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On exact maximum-likelihood detection for non-coherent MIMO wireless systems: A branch-estimate-bound optimization framework

Xu, Weiyu and Stojnic, Mihailo and Hassibi, Babak (2008) On exact maximum-likelihood detection for non-coherent MIMO wireless systems: A branch-estimate-bound optimization framework. In: IEEE International Symposium on Information Theory, 2008. ISIT 2008. IEEE , Piscataway, NJ, pp. 2017-2021. ISBN 978-1-4244-2256-2.

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Fast fading wireless environments pose a great challenge for achieving high spectral efficiency in next generation wireless systems. Joint maximum-likelihood (ML) channel estimation and signal detection is of great theoretical and practical interest, especially for multiple-input multiple-output(MIMO) systems where the multiple channel coefficients need to be estimated. However, this is a hard combinatorial optimization problem, for which obtaining efficient exact algorithms has been elusive for the general MIMO systems. In this paper, we propose an efficient branch-estimate-bound non-coherent optimization framework which provably achieves the exact ML joint channel estimation and data detection for general MIMO systems. Numerical results indicate that the exact joint ML method can achieve substantial performance improvements over suboptimal methods including iterative channel estimation and signal detection. We also derive analytical bounds on the computational complexity of the new exact joint ML method and show that its average complexity approaches a constant times the length of the coherence time, as the SNR approaches infinity.

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Additional Information:© 2008 IEEE. This work was supported in part by the National Science Foundation under grant no. CCR-0729203, by the David and Lucille Packard Foundation, and by Caltech’s Lee Center for Advanced Networking
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David and Lucille Packard FoundationUNSPECIFIED
Caltech’s Lee Center for Advanced NetworkingUNSPECIFIED
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:55137
Deposited By: Shirley Slattery
Deposited On:09 Mar 2020 14:56
Last Modified:03 Oct 2019 08:03

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