Low complexity soft input decoding in an iterative linear receiver for overloaded MIMO

Satoshi Denno, Tsubasa Inoue, Yuta Kawaguchi, Takuya Fujiwara, Yafei Hou

Research output: Contribution to journalArticlepeer-review

Abstract

This paper proposes a low complexity soft input decoding in an iterative linear receiver for overloaded MIMO. The proposed soft input decoding applies two types of lattice reduction-aided linear filters to estimate log-likelihood ratio (LLR) in order to reduce the computational complexity. A lattice reduction-aided linear with whitening filter is introduced for the LLR estimation in the proposed decoding. The equivalent noise caused by the linear filter is mitigated with the decoder output stream and the LLR is re-estimated after the equivalent noise mitigation. Furthermore, LLR clipping is introduced in the proposed decoding to avoid the performance degradation due to the incorrect LLRs. The performance of the proposed decoding is evaluated by computer simulation. The proposed decoding achieves about 2 dB better BER performance than soft decoding with the exhaustive search algorithm, so called the MLD, at the BER of 10−4, even though the complexity of the proposed decoding is 10 1 as small as that of soft decoding with the exhaustive search.

Original languageEnglish
Pages (from-to)600-608
Number of pages9
JournalIEICE Transactions on Communications
Issue number5
DOIs
Publication statusPublished - May 1 2020

Keywords

  • Iterative decoding
  • Linear detection
  • MIMO
  • Overloaded
  • Soft-input-soft-output (SISO)

ASJC Scopus subject areas

  • Software
  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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