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Abstract: In Multi-Input Multi-Output (MIMO) systems, Maximum-Likelihood (ML) decoding is equivalent to finding the closest lattice point in an N-dimensional complex space. In general, this problem is known to be NP hard. In this paper, we propose a quasi-maximum likelihood algorithm based on Semi-Definite Programming (SDP). We introduce several SDP relaxation models for MIMO systems, with increasing complexity. We use interior-point methods for solving the models and obtain a near-ML performance... (Update)
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BibTeX entry: (Update)
@misc{ mobasher-near,
author = "Amin Mobasher and Mahmoud Taherzadeh and Renata Sotirov and Amir K. Khandani",
title = "A Near Maximum Likelihood Decoding Algorithm for MIMO Systems Based on
Semi-Definite Programming",
url = "citeseer.ist.psu.edu/mobasher05near.html" }
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