Intelligent Improvement in Throughput of Cognitive Radio
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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.
KeywordsCognitive radio Threshold Single threshold Low SNR Spectrum sensing
- 1.Federal Communications Commission. (2002). Spectrum policy task force report. In FCC 02-155.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.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).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).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.
- 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.
- 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).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.
- 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).Google Scholar