Low complexity iterative equalization for severe time dispersive MIMO channels

Sajid Ahmed; Tharmalingam Ratnarajah; Mathini Sellathurai; Colin F. N. Cowan

doi:10.1109/ACSSC.2006.355138

Low complexity iterative equalization for severe time dispersive MIMO channels

Sajid Ahmed^*, Tharmalingam Ratnarajah, Mathini Sellathurai, Colin F. N. Cowan

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Citations (Scopus)

Abstract

In this work, reduced complexity minimum mean squared error (MMSE) iterative equalization methods for a multiple-input multiple-output (MIMO) frequency selective channel are proposed. To combat the severe time dispersiveness of the channel OFDM is incorporated. Use of OFDM simplifies the challenging problem of equalization in a MIMO system, due to both inter-symbol-interference (ISI) and co-antenna interference (CAI). The iterative algorithms work in two stages. The first stage estimates the transmitted symbols using a low complexity MMSE equalizer, which accounts for the variance of the already estimated symbols. Then, the second stage finds the a posteriori probabilities of the estimated symbols to find their means and variances to use in the MMSE equalizer in the following iteration. Simulation results show the performance of the proposed iterative algorithm is better than the MMSE equalizer and close to the matched filter bound (MFB) at low computational cost.

Original language	English
Title of host publication	Proceedings of the Fortieth Asilomar Conference on Signals, Systems and Computers 2006
Publisher	IEEE
ISBN (Print)	1424407850, 1424407842
DOIs	https://doi.org/10.1109/ACSSC.2006.355138
Publication status	Published - Oct 2006
Event	40th Asilomar Conference on Signals, Systems, and Computers 2006 - Pacific Grove, United States Duration: 29 Oct 2006 → 1 Nov 2006

Conference

Conference	40th Asilomar Conference on Signals, Systems, and Computers 2006
Abbreviated title	ACSSC '06
Country/Territory	United States
City	Pacific Grove
Period	29/10/06 → 1/11/06

Keywords

Dispersion
MIMO
Equalizers
OFDM
Iterative algorithms
Iterative methods
Intersymbol interference
Computer aided instruction
Computational modeling
Match filters
Low Complexity
Multiple-input
Multiple-output
Multiple-input Multiple-output channel
Dispersive Channel
Time-dispersive Channels
Iterative Algorithm
Minimum Mean Square Error
Multiple-input Multiple-output system
Frequency-selective Channels
variety of conditions
frequency domain
probability density function
fast fourier transform
dimensional matrix
conditional mean
channel model
discrete fourier transform
vector form
modulation scheme
computational complexity of algorithm
binary phase shift keying
single-input single-output
linear time-invariant
iterative estimation
fading channel
high data rate
single-input single out-put systems
data block
error propagation

ASJC Scopus subject areas

Signal Processing
Computer Networks and Communications

Access to Document

10.1109/ACSSC.2006.355138

Cite this

@inproceedings{57213cd4a4b24c9b81c6e42c86e24399,

title = "Low complexity iterative equalization for severe time dispersive MIMO channels",

abstract = "In this work, reduced complexity minimum mean squared error (MMSE) iterative equalization methods for a multiple-input multiple-output (MIMO) frequency selective channel are proposed. To combat the severe time dispersiveness of the channel OFDM is incorporated. Use of OFDM simplifies the challenging problem of equalization in a MIMO system, due to both inter-symbol-interference (ISI) and co-antenna interference (CAI). The iterative algorithms work in two stages. The first stage estimates the transmitted symbols using a low complexity MMSE equalizer, which accounts for the variance of the already estimated symbols. Then, the second stage finds the a posteriori probabilities of the estimated symbols to find their means and variances to use in the MMSE equalizer in the following iteration. Simulation results show the performance of the proposed iterative algorithm is better than the MMSE equalizer and close to the matched filter bound (MFB) at low computational cost.",

keywords = "Dispersion, MIMO, Equalizers, OFDM, Iterative algorithms, Iterative methods, Intersymbol interference, Computer aided instruction, Computational modeling, Match filters, Low Complexity, Multiple-input, Multiple-output, Multiple-input Multiple-output channel, Dispersive Channel, Time-dispersive Channels, Iterative Algorithm, Minimum Mean Square Error, Multiple-input Multiple-output system, Frequency-selective Channels, variety of conditions, frequency domain, probability density function, fast fourier transform, dimensional matrix, conditional mean, channel model, discrete fourier transform, vector form, modulation scheme, computational complexity of algorithm, binary phase shift keying, single-input single-output, linear time-invariant, iterative estimation, fading channel, high data rate, single-input single out-put systems, data block, error propagation",

author = "Sajid Ahmed and Tharmalingam Ratnarajah and Mathini Sellathurai and Cowan, {Colin F. N.}",

year = "2006",

month = oct,

doi = "10.1109/ACSSC.2006.355138",

language = "English",

isbn = "1424407850",

booktitle = "Proceedings of the Fortieth Asilomar Conference on Signals, Systems and Computers 2006",

publisher = "IEEE",

address = "United States",

note = "40th Asilomar Conference on Signals, Systems, and Computers 2006, ACSSC '06 ; Conference date: 29-10-2006 Through 01-11-2006",

