola, J. (2000). Cognitive radio: An integrated agent architecture for software defined radio. Ph.D. dissertation, Royal Institute of Technology, Stockholm, Sweden.

  4. Haykin, S. (2005). Cognitive radio: Brain-empowered wireless communications. IEEE Journal on Selected Areas in Communications, 23, 201–220.

    Article  Google Scholar 

  5. Liang, Y. C., Zeng, Y., et. al. (2007). Sensing throughput tradeoff for cognitive radio networks. In IEEE International conference on communication (ICC) (pp. 5330–5335).

  6. Liang, Y. C., Zeng, Y., et al. (2008). Sensing Throughput Tradeoff for Cognitive Radio Networks. IEEE Transactions on Wireless Communications, 7(4), 1326–1337.

    Article  Google Scholar 

  7. Ghasemi, A., & Sousa, E. S. (2007). Fundamental limits of spectrum-sharing in fading environments. IEEE Transactions on Wireless Communications, 6(2), 649–658.

    Article  Google Scholar 

  8. Musavian, L., & Aissa, S. (2007). Ergodic and outage capacities of spectrum-sharing systems in fading channels. In Proceedings of IEEE global telecommunication (GLOBECOM) conference (pp. 3327–3331).

  9. Stotas, S., & Nallanathan, A. (2011). Enhancing the capacity of spectrum sharing cognitive radio networks. IEEE Transactions on Vehicular Technology, 60(8), 3768–3779.

    Article  Google Scholar 

  10. Kang, X., et al. (2009). Sensing based spectrum sharing in cognitive radio networks. IEEE Transactions on Vehicular Technology, 58(8), 4649–4654.

    Article  Google Scholar 

  11. Stotas, S., & Nallanathan, A. (2010). Overcoming the Sensing-Throughput Tradeoff in Cognitive Radio Networks. IEEE International Conference on Communications (ICC). https://doi.org/10.1109/ICC.2010.5502792.

    Google Scholar 

  12. Stotas, S., & Nallanathan, A. (2012). On the throughput and spectrum sensing enhancement of opportunistic spectrum access cognitive radio networks. IEEE Transactions on Wireless Communications, 11(1), 97–101.

    Article  Google Scholar 

  13. Pandit, S., & Singh, G. (2013). Throughput maximization with reduced data loss rate in cognitive radio network. Telecommunication Systems. https://doi.org/10.1007/s11235-013-9858-z.

    Google Scholar 

  14. Xie, J. Q., & Chen, J. (2012). An adaptive double-threshold spectrum sensing algorithm under noise uncertainty. In IEEE 12th international conference on computer and information technology (CIT) (pp. 824–827). https://doi.org/10.1109/cit.2012.171.

  15. Liu, S.-Q., et al. (2012). Hierarchical cooperative spectrum sensing based on double thresholds energy detection. IEEE Communications Letters, 16(7), 1096–1099.

    Article  Google Scholar 

  16. Zhu, J., et. al. (2008). Double threshold energy detection of cooperative spectrum sensing in cognitive radio. In IEEE, cognitive radio oriented wireless networks and communication (CROWNCOM) (pp. 1–5). https://doi.org/10.1109/crowncom.2008.4562451.

  17. Jafarian, J., & Hamdi, K. A. (2012). Throughput optimization in a cooperative double-threshold sensing scheme. In IEEE, wireless communication and network (WCNC) (pp. 1034–1038). https://doi.org/10.1109/wcnc.2012.6213925.

  18. Kumar, S., et al. (2011). Cognitive radio concept and challenges in dynamic spectrum access for the future generation wireless communication systems. Wireless Personal Communications, 59, 525–535.

    Article  Google Scholar 

  19. Zhang, W., & Lataief, K. B. (2008). Cooperative spectrum sensing with transmit and relay diversity in cognitive radio networks. IEEE Transactions on Wireless Communications, 7(12), 4761–4766.

    Article  Google Scholar 

  20. Ghasemi. A., et. al. (2005). Collaborative spectrum sensing for opportunistic spectrum access in fading environments. In Proceedings of 1st IEEE international symposium on new frontiers in dynamic spectrum access networks, Baltimore, USA (pp. 131–136).

  21. Verma, G., & Sahu, O. P. (2017). Improved spectrum sharing (ISS) scheme for cognitive radio networks. Wireless Personal Communications, 96(2), 2323–2340.

    Article  Google Scholar 

  22. Wu, J., et. al. (2009). An energy detection algorithm based on double-threshold in cognitive radio systems. In IEEE, 1st international conference on information science and engineering. (ICISE) (pp. 493–496). https://doi.org/10.1109/icise.2009.257.

  23. Zhang, S., et al. (2009). A low-overhead energy detection based cooperative sensing protocol for cognitive radio systems. IEEE Transactions on Wireless Communications, 8(11), 5575–5581.

    Article  Google Scholar 

  24. Shen, J., et al. (2008). Optimisation of cooperative spectrum sensing in cognitive radio network. IET Communications, 3(7), 1170–1178.

    Article  Google Scholar 

  25. Zhang, W., et al. (2009). Optimization of cooperative spectrum sensing with energy detection in cognitive radio networks. IEEE Transactions on Wireless Communications, 8(12), 5761–5766.

    Article  Google Scholar 

  26. Peh, E. C. Y., et al. (2009). Optimization of cooperative sensing in cognitive radio networks: A sensing-throughput tradeoff view. IEEE Transactions on Vehicular Technology, 58(9), 5294–5299.

    Article  Google Scholar 

  27. Sun, C., et. al. (2007). Cooperative spectrum sensing for cognitive radios under bandwidth constraints. In Proceedings of IEEE wireless communication and networking conference, Hong Kong, China (pp. 1–5).

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Correspondence to Gaurav Verma.

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Verma, G., Sahu, O.P. Intelligent Improvement in Throughput of Cognitive Radio. Wireless Pers Commun 99, 1123–1140 (2018). https://doi.org/10.1007/s11277-017-5038-x

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