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Optimal and Suboptimal Resource Allocation in MIMO Cooperative Cognitive Radio Networks

DOI: 10.1155/2014/190196

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Abstract:

The core aim of this work is the maximization of the achievable data rate of the secondary user pairs (SU pairs), while ensuring the QoS of primary users (PUs). All users are assumed to be equipped with multiple antennas. It is assumed that when PUs are present, the direct communication between SU pairs introduces intolerable interference to PUs and thereby SUs transmit signal using the cooperation of one of the SUs and avoid transmission in the direct channel. In brief, an adaptive cooperative strategy for MIMO cognitive radio networks is proposed. At the presence of PUs, the issue of joint relay selection and power allocation in underlay MIMO cooperative cognitive radio networks (U-MIMO-CCRN) is addressed. The optimal approach for determining the power allocation and the cooperating SU is proposed. Besides, the outage probability of the proposed system is further derived. Due to high complexity of the optimal approach, a low complexity approach is further proposed and its performance is evaluated using simulations. The simulation results reveal that the performance loss due to the low complexity approach is only about 14%, while the complexity is greatly reduced. 1. Introduction Since the issuance of the report of Federal Communications Commission (FCC) in 2002, which revealed the spectrum inefficiency in the incumbent wireless communication systems, cognitive radio (CR) has been regarded as one potential technology to activate the utilization of spectrum resources in the recent evolution of wireless communication systems [1]. As a consequence, the overlay and underlay modes can be developed, based on the definitions of spectrum holes in [1] and the operation modes in [2], to use the white and gray spectrum holes, respectively. Cognitive radio (CR), MIMO communications, and cooperative communications are among the most promising solutions to improve spectrum utilization and efficiency. Dynamic and opportunistic spectrum access allows CR nodes to communicate on temporarily idle or underutilized frequencies. MIMO systems boost spectral efficiency by having a multiantenna node that simultaneously transmit multiple data streams. To further enhance the performance of cognitive radio networks, a cooperative relay network can be incorporated. Thus, in the underlay CR system with an interference temperature (IT) limit, the cooperative relay networks can also be applied to have a better capacity and error rate performance, trade-off between achievable rate and network lifetime, maximum signal-to-interference-plus-noise ratio (SINR) at the destination node,

