A two-phase maximum-likelihood sequence estimation for receivers with partial CSI

Chia Lung Wu, Po-Ning Chen, Mikael Skoglund, Xiao Ming, Shieh Shin-Lin

Research output: Contribution to conferencePaper

1 Scopus citations

Abstract

The optimality of the conventional maximum-likelihood sequence estimation (MLSE), also known as the Viterbi Algorithm (VA), relies on the assumption that the receiver has perfect knowledge of the channel coefficients or channel state information (CSI). However, in practical situations that fail the assumption, the MLSE method becomes suboptimal and then exhaustive checking is the only way to obtain the ML sequence. At this background, considering directly the ML criterion for partial CSI, we propose a two-phase low-complexity MLSE algorithm, in which the first phase performs the conventional MLSE algorithm in order to retain necessary information for the backward VA performed in the second phase. Simulations show that when the training sequence is moderately long in comparison with the entire data block such as 1/3 of the block, the proposed two-phase MLSE can approach the performance of the optimal exhaustive checking. In a normal case, where the training sequence consumes only 0.14 of the bandwidth, our proposed method still outperforms evidently the conventional MLSE.

Original languageEnglish
DOIs
StatePublished - 1 Jan 2013
Event9th International Conference on Information, Communications and Signal Processing, ICICS 2013 - Tainan, Taiwan
Duration: 10 Dec 201313 Dec 2013

Conference

Conference9th International Conference on Information, Communications and Signal Processing, ICICS 2013
CountryTaiwan
CityTainan
Period10/12/1313/12/13

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    Wu, C. L., Chen, P-N., Skoglund, M., Ming, X., & Shin-Lin, S. (2013). A two-phase maximum-likelihood sequence estimation for receivers with partial CSI. Paper presented at 9th International Conference on Information, Communications and Signal Processing, ICICS 2013, Tainan, Taiwan. https://doi.org/10.1109/ICICS.2013.6782818