International Journal of Wireless Communications and Mobile Computing
Volume 6, Issue 1, March 2018, Pages: 31-36
Received: Dec. 31, 2017;
Accepted: Jan. 30, 2018;
Published: Feb. 12, 2018
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Mohan Premkumar, Department of Electronics and Communication Engineering, Panimalar Institute of Technology, Chennai, India
Muthappa Perumal Chitra, Department of Electronics and Communication Engineering, Panimalar Institute of Technology, Chennai, India
This research paper is intended to derive, simulate and analyze the capacity of cognitive radio (CR) system in fading channels. Capacity being an information theoretic perspective for a wireless system plays a role in the amount of information bits which can be transmitted. As wireless channel is subjected to multipath effects in a CR system caused by fading, capacity analysis needs to be done. Simulation carried out in terms of capacity, mean square error for channel estimation and bit error rate (BER) for the proposed system model of cognitive radio can give valuable information about performance of CR system in terms of data bits handling capacity. The amount of capacity in flat fading channels and frequency selective fading channels are simulated. The obtained results in terms of capacity can be used as reference for further analysis to be explored relating to design of cognitive radio systems for developing applications for 5G systems.
Muthappa Perumal Chitra,
Analysis of Cognitive Radio Capacity in Fading Channels, International Journal of Wireless Communications and Mobile Computing.
Vol. 6, No. 1,
2018, pp. 31-36.
J. Mitola III “Cognitive Radio”, Licentiate Proposal, KTH Stockhom, Sweden 1998.
J. Mitola III, “Cognitive Radio: An intelligent agent Architecture for Software Defined Radio” Ph.D Thesis KTH Royak Institute of Technology, Sweden, 2000.
S. Haykin, “Cognitive radio:Brain-empowered wireless communications ”, IEEE J. Sel. Areas Commun., vol. 23, no. 2, pp. 201-220, Feb 2005.
C. X. wang, X. Hong, H. H. Chen and J. Thompson, “On capacity of cognitive radio networks with average interference power constraints” IEEE Transactions on Wireless Communications, vol. 8, no. 4, pp. 1620-1625, April 2009.
H. A. Suraweera, P. J. Smit hand M. Shafi, “ Capacity limits and performance analysis of cognitive radio with imperfect channel knowledge” IEEE Transactions on Vehicular Technology, vol. 59, no. 4, pp. 1811-1822, May 2010.
X. Hong, C. X. Wang, M. Uysal, X. Ge and S. Ouyang, “Capacity of hybrid cognitive radio networks with distributed VAAs” IEEE Transactions on Vehicular Technology, vol. 59, no. 7, pp 3510-3523, September 2010.
Y. liu, D. xu, Z. Feng and P. Zhang, “Outage capacity of cognitive radio in rayleigh fading environments with imperfect channel information” Journal of Information & Computational Science, pp 955–968, April 2012.
A. Gopalakrishna and D. B. Ha, “Capacity analysis of Cognitive Radio Rela networks with interference power constraings in fading channels”, in International Conference on Computing, Management and Telecommunications (ComManTel) pp. 111-116, Jan 2013.
K. A. Qaraqe, S. Ekin, T. Agarwal and E. Serpedin, “Performance analysis of cognitive radio multiple-access channels over dynamic fading environments” Wireless Personal Communications, pp 1031–1045, April 2013.
S. Akin and M. C. Gursoy, “Performance analysis of cognitive radio systems with imperfect channel sensing and estimation” IEEE Transactions on Communications, vol. 63, no. 5, pp 1554-1566, May 2015.
Dr. M. Prem Kumar, Dr. M. P. Chitra, M. Arun and M. S. Saravanan, “Least squares based channel estimation approach and bit error rate analysis of cognitive radio” International conference on robotics, automation, control and embedded systems-RACE 2015, 18-20 February 2015.
H. F. Al-Doseri and M. A. Mangoud, “Performance Analysis of Cooperative Spectrum Sensing Under Guaranteed Throughput Constraints for Cognitive Radio Networks”, Journal of Computer Networks and Communications, vo l.16, no. 5, March 2016.
A. Kaushik, S. K. Sharma, S. Chatzinotas, B. Ottersen and F. Jondral, “Performance Analysis of Hybrid Cognitive Radio Systems with Imperfect Channel Knowledge”, Proc. of. IEEE International Conference on Communications (ICC), May 2016.
P. Thakur, A. Kumar, S. Pandit, G. Singh, S. N. Satashia, “ Performance Analysis of Cognitive Radio Networks using Channel-Prediction-Probabilities and Improved Frame Structure”, Elsevier Journal Digital Communication aand Networks, Sept 2017 https://doi.org/10.1016/j.dcan.2017.09.012.
Y. Zhao and L/ Bai, “Performance Analysis and Optimization for Cognitive Radio Networks with Classified Secondary Users and Impatient Packets”, Hindawi Mobile Information Systems, volume 2017, article ID 3613496, 2017.