Max-Min SINR Coordinated Multipoint Downlink Transmission-Duality and Algorithms

• Published in: IEEE transactions on signal processing Vol. 60; no. 10; pp. 5384 - 5395
• Main Authors: Cai, D. W. H., Quek, T. Q. S., Chee Wei Tan, Low, S. H.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.10.2012; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Applied sciences; Array signal processing; Beamforming; Closed-form solutions; Decoupling; Detection, estimation, filtering, equalization, prediction; Exact sciences and technology; Exact solutions; Information, signal and communications theory; Interference; Mathematical analysis; multiple-input-multiple-output (MIMO); Optimization; Power control; Projection; Signal and communications theory; Signal processing algorithms; Signal to noise ratio; Signal, noise; Studies; Telecommunications and information theory; Transaction processing; uplink-downlink duality; Vectors; MIMO system; Maximin problem; Downlink; Iterative method; Closed form equation; Algorithm; Data broadcast; Information dissemination; Beam forming; Multicast; Beamforming; Power control; Optimal solution; uplink-downlink duality; Electric power consumption; Signal processing; Signal to interference plus noise ratio; MISO system; Uplink; multiple-input-multiple-output (MIMO)
• ISSN: 1053-587X; 1941-0476
• DOI: 10.1109/TSP.2012.2208631

This paper considers the max-min weighted signal-to-interference-plus-noise ratio (SINR) problem subject to multiple weighted-sum power constraints, where the weights can represent relative power costs of serving different users. First, we study the power control problem. We apply nonlinear Perron-Frobenius theory to derive closed-form expressions for the optimal value and solution and an iterative algorithm which converges geometrically fast to the optimal solution. Then, we use the structure of the closed-form solution to show that the problem can be decoupled into subproblems each involving only one power constraint. Next, we study the multiple-input-single-output (MISO) transmit beamforming and power control problem. We use uplink-downlink duality to show that this problem can be decoupled into subproblems each involving only one power constraint. We apply this decoupling result to derive an iterative subgradient projection algorithm for the problem.