Maximum Sum-Rate Interference Alignment Algorithms for MIMO Channels

• Published in: 2010 IEEE Global Telecommunications Conference GLOBECOM 2010 pp. 1 - 6
• Main Authors: Santamaria, Ignacio, Gonzalez, Oscar, Heath, Robert W, Peters, Steven W
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.12.2010
• Subjects: Convergence; Decoding; Interference channels; MIMO; Minimization; Signal to noise ratio
• ISBN: 1424456363; 9781424456369
• ISSN: 1930-529X
• DOI: 10.1109/GLOCOM.2010.5683919

Alternating minimization algorithms are typically used to find interference alignment (IA) solutions for multiple-input multiple-output (MIMO) interference channels with more than K=3 users. For these scenarios many IA solutions exit, and the initial point determines which one is obtained upon convergence. In this paper, we propose a new iterative algorithm that aims at finding the IA solution that maximizes the average sum-rate. At each step of the alternating minimization algorithm, either the precoders or the decoders are moved along the direction given by the gradient of the sum-rate. Since IA solutions are defined by a set of subspaces, the gradient optimization is performed on the Grassmann manifold. The step size of the gradient ascent algorithm is annealed to zero over the iterations in such a way that during the last iterations only the interference leakage is being minimized and a perfect alignment solution is finally reached. Simulation examples are provided showing that the proposed algorithm obtains IA solutions with significant higher throughputs than the conventional IA algorithms.