Effective Capacity and Interference Analysis in Multiband Dynamic Spectrum Sensing

Mohamed Elalem, Lian Zhao

.
Electrical and Computer Engineering Department, Ryerson University, Toronto, Canada.

DOI: 10.4236/cn.2013.52011                

Abstract

In this paper, the performance of multichannel transmission in cognitive radio is studied. Both QoS constraints and interference limitations are considered. The activities of the primary users (PU)s are initially detected by cognitive users (CU)s who perform sensing process over multiple channels. They transmit in a single channel at variable power and rates depending on the channel sensing decisions and the fading environment. The cognitive operation is modeled as a state transition model in which all possible scenarios are studied. The QoS constraint of the cognitive users is investigated through statistical analysis. Analytical form for the effective capacity of the cognitive radio channel is found. Optimal power allocation and optimal channel selection criterion are obtained. Impact of several parameters on the transmission performance, as channel sensing parameters, number of available channels, fading and other, are identified through numerical example.

Keywords

Effective Capacity; Cognitive Radio; Multiband Sensing; Interference

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	L. Musavian and S. Aissa, “Quality-of-Service Based Power Allocation in Spectrum-Sharing Channels,” IEEE Global Communication Conference GOLBCOM, New Orleans, 30 November-4 December 2008.
[2]	L. Musavian and S. Aissa, “Adaptive Modulation in Spectrum-Sharing Systems with Delay Constraints,” IEEE International Conference on Communications ICC, Dresden, 14-18 June 2009.
[3]	W. Magnus, F. Oberhettinger and F. Tricomi, “Higher Transcendental Functions,” McGraw Hill, New York, 1982.
[4]	Wolfram Mathematica, the Web’s Most Extensive Mathematics Recourses. http://mathworld.wolfram.com
[5]	D. Wu and R. Negi, “Effective Capacity: A Wireless Link Model for Support of Quality of Service,” IEEE Transactions on Wireless Communication, Vol. 2, No. 4, 2003, pp. 630-643.
[6]	E. Jorswieck, R. Mochaourab and M. Mittelbach, “Effective Capacity Maximization in Multi-Antenna Channels with Covariance Feedback,” IEEE Transactions on Wireless Communication, Vol. 9, No. 10, 2010, pp. 2988-2993. doi:10.1109/TWC.2010.080210.091060
[7]	L. Musavian, S. Aissa and S. Lambotharan, “Effective Capacity for Interference and Delay Constrained Cognitive Radio Relay Channels,” IEEE Transactions on Wireless Communication, Vol. 9, No. 5, 2010, pp. 1698-1707. doi:10.1109/TCOMM.2010.05.090600
[8]	S. Boyd and L. Vandenberghe, “Convex Optimization,” 7th Edition, Cambridge University Press, Cambridge, 2009.
[9]	D. Bertsekas, “Convex Analysis and Optimization,” Athena Scientific, Belmont, 2003.
[10]	R. Yates and D. Goodman, “Probability and Stochastic Processes: A Friendly Introduction for Electrical and Computer Engineers,” 2nd Edition, John Wiley & Sons, Hoboken, 2005, pp. 257-264.