NDLI: BEM-based soft-in soft-out detection of DUSTM employing cyclic group codes

Content Provider	IEEE Xplore Digital Library
Author	Zhengfeng Du Jiee Chen Dongfeng Yuan Xiaotian Zhou
Copyright Year	2010
Description	Author affiliation: National Mobile Communications Research Laboratory, Southeast University, Nanjing, China (Jiee Chen) \|\| School of Information Science and Engineering, Shandong University, Jinan, China (Zhengfeng Du; Dongfeng Yuan; Xiaotian Zhou)
Abstract	In this paper, the expectation-maximization (EM) algorithm for maximum a posteriori (MAP) estimation is employed to derive an iterative soft-in soft-out (SISO) detection scheme for differential unitary space-time modulation (DUSTM) system employing cyclic group codes. The data sequence produced by conventional differential detection is differentially recoded and used to estimate the channel state information which acts as the initial value for the Bayesian EM (BEM) algorithm. In each BEM iteration soft decision and more refined channel estimation are successively performed. In the final iteration, The transmitted symbol decisions can be made according to the MAP decision strategy and is differentially decoded to produce the output of the data sequence. Simulation results show the good performance of the proposed scheme compared with the conventional differential unitary space-time demodulation (DUSTD) and hard decision based iterative scheme.
Starting Page	813
Ending Page	817
File Size	160416
Page Count	5
File Format	PDF
ISBN	9781424469420
e-ISBN	9781424469437
DOI	10.1109/ICITIS.2010.5689697
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-12-17
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fading Soft-in soft-out Iterative receiver Unitary space-time codes Expectation maximization algorithm Channel estimation Modulation Receiving antennas Detectors Signal to noise ratio Differential modulation
Content Type	Text
Resource Type	Article

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