Blind equalization by alternating minimization for applications to mobile communications

Yu Li You, M. Kaveh

Research output: Contribution to conferencePaper

Abstract

Alternating minimization is proposed as a general framework to accomplish joint data estimation and channel identification. Under this framework, a cost function is minimized through alternating two minimization steps which turn out to be data estimation and channel identification, and algorithms derived from this scheme is guaranteed to be convergent. These two minimization steps can be implemented using many previously proposed sequence estimation and channel identification methods (such as the Viterbi and LMS algorithms) as well as many optimization methods. A simple blind equalization algorithm is derived based on the steepest descent method. This algorithm degenerates into a simple sequence estimator if the channel response is known. The computational complexity is at most linear with channel memory, yet simulation shows that the blind algorithm suffers only 3 to 5 dB SNR loss when compared with the Viterbi algorithm with known channel response.

Original languageEnglish (US)
Pages88-92
Number of pages5
StatePublished - Dec 1 1995
EventProceedings of the 1995 IEEE Global Telecommunications Conference. Part 2 (of 3) - Singapore, Singapore
Duration: Nov 14 1995Nov 16 1995

Other

OtherProceedings of the 1995 IEEE Global Telecommunications Conference. Part 2 (of 3)
CitySingapore, Singapore
Period11/14/9511/16/95

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  • Cite this

    You, Y. L., & Kaveh, M. (1995). Blind equalization by alternating minimization for applications to mobile communications. 88-92. Paper presented at Proceedings of the 1995 IEEE Global Telecommunications Conference. Part 2 (of 3), Singapore, Singapore, .