Journal of Communications and Networks

The Korean Institute of Commucations and Information Sciences (한국통신학회)
권호 표지

Large-Scale Joint Rate and Power Allocation Algorithm Combined with Admission Control in Cognitive Radio Networks

  • Shin, Woo-Jin (School of Information and Communication Engineering, Sungkyunkwan University) ;
  • Park, Kyoung-Youp (School of Information and Communication Engineering, Sungkyunkwan University) ;
  • Kim, Dong-In (School of Information and Communication Engineering, Sungkyunkwan University) ;
  • Kwon, Jang-Woo (Department of Computer Engineering, Tongmyoung University)
  • Received : 2008.10.03
  • Published : 2009.04.30
Download PDF
⟨ Previous Next ⟩

Abstract

In this paper, we investigate a dynamic spectrum sharing problem for the centralized uplink cognitive radio networks using orthogonal frequency division multiple access. We formulate a large-scale joint rate and power allocation as an optimization problem under quality of service constraint for secondary users and interference constraint for primary users. We also suggest admission control to nd a feasible solution to the optimization problem. To implement the resource allocation on a large-scale, we introduce a notion of using the conservative factors $\alpha$ and $\beta$ depending on the outage and violation probabilities. Since estimating instantaneous channel gains is costly and requires high complexity, the proposed algorithm pursues a practical and implementation-friendly resource allocation. Simulation results demonstrate that the large-scale joint rate and power allocation incurs a slight loss in system throughput over the instantaneous one, but it achieves lower complexity with less sensitivity to variations in shadowing statistics.

Keywords

References

  1. Q. Zhao and B. M. Sadler, "A survey of dynamic spectrum access: Signal processing, networking, and regulatory policy," IEEE Signal Process. Mag., pp. 79–89, May 2007
  2. D. I. Kim, E. Hossain, and V. K. Bhargava, "Downlink joint rate and power allocation in cellular multi-rate WCDMA systems," IEEE Trans. Wireless Commun., vol. 2, pp. 69–80, Jan. 2003
  3. L. Le and E. Hossain, "Resource allocation for spectrum underlay in cognitive radio networks," IEEE Trans. Wireless Commun., vol. 7, pp. 5306-5315, Dec. 2008 https://doi.org/10.1109/T-WC.2008.070890
  4. D. I. Kim, L. Le, and E. Hossain, "Joint rate and power allocation for cognitive radios in dynamic spectrum access environment," IEEE Trans. Wireless Commun., vol. 7, pp. 5517-5527, Dec. 2008 https://doi.org/10.1109/T-WC.2008.071465
  5. S. Boyd and L. Vandenberge, Convex Optimization, Cambridge University Press, 2004
  6. S. Boyd, S. J. Kim, L. Vandenberghe, and A. Hassibi, A Tutorial on Geo- metric Programming. [Online]. Available: www.stanford.edu/boyd/research. html
  7. M. Chiang. C. W. Tan." Power control by geometric programming," IEEE Trans. Wireless Commun., vol. 6, pp. 2640-2651, July 2007 https://doi.org/10.1109/TWC.2007.05960
  8. Z.-Q. Luo and W. Yu, "An introduction to convex optimization for communications and signal processing," IEEE J. Sel. Areas Commun., vol. 24, pp. 1426-1438, Aug. 2006 https://doi.org/10.1109/JSAC.2006.879347
  9. J. Papandriopoulos and J. Evans, "Low-complexity distributed algorithms for spectrum balancing in multi-user DSL networks," in Proc. IEEE ICC, vol. 7, June 2006, pp. 3270-3275
  10. C. Cordeiro, K. Challapali, D. Birru, and Sai Shankar, "IEEE 802.22: The first worldwide wireless standard based on cognitive radios," in Proc.IEEE DySPAN, Nov. 2005, pp. 328-337
  11. C. Cordeiro et al., "IEEE 802.22: An introduction to the first wireless standard based on cognitive radios," J. Commun., vol. 1, pp. 38-47, Apr. 2006
  12. D. Tse and P. Viswanath, Fundamentals of Wirelesss Communications, Cambridge University Press, 2005