Layered Tabu Search Algorithm for Large-MIMO Detection and a Lower Bound on ML Performance

Srinidhi, N and Datta, Tanumay and Chockalingam, A and Rajan, Sundar B (2010) Layered Tabu Search Algorithm for Large-MIMO Detection and a Lower Bound on ML Performance. In: IEEE Global Telecommunications Conference (GLOBECOM 2010), DEC 06-10, 2010, Miami, FL.

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Abstract

In this paper, we are concerned with low-complexity detection in large multiple-input multiple-output (MIMO) systems with tens of transmit/receive antennas. Our new contributions in this paper are two-fold. First, we propose a low-complexity algorithm for large-MIMO detection based on a layered low-complexity local neighborhood search. Second, we obtain a lower bound on the maximum-likelihood (ML) bit error performance using the local neighborhood search. The advantages of the proposed ML lower bound are i) it is easily obtained for MIMO systems with large number of antennas because of the inherent low complexity of the search algorithm, ii) it is tight at moderate-to-high SNRs, and iii) it can be tightened at low SNRs by increasing the number of symbols in the neighborhood definition. Interestingly, the proposed detection algorithm based on the layered local search achieves bit error performances which are quite close to this lower bound for large number of antennas and higher-order QAM. For e. g., in a 32 x 32 V-BLAST MIMO system, the proposed detection algorithm performs close to within 1.7 dB of the proposed ML lower bound at 10(-3) BER for 16-QAM (128 bps/Hz), and close to within 4.5 dB of the bound for 64-QAM (192 bps/Hz).

Item Type:	Conference Paper
Series.:	IEEE Global Telecommunications Conference (Globecom)
Publisher:	IEEE
Additional Information:	Copyright 2010 IEEE. Personal use of this material is permitted.However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Keywords:	Large-MIMO detection;local neighborhood search;QR decomposition;ML lower bound;higher-order QAM;high spectral efficiency.
Department/Centre:	Division of Electrical Sciences > Electrical Communication Engineering
Date Deposited:	06 Apr 2011 09:44
Last Modified:	06 Apr 2011 09:44
URI:	http://eprints.iisc.ac.in/id/eprint/36610

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