The Waterfilling Based Subcarrier and Power Allocation for OFDM Cognitive Radio Networks

Article Preview

Abstract:

In this paper, the subcarrier and power allocation problem for the orthogonal frequency division multiplexing (OFDM) cognitive radio network which coexists with the primary network is studied. Specifically, in consideration of both transmit power constraints of secondary users and interference power constraint at each primary receiver. A cognitive waterfilling (CWF) power allocation algorithm which based upon the classical waterfilling mechanism is proposed for the single SU and multi-PU scenario. As for the multi-SU and multi-PU case, we present an efficient joint subcarrier and power allocation algorithm called MS-CWF algorithm with low complexity. Simulation results show the effectiveness of the proposed CWF and MS-CWF algorithms.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

406-412

Citation:

Online since:

December 2012

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2013 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] S. Haykin, Cognitive radio: Brain-empowered wireless communications, IEEE J. Select. Areas Commun., vol. 23, no. 2, p.201–220, Feb. (2005).

DOI: 10.1109/jsac.2004.839380

Google Scholar

[2] G. Bansal, J. Hossian, K. Bhargava, Optimal and suboptimal power allocation schemes for OFDM-based cognitive radio systems, IEEE Trans. on Wireless Commun., vol. 7, no. 11, p.4710–4718, Nov. (2008).

DOI: 10.1109/t-wc.2008.07091

Google Scholar

[3] P. Cheng, Z. Zhang, H. -H. Chen, and P. Qiu, Optimal distributed joint frequency, rate, and power allocation in cognitive OFDMA systems, IET Commun., vol. 2, no. 6, Jul. 2008, p.815–826.

DOI: 10.1049/iet-com:20070358

Google Scholar

[4] Z. Yonghong, and L. Cyril, Resource allocation in an OFDM-based cognitive radio system, IEEE Commun. Letters, vol. 57, no. 7, p.1928–1931, July (2009).

Google Scholar

[5] Rui Zhang. Shuguang Cui, and Ying-Chang Liang. On ergodic sum capacity of fading cognitive multiple-access and broadcast channels, IEEE Trans. Inf. Theory, vol. 55, Nov. 2009: 5161–5178.

DOI: 10.1109/tit.2009.2030449

Google Scholar

[6] S. Boyd and L. Vandenberghe, Convex Optimization, Cambridge, UK: Cambridge University Press, (2004).

Google Scholar

[7] Y. Ma, Y. Xu, D. Zhang, Joint Subcarrier and Power Allocation for Uplink Spectrum Sharing in Cognitive OFDMA Networks: A Waterfilling-Based Approach, [Online]. Available: arxiv. org/abs/1009. 4101v1.

DOI: 10.4028/www.scientific.net/amr.756-759.1979

Google Scholar

[8] C. Y. Ng, C. W. Sung, Low Complexity Subcarrier and Power Allocation for Utility Maximization in Uplink OFDMA Systems, IEEE Trans. On wireless Commun., vol. 7, no. 5, May 2008: 1667 – 1675.

DOI: 10.1109/twc.2008.060723.

Google Scholar

[9] J. Jang and K. B. Lee, Transmit power adaptation for multiuser OFDM systems, IEEE J. Sel. Areas Commun., vol. 21, pp.171-178, Feb. (2003).

DOI: 10.1109/jsac.2002.807348

Google Scholar

[10] A. Mehrotra, GSM System Engineering. Boston, MA: Artech House, (1996).

Google Scholar