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

Conference Paper


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 ×Nr 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.

UOW Authors


  •   Fang, Licai (external author)
  •   Xu, Lu (external author)
  •   Guo, Qinghua
  •   Huang, Defeng (David) (external author)
  •   Nordholm, Sven (external author)

Publication Date


  • 2014

Citation


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

Scopus Eid


  • 2-s2.0-84922572530

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/3521

Start Page


  • 463

End Page


  • 468

Place Of Publication


  • United States

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 ×Nr 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.

UOW Authors


  •   Fang, Licai (external author)
  •   Xu, Lu (external author)
  •   Guo, Qinghua
  •   Huang, Defeng (David) (external author)
  •   Nordholm, Sven (external author)

Publication Date


  • 2014

Citation


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

Scopus Eid


  • 2-s2.0-84922572530

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/3521

Start Page


  • 463

End Page


  • 468

Place Of Publication


  • United States