DocumentCode
2656098
Title
A Unified Approach for Weighted Viterbi Decoding in MIMO-OFDM Precoding Systems
Author
Zhou, Liang ; Takano, Takeshi
Author_Institution
YRP R&D Center, Fujitsu Labs. Ltd., Kanagawa
fYear
2007
fDate
22-25 April 2007
Firstpage
2078
Lastpage
2082
Abstract
In this paper, a unified approach for weighted Viterbi decoding is proposed to improve error rate performance in multiple-input multiple-output (MIMO) and orthogonal frequency division multiplexing (OFDM) systems with linear precoding. The MIMO-OFDM systems with limited feedback precoding, optimal linear precoding (eigenmode), and spatial multiplexing are considered as a unified framework. In the proposed method, the branch metric is weighted by using the signal to interference noise ratio (SINR) of the effective channel in soft decision Viterbi decoding. The proposed scheme can mitigate noise enhancement for the coherent zero-forcing (ZF) or minimum mean square error (MMSE) decoder in these coded systems. Two low complexity linear decoders based on ZF and MMSE are compared. Extensive simulations show that the proposed unified approach with low complexity exhibit excellent performance.
Keywords
MIMO communication; OFDM modulation; Viterbi decoding; least mean squares methods; linear codes; precoding; MIMO-OFDM precoding systems; MMSE decoder; SINR; coherent zero-forcing; feedback precoding; linear decoders; minimum mean square error decoder; multiple-input multiple-output systems; optimal linear precoding; orthogonal frequency division multiplexing; signal to interference noise ratio; soft decision Viterbi decoding; spatial multiplexing; weighted Viterbi decoding; Decoding; Error analysis; Feedback; MIMO; Matrix decomposition; Mean square error methods; OFDM; Signal to noise ratio; Transmitters; Viterbi algorithm;
fLanguage
English
Publisher
ieee
Conference_Titel
Vehicular Technology Conference, 2007. VTC2007-Spring. IEEE 65th
Conference_Location
Dublin
ISSN
1550-2252
Print_ISBN
1-4244-0266-2
Type
conf
DOI
10.1109/VETECS.2007.430
Filename
4212858
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