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Low-complexity near-optimal signal detection in underdetermined large-MIMO systems

Datta, Tanumay and Srinidhi, N and Rajan, Sundar B and Chockalingam, A (2012) Low-complexity near-optimal signal detection in underdetermined large-MIMO systems. In: 2012 National Conference on Communications (NCC), 3-5 Feb. 2012, Kharagpur.

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Official URL: http://dx.doi.org/10.1109/NCC.2012.6176823ACTV

Abstract

In this paper, we consider signal detection in nt × nr underdetermined MIMO (UD-MIMO) systems, where i) nt >; nr with a overload factor α = nt over nr >; 1, ii) nt symbols are transmitted per channel use through spatial multiplexing, and iii) nt, nr are large (in the range of tens). A low-complexity detection algorithm based on reactive tabu search is considered. A variable threshold based stopping criterion is proposed which offers near-optimal performance in large UD-MIMO systems at low complexities. A lower bound on the maximum likelihood (ML) bit error performance of large UD-MIMO systems is also obtained for comparison. The proposed algorithm is shown to achieve BER performance close to the ML lower bound within 0.6 dB at an uncoded BER of 10-2 in 16 × 8 V-BLAST UD-MIMO system with 4-QAM (32 bps/Hz). Similar near-ML performance results are shown for 32 × 16, 32 × 24 V-BLAST UD-MIMO with 4-QAM/16-QAM as well. A performance and complexity comparison between the proposed algorithm and the λ-generalized sphere decoder (λ-GSD) algorithm for UD-MIMO shows that the proposed algorithm achieves almost the same performance of λ-GSD but at a significantly lesser complexity.

Item Type: Conference Paper
Additional Information: Copyright of this article belongs to IEEE.
Keywords: Underdetermined MIMO Systems; Near-Optimal Performance, Low-Complexity Detection; Tabu Search; Generalized Sphere Decoder
Department/Centre: Division of Electrical Sciences > Electrical Communication Engineering
Depositing User: Francis Jayakanth
Date Deposited: 06 Feb 2014 07:41
Last Modified: 06 Feb 2014 07:41
URI: http://eprints.iisc.ac.in/id/eprint/48336

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