Abstract
Efficient resource allocation is a major challenge in cognitive radio networks, especially when Cognitive Users (CUs) share the same frequency band with the Primary User. In this paper, we consider minimizing the total power consumption by combining power control, rate control and adaptive modulation. We analyze the existence, uniqueness and Pareto optimality of Nash Equilibrium (NE) in the power control game, and propose an iterative algorithm to find the NE followed by the adjustment of both the transmission rate and modulation scheme based on the convergent power. If compared with previous works, the key feature of the proposed strategy is that each CU can prolong its battery life in energy-constrained networks to support heterogenous services with different transmission rates and modulation schemes requirements. Simulation results are provided to confirm the effectiveness of the proposed method in power saving, improvement of both the transmission rate and the spectral efficiency and the simplicity of implementation.
Explore related subjects
Discover the latest articles and news from researchers in related subjects, suggested using machine learning.References
Cabric, D., Mishra, S. M., & Brodersen, R. W. (2004). Implementation issues in spectrum sensing for cognitive radios. In Proceedings of the Asilomar conference on signals, systems, computers (pp. 772–776). Nov. 2004.
Zhao Q., Sadler B. M. (2007) A survey of dynamic spectrum access. IEEE Signal Processing Magazine 24(3): 79–89
Peha J. M. (2005) Approaches to spectrum sharing. IEEE Communications Magazine 43(2): 10–12
Wang F., Krunz M., Cui S. (2008) Price-based spectrum management in cognitive radio networks. IEEE Journal of Selected Topics in Signal Processing 2(1): 74–87
Zhou, P., Yuan, W., Liu, W., & Cheng, W. (2008). Joint power and rate control in cognitive radio networks: A game-theoretical approach. In Proceedings of the IEEE conference on communication (pp. 3296–3301). May 2008
Jayaweera S. K., Li T. (2009) Dynamic spectrum leasing in cognitive radio networks via primary-secondary user power contrl games. IEEE Transactions on Wireless Communications 8(6): 3300–3310
Wu, Y., & Tsang, D. H. K. (2009). Distributed power allocation algorithm for spectrum sharing cognitive radio networks with QoS guarantee. In Proceedings of the IEEE conference on computer communication (pp. 981–989). Apr. 2009
Rappaport T. S. (1996) Wireless communications principles and practice. Prentice Hall Inc, Englewood Cliffs
Fudenberg D., Tirole J. (1991) Game theory. MIT Press, Cambridge
Yates R. D. (1995) A framework for uplink power control in cellular radio systems. IEEE Journal on Selected Areas in Communications 1(7): 1341–1347
Huang W. L., Letaief K. B. (2007) Cross-layer scheduling and power control combined with adaptive modulation for wireless ad hoc networks. IEEE Transactions on Communications 55(4): 726–739
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Li, D. Joint Power and Rate Control Combined with Adaptive Modulation in Cognitive Radio Networks. Wireless Pers Commun 63, 549–559 (2012). https://doi.org/10.1007/s11277-010-0149-7
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11277-010-0149-7