Power Control Optimization Algorithm in Cognitive Radio Network

Abstract:

For cognitive radio environment needs of different users, A space-time diversity multi-carrier code division multiple access (OFDM-CDMA) technology architecture of the cognitive radio (CR) system is used, a novel non-cooperative power control algorithm and the price game (NPGP), in order to protect the economic interests of the spectrum of network providers, to achieve a fair and efficient allocation of spectrum resources have cognitive and improve spectrum efficiency. Simulation results show that the algorithm under the protection of the economic spectrum premise network provider benefits, both to ensure the fair and efficient allocation of spectrum resources, and achieve effective control of power users, system performance improved significantly.

• Periodical: Advanced Materials Research (Volumes 926-930)
• Pages: 3669-3672
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.926-930.3669
• Online since: May 2014
• Authors: Guang Long Yang*, Xiao Wang, Xue Zhi Tan
• Keywords: Cognitive Radio (CR), NPGP, Power Control, Pricing Algorithm, SIR

References

[1] S. Haykin, Cognitive radio: brain-empowered wireless communications, IEEE Journal on Selected Areas in Communications, vol. 23, no. 2, pp.201-220, (2005).

DOI: 10.1109/jsac.2004.839380

[2] Q. Jin, D. Yuan, and Z. Guan, Distributed geometric-programming based power control in cellular cognitive radio networks, in Proc. IEEE VTC 2009-Spring, p.1–5, (2009).

DOI: 10.1109/vetecs.2009.5073504

[3] S. Huang, X. Liu, and Z. Ding, Distributed power control for cognitive user access based on primary link control feedback, in Proc. IEEE INFOCOM, p.1–9, (2010).

DOI: 10.1109/infcom.2010.5461916

[4] S. Sun, J. Di, and W. Ni, Distributed power control based on convex optimization in cognitive radio networks, in Proc. 2nd International Conference on Wireless Communications and Signal Processing (WCSP), p.1–6, (2010).

DOI: 10.1109/wcsp.2010.5633676

[5] L. Zhang L, Y-C. Liang, Y. Xin, and H. V. Poor, Robust cognitive beamforming with partial channel state information, IEEE Transactions on Wireless Communications, vol. 8, no. 8, pp.4143-4153, (2009).

DOI: 10.1109/twc.2009.080698

[6] G. Zheng G, K. Wong , and B. Ottersten, Robust cognitive beamforming with bounded channel uncertainties, IEEE Transactions on Signal Processing, vol. 57, no. 12, pp.4871-4881, (2009).

DOI: 10.1109/tsp.2009.2027462

[7] F. Wang and W. Wang, Robust beamforming and power control for multiuser cognitive radio network, IEEE GLOBECOM, p.1–5, (2010).

DOI: 10.1109/glocom.2010.5683735

[8] T. N. Shenouda and M. Davidson. On the design of linear transceivers for multiuser systems with channel uncertainty, " IEEE Journal on Selected Areas in Communications, vol. 26, no. 6, pp.1015-1024, (2008).

DOI: 10.1109/jsac.2008.080817

[9] S. Parsaeefard and A. R. Sharafat, Robust distributed power control in cognitive radio networks, IEEE Transactions on Mobile Computing, vol. 12, no. 4, p.609–620, (2013).

DOI: 10.1109/tmc.2012.28

[10] F. Zhao, B. Li, H. -B. Chen, and X. Z. Lv, Joint beamforming and power allocation for cognitive MIMO systems under imperfect CSI based on game theory, Wireless Personal Communications, vol. 73, no. 3, p.679–694, (2013).

DOI: 10.1007/s11277-013-1210-0