Title

A hybrid iterative MIMO detection algorithm: Partial Gaussian approach with integer programming

RIS ID

98504

Publication Details

L. Fang, L. Xu, Q. Guo, D. Huang & S. Nordholm, "A hybrid iterative MIMO detection algorithm: Partial Gaussian approach with integer programming," in Communications in China (ICCC), 2014 IEEE/CIC International Conference on, 2014, pp. 463-468.

Abstract

In this paper, after showing MMSE-SIC suffers from performance loss when the channel is spatially correlated for Massive MIMO, we propose an effective hybrid iterative detection algorithm named partial Gaussian approach with integer programming (PGA-IP) to handle correlated channels. In PGA-IP, a partial gaussian approach is first employed to reduce the massive MIMO detection (with large dimension Nt xNr MIMO channel) to a problem of marginalizing M (M is a parameter and M蠐 Nt, Nr) discrete valued symbols over an M-degree quadratic function. Then we employ integer programming which is a tree based branch-and-bound search algorithm to further reduce the complexity of the M-dimensional marginalization. Simulation results show that the proposed PGA-IP outperforms MMSE-SIC by about 5dB under heavily correlated channel with only several times of increased computational complexity. At the same time, with about 5% of the complexity of the exact PGA algorithm, the proposed PGA-IP only suffers marginal performance penalty.

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Link to publisher version (DOI)

http://dx.doi.org/10.1109/ICCChina.2014.7008322