Gaussian Belief Propagation Based Multiuser Detection

Abstract

In this work, we present a novel construction for solving the linear multiuser detection problem using the Gaussian Belief Propagation algorithm. Our algorithm yields an efficient, iterative and distributed implementation of the MMSE detector. We compare our algorithm's performance to a recent result and show an improved memory consumption, reduced computation steps and a reduction in the number of sent messages. We prove that recent work by Montanari et al. is an instance of our general algorithm, providing new convergence results for both algorithms.

6 pages, 1 figures, appeared in the 2008 IEEE International Symposium on Information Theory, Toronto, July 2008

References in corpus (3)

• Gaussian Belief Propagation Solver for Systems of Linear Equations
• Improved message passing for inference in densely connected systems
• Efficient Bayesian Inference for Learning in the Ising Linear Perceptron and Signal Detection in CDMA

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