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Out-sphere decoder for non-coherent ML SIMO detection and its expected complexity

Stojnic, M. and Hassibi, B. (2007) Out-sphere decoder for non-coherent ML SIMO detection and its expected complexity. In: Conference Record of the Forty-first Asilomar Conference on Signals, Systems and Computers. IEEE , Piscataway, NJ, pp. 1568-1572. ISBN 978-1-4244-2109-1.

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In multi-antenna communication systems, channel information is often not known at the receiver. To fully exploit the bandwidth resources of the system and ensure the practical feasibility of the receiver, the channel parameters are often estimated and then employed in the design of signal detection algorithms. However, sometimes communication can occur in an environment where learning the channel coefficients becomes infeasible. In this paper we consider the problem of maximum-likelihood (ML)-detection in singleinput multiple-output (SIMO) systems when the channel information is completely unavailable at the receiver and when the employed signalling at the transmitter is q-PSK. It is well known that finding the solution to this optimization requires solving an integer maximization of a quadratic form and is, in general, an NP hard problem. To solve it, we propose an exact algorithm based on the combination of branch and bound tree search and semi-definite program (SDP) relaxation. The algorithm resembles the standard sphere decoder except that, since we are maximizing we need to construct an upper bound at each level of the tree search. We derive an analytical upper bound on the expected complexity of the proposed algorithm.

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Additional Information:© 2007 IEEE. This work was supported in part by the National Science Foundation under grant no. CCR-0 133818, by Caltech's Lee Center for Advanced Networking, and by a grant from the David and Lucille Packard Foundation.
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Caltech Lee Center for Advanced NetworkingUNSPECIFIED
David and Lucille Packard FoundationUNSPECIFIED
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INSPEC Accession Number 9941759
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:20683
Deposited By: Ruth Sustaita
Deposited On:05 Nov 2010 18:08
Last Modified:03 Oct 2019 02:13

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