An efficient soft MIMO detection based on differential METRICS

Wang Yueh Chang, Ming-Xian Chang

Research output: Contribution to journalArticle

Abstract

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
Volume25
Issue number4
DOIs
Publication statusPublished - 2018 Aug 1

Fingerprint

Decoding
Throughput
Decomposition
Hardware
Communication

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

Cite this

@article{e17a118258f141499f1c21d9264d67c5,
title = "An efficient soft MIMO detection based on differential METRICS",
abstract = "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.",
author = "Chang, {Wang Yueh} and Ming-Xian Chang",
year = "2018",
month = "8",
day = "1",
doi = "10.6329/CIEE.201806-25(4).0001",
language = "English",
volume = "25",
pages = "127--133",
journal = "International Journal of Electrical Engineering",
issn = "1812-3031",
publisher = "Chinese Institute of Electrical Engineering",
number = "4",

}

An efficient soft MIMO detection based on differential METRICS. / Chang, Wang Yueh; Chang, Ming-Xian.

In: International Journal of Electrical Engineering, Vol. 25, No. 4, 01.08.2018, p. 127-133.

Research output: Contribution to journalArticle

TY - JOUR

T1 - An efficient soft MIMO detection based on differential METRICS

AU - Chang, Wang Yueh

AU - Chang, Ming-Xian

PY - 2018/8/1

Y1 - 2018/8/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85052137144&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85052137144&partnerID=8YFLogxK

U2 - 10.6329/CIEE.201806-25(4).0001

DO - 10.6329/CIEE.201806-25(4).0001

M3 - Article

AN - SCOPUS:85052137144

VL - 25

SP - 127

EP - 133

JO - International Journal of Electrical Engineering

JF - International Journal of Electrical Engineering

SN - 1812-3031

IS - 4

ER -