}

Ahmed, S, Ratnarajah, T, Sellathurai, M & Cowan, CFN 2006, Low complexity iterative equalization for severe time dispersive MIMO channels. in Proceedings of the Fortieth Asilomar Conference on Signals, Systems and Computers 2006., 4176948, IEEE, 40th Asilomar Conference on Signals, Systems, and Computers 2006, Pacific Grove, California, United States, 29/10/06. https://doi.org/10.1109/ACSSC.2006.355138

TY - GEN

T1 - Low complexity iterative equalization for severe time dispersive MIMO channels

AU - Ahmed, Sajid

AU - Ratnarajah, Tharmalingam

AU - Sellathurai, Mathini

AU - Cowan, Colin F. N.

PY - 2006/10

Y1 - 2006/10

N2 - In this work, reduced complexity minimum mean squared error (MMSE) iterative equalization methods for a multiple-input multiple-output (MIMO) frequency selective channel are proposed. To combat the severe time dispersiveness of the channel OFDM is incorporated. Use of OFDM simplifies the challenging problem of equalization in a MIMO system, due to both inter-symbol-interference (ISI) and co-antenna interference (CAI). The iterative algorithms work in two stages. The first stage estimates the transmitted symbols using a low complexity MMSE equalizer, which accounts for the variance of the already estimated symbols. Then, the second stage finds the a posteriori probabilities of the estimated symbols to find their means and variances to use in the MMSE equalizer in the following iteration. Simulation results show the performance of the proposed iterative algorithm is better than the MMSE equalizer and close to the matched filter bound (MFB) at low computational cost.

AB - In this work, reduced complexity minimum mean squared error (MMSE) iterative equalization methods for a multiple-input multiple-output (MIMO) frequency selective channel are proposed. To combat the severe time dispersiveness of the channel OFDM is incorporated. Use of OFDM simplifies the challenging problem of equalization in a MIMO system, due to both inter-symbol-interference (ISI) and co-antenna interference (CAI). The iterative algorithms work in two stages. The first stage estimates the transmitted symbols using a low complexity MMSE equalizer, which accounts for the variance of the already estimated symbols. Then, the second stage finds the a posteriori probabilities of the estimated symbols to find their means and variances to use in the MMSE equalizer in the following iteration. Simulation results show the performance of the proposed iterative algorithm is better than the MMSE equalizer and close to the matched filter bound (MFB) at low computational cost.

KW - Dispersion

KW - MIMO

KW - Equalizers

KW - OFDM

KW - Iterative algorithms

KW - Iterative methods

KW - Intersymbol interference

KW - Computer aided instruction

KW - Computational modeling

KW - Match filters

KW - Low Complexity

KW - Multiple-input

KW - Multiple-output

KW - Multiple-input Multiple-output channel

KW - Dispersive Channel

KW - Time-dispersive Channels

KW - Iterative Algorithm

KW - Minimum Mean Square Error

KW - Multiple-input Multiple-output system

KW - Frequency-selective Channels

KW - variety of conditions

KW - frequency domain

KW - probability density function

KW - fast fourier transform

KW - dimensional matrix

KW - conditional mean

KW - channel model

KW - discrete fourier transform

KW - vector form

KW - modulation scheme

KW - computational complexity of algorithm

KW - binary phase shift keying

KW - single-input single-output

KW - linear time-invariant

KW - iterative estimation

KW - fading channel

KW - high data rate

KW - single-input single out-put systems

KW - data block

KW - error propagation

UR - http://www.scopus.com/inward/record.url?scp=47049119708&partnerID=8YFLogxK

U2 - 10.1109/ACSSC.2006.355138

DO - 10.1109/ACSSC.2006.355138

M3 - Conference contribution

AN - SCOPUS:47049119708

SN - 1424407850

SN - 1424407842

BT - Proceedings of the Fortieth Asilomar Conference on Signals, Systems and Computers 2006

PB - IEEE

T2 - 40th Asilomar Conference on Signals, Systems, and Computers 2006

Y2 - 29 October 2006 through 1 November 2006

ER -

Low complexity iterative equalization for severe time dispersive MIMO channels

Abstract

Conference

Keywords

ASJC Scopus subject areas

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