PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

A probabilistic approach to Integer Least Squares and MIMO decoding
Yosi Keller and amir leshem
IEEE Transactions on Signal Processing 2010.


In this work we propose a novel probabilistic approach to solving the integer least squares (ILS) problem, where the unknown variables are constrained to be in a finite set. First, we introduce a novel subspace projection operator that estimates the pairwise assignment probabilities of the ILS variables. Thus, we cast the ILS as a probabilistic inference problem. Second, we formulate the ILS inference as a pairwise assignment problem and propose a computationally efficient spectral approach to its solution. We demonstrate our approach by applying it to MIMO decoding, a problem that attracted significant research interest. This provides a viable set of baseline algorithms to compare against. Under a wide range of conditions our method compares favorably with contemporary state-of-the-art MIMO decoding schemes.

EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
ID Code:5834
Deposited By:Yosi Keller
Deposited On:17 March 2011