Fast convergence with q-expectation in EM-based blind iterative detection

Wenbin Guo; Shuguang Cui; IEEE

doi:10.1109/ACSSC.2006.354789

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Fast convergence with q-expectation in EM-based blind iterative detection

Wenbin Guo, Shuguang Cui and IEEE

2006 FORTIETH ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS AND COMPUTERS, VOLS 1-5, pp.458-462

Conference Record of the Asilomar Conference on Signals Systems and Computers

01/01/2006

DOI: https://doi.org/10.1109/ACSSC.2006.354789

Abstract

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We develop the q parameterized Expectation Maximization (q-EM) algorithm for parameter estimation based on incomplete observations. The q-EM algorithm is a one-parameter generalization of the standard EM algorithm that has been successfully used in many applications. With q-EM algorithm, we investigate iterative schemes for joint channel estimation and signal detection over frequency selective channels. We show that the convergence speed is improved by replacing the standard expectation with q-expectation, which was first introduced in the Tsallis entropy literature. Simulation results with different q values are given. A variable-q strategy is proposed to further improve the system performance.

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Title: Fast convergence with q-expectation in EM-based blind iterative detection
Creators - without role: Wenbin Guo - University of Arizona
Shuguang Cui - University of Arizona
IEEE
Publication Details: 2006 FORTIETH ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS AND COMPUTERS, VOLS 1-5, pp.458-462
Series: Conference Record of the Asilomar Conference on Signals Systems and Computers
Publisher: IEEE
Number of pages: 2
Identifiers: 9937418808331
Academic Unit: King Abdulaziz University
Language: English
Resource Type: Conference proceeding