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. In, IEE 3G and Beyond, Savoy Place, London, UK, 07 - 09 Nov 2005. , 201-205.

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Description/Abstract

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.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Event Dates: 7-9 November 2005
Divisions: Faculty of Physical Sciences and Engineering > Electronics and Computer Science > Comms, Signal Processing & Control
ePrint ID: 261682
Date Deposited: 15 Dec 2005
Last Modified: 27 Mar 2014 20:04
Further Information:Google Scholar
URI: http://eprints.soton.ac.uk/id/eprint/261682

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