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Blind Joint Maximum Liklihood Channel Estimation and Data Detection for Single-Input Multiple-Output Systems

Chen, S., Yang, X.C. and Hanzo, L. (2005) Blind Joint Maximum Liklihood Channel Estimation and Data Detection for Single-Input Multiple-Output Systems At IEE 3G and Beyond, United Kingdom. 07 - 09 Nov 2005. , pp. 201-205.

Record type: Conference or Workshop Item (Paper)


A blind adaptive scheme is proposed for joint maximum likelihood (ML) channel estimation and data detection of single-input multiple-output (SIMO) systems. The joint ML optimization of the channel and data estimation is decomposed into an iterative optimization loop. An efficient global optimization algorithm termed as the repeated weighted boosting aided search is employed first to identify the unknown SIMO channel model, and then the Viterbi algorithm is used for the maximum likelihood sequence estimation of the unknown data sequence. A simulation example is used for demonstrating the efficiency of this joint ML optimization scheme designed for blind adaptive SIMO systems.

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Published date: 2005
Additional Information: Event Dates: 7-9 November 2005
Venue - Dates: IEE 3G and Beyond, United Kingdom, 2005-11-07 - 2005-11-09
Organisations: Southampton Wireless Group


Local EPrints ID: 261682
PURE UUID: fa4ef108-7642-41b5-9a4a-bfecfc70a71c

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Date deposited: 15 Dec 2005
Last modified: 18 Jul 2017 09:00

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Author: S. Chen
Author: X.C. Yang
Author: L. Hanzo

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