Modified QRM-ML Detection by Stage Reduction in MIMO Systems

Gunyoung Ko (고건영); SangKyu Park (박상규); Kwangmin Hyun (현광민)

Modified QRM-ML Detection by Stage Reduction in MIMO Systems

Journal of Knowledge Information Technology and Systems
Abbr : JKITS
2015, 10(1), pp.79-87
Publisher : Korea Knowledge Information Technology Society
Research Area : Interdisciplinary Studies > Interdisciplinary Research
Published : February 28, 2015

Gunyoung Ko ¹, SangKyu Park ¹, Kwangmin Hyun ²

¹한양대학교
²강릉원주대학교

Accredited

ABSTRACT

In this paper, modified QRM-ML detection algorithm is proposed to reduce computational complexity of the conventional QRM-ML detection algorithm in MIMO systems. We consider a stage reduction algorithm to QRM-ML detection algorithm and arrange all steps of each stage and computational complexity, which is calculated the number of multiplications per each step. The proposed detection algorithm has lower complexity than full candidates of QRM-ML detection algorithm. It also has no saturation on BER performance and better performance in high SNR than QRM-ML detection algorithm of lower candidates, which has a similar complexity to proposed algorithm. We also set a new arbitrary parameter which can adjust the number of reduced stages, and it can be selected by considering a trade-off relationship between BER performance and computational complexity. A stage reduction algorithm and each detection algorithm are presented in a row and compared in terms of BER performance and computational complexity by numerical results and experimentations. In the process of experimentations, the cross points of conventional QRM-ML detection algorithm and modified QRM-ML detection algorithm in BER performance graphs are also analyzed in diverse situations and compared in terms of efficiency of proposed algorithm according to the number of antennas and modulation order.

KEYWORDS

Multiple-input-multiple-output (MIMO), Maximum Likelihood, QRM-ML detection, Complexity Reductions

Citation status

* References for papers published after 2023 are currently being built.

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Journal of Knowledge Information Technology and Systems 2023 KCI Impact Factor : 0.89