Joint Channel, Carrier-Frequency-Offset and Noise-Variance Estimation for OFDM Systems Based on Expectation Maximization
Joint Channel, Carrier-Frequency-Offset and Noise-Variance Estimation for OFDM Systems Based on Expectation Maximization
In this paper, a joint channel, carrier-frequency-offset (CFO) and noise-variance estimation scheme is proposed for OFDM systems which is based on Expectation and Maximization (EM) algorithm. The channel parameters are estimated using training sequences incorporated at the beginning of each transmission frame. Based on the assumption that the amplitude and CFO of different paths are independent, the received multipath components may be decomposed into $L$ independent data sets of the $L$ resolvable propagation paths. Hence the associated multi-dimensional minimization problem may be decomposed into separate single-dimensional minimization processes, the maximum likelihood and yet, remains capable of approaching performance at a significantly reduced complexity.
978-1-4244-2518-1
Zhang, Jiankang
6add829f-d955-40ca-8214-27a039defc8a
Mu, Xiaomin
3d578909-36ba-4b16-b703-2ef63532116c
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
16 May 2010
Zhang, Jiankang
6add829f-d955-40ca-8214-27a039defc8a
Mu, Xiaomin
3d578909-36ba-4b16-b703-2ef63532116c
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Zhang, Jiankang, Mu, Xiaomin and Hanzo, Lajos
(2010)
Joint Channel, Carrier-Frequency-Offset and Noise-Variance Estimation for OFDM Systems Based on Expectation Maximization.
2010 IEEE 71st Vehicular Technology Conference (VTC 2010-Spring),.
Record type:
Conference or Workshop Item
(Poster)
Abstract
In this paper, a joint channel, carrier-frequency-offset (CFO) and noise-variance estimation scheme is proposed for OFDM systems which is based on Expectation and Maximization (EM) algorithm. The channel parameters are estimated using training sequences incorporated at the beginning of each transmission frame. Based on the assumption that the amplitude and CFO of different paths are independent, the received multipath components may be decomposed into $L$ independent data sets of the $L$ resolvable propagation paths. Hence the associated multi-dimensional minimization problem may be decomposed into separate single-dimensional minimization processes, the maximum likelihood and yet, remains capable of approaching performance at a significantly reduced complexity.
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VTC_2010_Spring_Jiankang.pdf
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Published date: 16 May 2010
Venue - Dates:
2010 IEEE 71st Vehicular Technology Conference (VTC 2010-Spring),, 2010-05-16
Organisations:
Southampton Wireless Group
Identifiers
Local EPrints ID: 271413
URI: http://eprints.soton.ac.uk/id/eprint/271413
ISBN: 978-1-4244-2518-1
PURE UUID: 3772d98e-a83f-4d46-898f-d2db9fb33623
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Date deposited: 18 Jul 2010 16:11
Last modified: 18 Mar 2024 03:14
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Contributors
Author:
Jiankang Zhang
Author:
Xiaomin Mu
Author:
Lajos Hanzo
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