SINR Balancing Technique for Downlink Beamforming in Cognitive Radio Networks

We propose a novel signal to interference and noise (SINR) balancing technique for a downlink cognitive radio network (CRN) wherein multiple cognitive users (also referred to as secondary users (SUs)) coexist and share the licensed spectrum with the primary users (PUs) using the underlay approach. The proposed beamforming technique maximizes the worst SU SINR while ensuring that the interference leakage to PUs is below specific thresholds. Due to the additional interference constraints imposed by PUs, the principle of uplink-downlink duality used in the conventional downlink beamformer design cannot be directly applied anymore. To circumvent this problem, using an algebraic manipulation on the interference constraints, we propose a novel SINR balancing technique for CRNs based on uplink-downlink iterative design techniques. Simulation results illustrate the convergence and the optimality of the proposed beamformer design.

[1]  Nikos D. Sidiropoulos,et al.  Spectrum Sharing in Wireless Networks via QoS-Aware Secondary Multicast Beamforming , 2009, IEEE Transactions on Signal Processing.

[2]  K. Cumanan,et al.  SINR Balancing Technique and its Comparison to Semidefinite Programming Based QoS Provision for Cognitive Radios , 2009, VTC Spring 2009 - IEEE 69th Vehicular Technology Conference.

[3]  L. C. Godara,et al.  Handbook of Antennas in Wireless Communications , 2001 .

[4]  Joseph Mitola,et al.  Cognitive radio: making software radios more personal , 1999, IEEE Wirel. Commun..

[5]  Leandros Tassiulas,et al.  Transmit beamforming and power control for cellular wireless systems , 1998, IEEE J. Sel. Areas Commun..

[6]  Weidong Yang,et al.  Optimal downlink power assignment for smart antenna systems , 1998, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181).

[7]  Holger Boche,et al.  Solution of the multiuser downlink beamforming problem with individual SINR constraints , 2004, IEEE Transactions on Vehicular Technology.

[8]  Leandros Tassiulas,et al.  Convex approximation techniques for joint multiuser downlink beamforming and admission control , 2008, IEEE Transactions on Wireless Communications.

[9]  K. Cumanan,et al.  Robust interference control techniques for multiuser cognitive radios using worst-case performance optimization , 2008, 2008 42nd Asilomar Conference on Signals, Systems and Computers.

[10]  Vahid Tarokh,et al.  Interference Reduction by Beamforming in Cognitive Networks , 2008, IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference.

[11]  Paul Tseng.  Further Results on Approximating Nonconvex Quadratic Optimization by Semidefinite Programming Relaxation , 2003, SIAM J. Optim..

[12]  Yinyu Ye,et al.  Interior point algorithms: theory and analysis , 1997 .

[13]  H. Vincent Poor,et al.  On Gaussian MIMO BC-MAC duality with multiple transmit covariance constraints , 2008, 2009 IEEE International Symposium on Information Theory.

[14]  Khaled Ben Letaief,et al.  Joint Beamforming and Scheduling in Cognitive Radio Networks , 2007, IEEE GLOBECOM 2007 - IEEE Global Telecommunications Conference.

[15]  Ying-Chang Liang,et al.  Exploiting Multi-Antennas for Opportunistic Spectrum Sharing in Cognitive Radio Networks , 2007, IEEE Journal of Selected Topics in Signal Processing.

[16]  Tung-Sang Ng,et al.  Robust beamforming in cognitive radio , 2009, IEEE Transactions on Wireless Communications.