Signal de-multiplexing in branch metric calculation for spatially multiplexed MIMO system

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

3 Citations (Scopus)

Abstract

This paper presents a signal de-multiplexing scheme in branch metric calculation of soft decision decoding for a spatially multiplexed MIMO system. In a conventional MIMO system, de-multiplexing is carried out over the symbols received by multiple antenna elements and is separated from decoding. Therefore, the de-multiplexing requires multiple uncorrelated antenna elements in order to realize a full rank channel matrix. This leads to the limitation of the system capacity by the number of the receive antenna elements. Instead of splitting de-multiplexing and decoding, in this paper, a de-multiplexing scheme at branch metric calculation in soft decision decoding is proposed. Based on ideal interleaving, independence among the coded symbols is assumed. Thus, the full rank channel matrix with the size of minimum free distance can be realized for signal de-multiplexing. As examples of the proposed system, the performance of repetition codes, block codes, and convolutional codes with MMSE de-multiplexing and soft decision Viterbi decoding on a Rayleigh fading channel is investigated. It is shown through numerical analysis that a lower BER can be achieved with a larger minimum free distance for the same normalized transmission rate that is given as the product of the coding rate and the number of multiplexed signal streams.

Original languageEnglish
Title of host publicationIEEE Vehicular Technology Conference
DOIs
Publication statusPublished - 2012
EventIEEE 75th Vehicular Technology Conference, VTC Spring 2012 - Yokohama, Japan
Duration: 2012 May 62012 Jun 9

Other

OtherIEEE 75th Vehicular Technology Conference, VTC Spring 2012
CountryJapan
CityYokohama
Period12/5/612/6/9

Fingerprint

MIMO Systems
Multiplexing
MIMO systems
Branch
Metric
Decoding
Multiple Antennas
Antennas
Convolutional Codes
Convolutional codes
Rayleigh Fading Channel
Block Codes
Interleaving
Block codes
Minimum Mean Square Error
Rayleigh fading
Fading channels
Antenna
Numerical analysis
Numerical Analysis

Keywords

  • Channel Capacity
  • Coding Rate
  • MIMO
  • Minimum Free Distance

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Science Applications
  • Applied Mathematics

Cite this

Signal de-multiplexing in branch metric calculation for spatially multiplexed MIMO system. / Sanada, Yukitoshi.

IEEE Vehicular Technology Conference. 2012. 6239949.

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

Sanada, Y 2012, Signal de-multiplexing in branch metric calculation for spatially multiplexed MIMO system. in IEEE Vehicular Technology Conference., 6239949, IEEE 75th Vehicular Technology Conference, VTC Spring 2012, Yokohama, Japan, 12/5/6. https://doi.org/10.1109/VETECS.2012.6239949
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AB - This paper presents a signal de-multiplexing scheme in branch metric calculation of soft decision decoding for a spatially multiplexed MIMO system. In a conventional MIMO system, de-multiplexing is carried out over the symbols received by multiple antenna elements and is separated from decoding. Therefore, the de-multiplexing requires multiple uncorrelated antenna elements in order to realize a full rank channel matrix. This leads to the limitation of the system capacity by the number of the receive antenna elements. Instead of splitting de-multiplexing and decoding, in this paper, a de-multiplexing scheme at branch metric calculation in soft decision decoding is proposed. Based on ideal interleaving, independence among the coded symbols is assumed. Thus, the full rank channel matrix with the size of minimum free distance can be realized for signal de-multiplexing. As examples of the proposed system, the performance of repetition codes, block codes, and convolutional codes with MMSE de-multiplexing and soft decision Viterbi decoding on a Rayleigh fading channel is investigated. It is shown through numerical analysis that a lower BER can be achieved with a larger minimum free distance for the same normalized transmission rate that is given as the product of the coding rate and the number of multiplexed signal streams.

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