Share This Article:

Spectrum Efficiency Improvement Based on the Cognitive Radio Management

Abstract Full-Text HTML Download Download as PDF (Size:291KB) PP. 280-288
DOI: 10.4236/ijcns.2010.33036    5,298 Downloads   9,701 Views   Citations
Author(s)    Leave a comment


Interference and delay are considered as the major reasons limiting the capacity and increasing the new call blocking probability in cellular system. In this paper we introduce a novel strategy based on cognitive radio. Cognitive radio is defined as a radio or system that senses its environment and can dynamically and autonomously change its transmitter parameters based on interaction with the environment in which it operates, such as maximize throughput and reduce interference. The goal of the use of cognitive radio is to improve the spectrum efficiency in cellular system. Spectrum management based on radio cognitive plays thereby an important role to increase the capacity of the radio systems and spectrum utilization, especially in the context of open spectrum.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

J. Raiyn, "Spectrum Efficiency Improvement Based on the Cognitive Radio Management," International Journal of Communications, Network and System Sciences, Vol. 3 No. 3, 2010, pp. 280-288. doi: 10.4236/ijcns.2010.33036.


[1] N. D. Tripathi, et al., “Handoff in cellular systems,” IEEE Personal Communications, December 1998.
[2] B. Friedlander and S. Scherzer, “Beamforming versus transmit diversity in the downlink of a cellular communication,” IEEE Transactions on Vehicular Technology, Vol. 53, No. 53, July 2004.
[3] C. W. Leong, W. Zhuang, Y. Cheng, and L. Wang, “Optimal resource allocation and adaptive call admission control for voice/data integrated cellular networks,” IEEE Transactions on Vehicular Technology, Vol. 55, No. 2, March 2006.
[4] L. Cong, et al., “Performance analysis of dynamic channel assignment algorithms in cellular mobile systems with hand-off,” International Journal of Communication Systems, July 2002.
[5] S. S. Manvi and P. Venkataram, “Agent based subsystem for multimedia communications,” IEE Proceedings Software, Vol. 153, No.1, February 2006.
[6] S. Anand, A. Sridharan, and K. N. Sivarajan, “Performance analysis of channlized cellular systems with dynamic channel allocation,” IEEE Transactions on Vehicular Technology, Vol. 52, No. 4, July 2003.
[7] T. Ren and R. J. La, “Downlink beamformig algorithms with inter-cell interference in cellular networks,” IEEE Transactions on Wireless Communications, Vol. 5, No.10, October 2006.
[8] M. Zafer and E. Modiano, “Blocking probability and channel assignment in wireless networks,” IEEE Transactions on Wireless Communications, Vol. 5, No. 4, April 2006.
[9] S. Gupta and P. Srimani, “Distributed dynamic channel allocation in mobile networks: Combining search and update,” The Journal Supercomputing, Vol. 17, No. 1, August 2000.
[10] S. Kandukuri and S. Boyd, “Optimal power control in interference limited fading wireless channels with outage probability specifications,” IEEE Transactions on Wireless Communications, Vol. 1, No. 1, January 2002.
[11] C. J. Chen and L. W. Wang, “Impacts of radio channel characteristics, heterogeneous traffic intensity, and near- far effect on rate adaptive scheduling algorithms,” IEEE Transactions on Vehicular Technology, Vol. 55, No. 5, September 2006.
[12] J. Raiyn, et al., “Using adaptive agent-based on iterative distributed swapping prediction for interference reduction in cellular systems, international symposium on performance evaluation of computer and telecommunication systems,” Endinburgh, U.K., 16–18 June 2008.
[13] M. Bublin, M. Kongegger, and P. Slanina, “A cost-function-based dynamic channel allocation and its limits,” IEEE Transactions on Vehicular Technology, Vol. 56, No. 4, July 2007.
[14] M. S. Do, Y. Park, and J. Y. Lee, “Channel assignment with QoS guarantees for a multiclass multicode CDMA system,” IEEE Transactions on Vehicular Technology, Vol. 51, pp. 935–948, September 2002.
[15] A. Seth, H. M. Gupta, and K. Momaya, “Quality of service parameters in cellular mobile communication,” International Journal of Mobile Communications, Vol. 5, No. 1, pp. 65–93, 2007.
[16] S. Zhao, Z. Xiong, and X. Wang, “Optimal resource allocation for wireless video over CDMA networks,” IEEE Transaction on Mobile Computing, Vol. 4, No. 1, pp. 441–424, January–February 2005.
[17] G. J. Foschini and Z. Miljanic, “A simple distribute autonomous power control algorithm and its convergence,” IEEE Transactions on Vehicular Technology, Vol. 42, No. 4, pp. 641–646, November 1993.
[18] S. A. Grandhi, J. Zander, and R. Yates, “Constrained power control,” Wireless Personal Communications, Vol. 1, No. 4, pp. 257–270, 1995.
[19] B. C. Jung, Y. J. Hong, D. K. Sung, and S. Y. Chung, “Fixed power allocation with nulling for TDD-based cellular uplink,” IEEE Communications Letters, Vol. 12, No. 4, April 2008.
[20] X. Li and D. Wu, “Power control and channel allocation for real time applications in cellular networks,” Wireless Communications and Mobile Computing, Vol. 8, No. 6, pp. 705–713, 2007.
[21] J. L. Eaves and E. K. Reely, “Principles of modern radar,” Van Nostrand Reinhold Company, New York, 1987.
[22] G. J. Foschini and Z. Miljanic, “Distributed autonomous wireless channel assignment algorithm with power control,” IEEE Transactions on Vehicular Technology, Vol. 44, No. 3, pp. 420–429, August 1995.
[23] D. Beckmann and U. Killat, “A new strategy for the application of genetic algorithms to channel assignment problem,” IEEE Transactions on Vehicular Technology, Vol. 48, No. 4, pp. 1261–1269, 1999.
[24] M. Bergounioux and K. Kunisch, “On the structure of Lagrange multipliers for state-constrained optimal control problems,” Optimization and Control of Distributed Systems, Vol. 48, No. 3–4, pp. 169–176, March 2003.
[25] S. Hykin, J. D. Thomson, and H. J. Reed, “Spectrum sensing for cognitive radio,” Proceedings of the IEEE, Vol. 97, No. 5, pp. 849–877, May 2009.

comments powered by Disqus

Copyright © 2018 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.