Distributed Cooperative Multicell Beamforming Based on a Viewpoint of Layered Channel

In this paper, a distributed cooperative multicell beamforming algorithm is proposed, and a detail analysis and solving method for instantaneous and statistical channel state information (CSI) are presented. Firstly, an improved distributed iterative beamforming algorithm is proposed for the multiple-input single-output interference channel (MISO IC) scenario which chooses virtual signal-to-interference-and-noise (SINR) as decision criterion to initialize and then iteratively solves the constrained optimization problem of maximizing the virtual SINR for a given level of generated interference to other users. Then, the algorithm is generalized to the multicell date sharing scenario with a heuristics power allocation scheme based on a viewpoint of the layered channel. Finally, the performance is illustrated through numerical simulations.

[1]  David Gesbert,et al.  Distributed Multicell-MISO Precoding Using the Layered Virtual SINR Framework , 2010, IEEE Transactions on Wireless Communications.

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

[3]  Johannes Lindblom,et al.  Cooperative beamforming for the MISO interference channel , 2010, 2010 European Wireless Conference (EW).

[4]  Erik G. Larsson,et al.  The MISO interference channel from a game-theoretic perspective: A combination of selfishness and altruism achieves pareto optimality , 2008, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing.

[5]  E.G. Larsson,et al.  Pareto-optimal beamforming for the MISO interference channel with partial CSI , 2009, 2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP).

[6]  Randa Zakhour,et al.  Coordination on the MISO interference channel using the virtual SINR framework , 2009 .

[7]  Emil Björnson,et al.  Distributed Multicell and Multiantenna Precoding: Characterization and Performance Evaluation , 2009, GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference.

[8]  Daniel Pérez Palomar,et al.  Rank-Constrained Separable Semidefinite Programming With Applications to Optimal Beamforming , 2010, IEEE Transactions on Signal Processing.

[9]  Ming Chen,et al.  Cooperative distributed antenna systems for mobile communications [Coordinated and Distributed MIMO] , 2010, IEEE Wireless Communications.

[10]  Erik G. Larsson,et al.  Complete Characterization of the Pareto Boundary for the MISO Interference Channel , 2008, IEEE Transactions on Signal Processing.

[11]  B. Ottersten,et al.  On the principles of multicell precoding with centralized and distributed cooperation , 2009, 2009 International Conference on Wireless Communications & Signal Processing.