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.
[2]  Q. Zhao and B. M. Sadler, “A survey of dynamic spectrum access,” IEEE Signal Processing Magazine, vol. 24, no. 3, pp. 79–89, 2007.
[3]  Y. Yu, W. Wang, C. Wang, F. Yan, and Y. Zhang, “Joint relay selection and power allocation with QoS support for cognitive radio networks,” in Proceedings of the IEEE Wireless Communications and Networking Conference (WCNC '13), pp. 4516–4521, Shanghai, China, April 2013.
[4]  K. J. Kim, T. Q. Duong, and X. Tran, “Performance analysis of cognitive spectrum-sharing single-carrier systems with relay selection,” IEEE Transactions on Signal Processing, vol. 60, no. 12, pp. 6435–6449, 2012.
[5]  M. G. Adian and H. Aghaeinia, “Optimal resource allocation for opportunistic spectrum access in multiple-input multiple-output-orthogonal frequency division multiplexing based cooperative cognitive radio networks,” IET Signal Processing, vol. 7, no. 7, pp. 549–557, 2013.
[6]  P. Ubaidulla and S. A?ssa, “Optimal relay selection and power allocation for cognitive two-way relaying networks,” IEEE Wireless Communications Letters, vol. 1, no. 3, pp. 225–228, 2012.
[7]  L. Li, X. Zhou, H. Xu, G. Y. Li, D. Wang, and A. Soong, “Simplified relay selection and power allocation in cooperative cognitive radio systems,” IEEE Transactions on Wireless Communications, vol. 10, no. 1, pp. 33–36, 2011.
[8]  P. Li, S. Guo, W. Zhuang, and B. Ye, “On efficient resource allocation for cognitive and cooperative communications,” IEEE Journal on Selected Areas in Communications, vol. 32, no. 2, pp. 264–273, 2014.
[9]  M. G. Adian, H. Aghaeinia, and Y. Norouzi, “pectrum sharing and power allocation in multi-input-multi-output multi-band underlay cognitive radio networks,” IET Communications, vol. 7, no. 11, pp. 1140–1150, 2013.
[10]  M. G. Adian and H. Aghaeinia, “An auction-based approach for spectrum leasing in cooperative cognitive radio networks: when to lease and how much to be leased,” Wireless Networks, vol. 20, pp. 411–422, 2014.
[11]  M. G. Adian and H. Aghaeinia, “Spectrum sharing and power allocation in multiple-in multiple-out cognitive radio networks via pricing,” IET Communications, vol. 6, no. 16, pp. 2621–2629, 2012.
[12]  M. G. Adian and H. Aghaeinia, “Resource allocation in MIMO-OFDM based cooperative cognitive radio networks,” IEEE Transactions on Communications, vol. 62, no. 7, pp. 2224–2235, 2014.
[13]  M. G. Adian and H. Aghaeinia, “Low complexity resource allocation in MIMO-OFDM-based cooperative cognitive radio networks,” Transactions on Emerging Telecommunications Technology, 2014.
[14]  M. G. Adian, “Beamforming with reduced complexity in MIMO cooperative cognitive radio networks,” Journal of Optimization, vol. 2014, Article ID 325217, 10 pages, 2014.
[15]  M. G. Adian and H. Aghaeinia, “Optimal resource allocation in heterogeneous MIMO cognitive radio networks,” Wireless Personal Communication, vol. 76, no. 1, pp. 23–39, 2014.
[16]  M. G. Adian and H. Aghaeinia, “A two-level cooperative game-based approach for joint relay selection and distributed resource allocation in MIMO-OFDM-based cooperative cognitive radio networks,” Transactions on Emerging Telecommunications Technology, 2014.
[17]  J. Liu, N. B. Shroff, and H. D. Sherali, “Optimal power allocation in multi-relay MIMO cooperative networks: theory and algorithms,” IEEE Journal on Selected Areas in Communications, vol. 30, no. 2, pp. 331–340, 2012.
[18]  C. Stevenson, G. Chouinard, Z. Lei, W. Hu, S. Shellhammer, and W. Caldwell, “IEEE 802.22: the first cognitive radio wireless regional area network standard,” IEEE Communications Magazine, vol. 47, no. 1, pp. 130–138, 2009.
[19]  J. Jia, J. Zhang, and Q. Zhang, “Cooperative relay for cognitive radio networks,” in Proceedings of the 28th Conference on Computer Communications (INFOCOM '09), pp. 2304–2312, IEEE, Rio de Janeiro, Brazil, April 2009.
[20]  V. Brik, E. Rozner, S. Banerjee, and P. Bahl, “DSAP: a protocol for coordinated spectrum access,” in Proceedings of the 1st IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks (DySPAN '05), pp. 611–614, November 2005.
[21]  G. Zhao, C. Yang, G. Y. Li, D. Li, and A. C. K. Soong, “Power and channel allocation for cooperative relay in cognitive radio networks,” IEEE Journal on Selected Topics in Signal Processing, vol. 5, no. 1, pp. 151–159, 2011.
[22]  G. Bansal, M. J. Hossain, and V. K. Bhargava, “Optimal and suboptimal power allocation schemes for OFDM-based cognitive radio systems,” IEEE Transactions on Wireless Communications, vol. 7, no. 11, pp. 4710–4718, 2008.
[23]  Y. Ma, D. I. Kim, and Z. Wu, “Optimization of OFDMA-based cellular cognitive radio networks,” IEEE Transactions on Communications, vol. 58, no. 8, pp. 2265–2276, 2010.
[24]  X. Kang, H. Garg, Y. Liang, and R. Zhang, “Optimal power allocation for OFDM-based cognitive radio with new primary transmission protection criteria,” IEEE Transactions on Wireless Communications, vol. 9, no. 6, pp. 2066–2075, 2010.
[25]  L. Zhang, Y.-C. Liang, and Y. Xin, “Joint beamforming and power allocation for multiple access channels in cognitive radio networks,” IEEE Journal on Selected Areas in Communications, vol. 26, no. 1, pp. 38–51, 2008.
[26]  L. Zhang, Y. Xin, Y. Liang, and H. V. Poor, “Cognitive multiple access channels: optimal power allocation for weighted sum rate maximization,” IEEE Transactions on Communications, vol. 57, no. 9, pp. 2754–2762, 2009.
[27]  S. Boyd and L. Vandenberghe, Convex Optimization, Cambridge University Press, 2004.
[28]  W. Yu and R. Lui, “Dual methods for nonconvex spectrum optimization of multicarrier systems,” IEEE Transactions on Communications, vol. 54, no. 7, pp. 1310–1322, 2006.
[29]  E. Telatar, “Capacity of multi-antenna Gaussian channels,” European Transactions on Telecommunications, vol. 10, no. 6, pp. 585–598, 1999.
[30]  E. Biglieri, G. Caire, and G. Taricco, “Limiting performance of block-fading channels with multiple antennas,” IEEE Transactions on Information Theory, vol. 47, no. 4, pp. 1273–1289, 2001.
[31]  B. M. Hochwald, T. L. Marzetta, and V. Tarokh, “Multiple-antenna channel hardening and its implications for rate feedback and scheduling,” IEEE Transactions on Information Theory, vol. 50, no. 9, pp. 1893–1909, 2004.
[32]  X. Tang and Y. Hua, “Optimal design of non-regenerative MIMO wireless relays,” IEEE Transactions on Wireless Communications, vol. 6, no. 4, pp. 1398–1407, 2007.

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