An efficient soft MIMO detection based on differential METRICS

Wang Yueh Chang, Ming Xian Chang

Research output: Contribution to journalArticlepeer-review


The multiple-input multiple-output (MIMO) technology can make full use of spectrum and increase the communication throughput. In the coded MIMO system, the main challenge of soft detection is to efficiently generate the log-likelihood ratios (LLR) values for channel decoder. The exact maximum a posteriori (MAP) probability detection can guarantee the optimal performance, but its realization is difficult due to its enormous complexity. In this paper, we propose the efficient soft detection algorithms based on differential metrics. We apply the differential metrics for the list sphere decoding, and propose the list gradient algorithm. We further propose a novel algorithm that can generate the values of LLR and provide a trade-off between performance and complexity. The proposed algorithms do not need the QR decomposition and matrix inversion. The proposed algorithms have fixed complexity, and are appropriate for pipelined hardware implementation. The numerical results verify the efficiency of our algorithms.

Original languageEnglish
Pages (from-to)127-133
Number of pages7
JournalInternational Journal of Electrical Engineering
Issue number4
Publication statusPublished - 2018 Aug 1

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering


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