A reduced-complexity MIMO receiver via channel ordering

Boon Sim Thian, Andrea Goldsmith

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

We consider the problem of maximum likelihood (ML) signal detection in multiple-input multiple-output (MIMO) wireless communication systems. We propose a new preprocessing algorithm in the form of channel ordering for sphere decoders. Numerical results show that this new channel ordering leads to significantly lower complexity (in the form of the number of nodes visited by the search algorithm); for MPSK modulation where M ≥ 8 and a moderate SNR range of 15 - 24 dB, our channel ordering results in a two-fold to four-fold decrease in the number of nodes visited by the search algorithm. We also present a brief review of the SDR-ML detector, formulated using semidefinite programming and relaxation techniques. Finally, we propose a combined SDR-ML-sphere decoder and demonstrate that it further reduces the number of nodes visited by the search algorithm; for a 20 x 20 BPSK-modulated MIMO system and SNR of 8 dB, the SDR-ML-sphere decoder has an average complexity that is approximately 5 times less than the sphere decoder.

Original languageEnglish (US)
Title of host publicationGLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference
DOIs
StatePublished - 2009
Externally publishedYes
Event2009 IEEE Global Telecommunications Conference, GLOBECOM 2009 - Honolulu, HI, United States
Duration: Nov 30 2009Dec 4 2009

Publication series

NameGLOBECOM - IEEE Global Telecommunications Conference

Other

Other2009 IEEE Global Telecommunications Conference, GLOBECOM 2009
CountryUnited States
CityHonolulu, HI
Period11/30/0912/4/09

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

Keywords

  • Maximum likelihood
  • Semidefinite programming
  • Sphere decoding

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