NDLI: A novel approach to signal detection in MIMO systems combining coding and joint detection techniques

Content Provider	IEEE Xplore Digital Library
Author	Anxin Li Youzheng Wang Weiyu Xu Zucheng Zhou
Copyright Year	2004
Description	Author affiliation: Dept. of Electron. Eng., Tsinghua Univ., China (Anxin Li; Youzheng Wang; Weiyu Xu; Zucheng Zhou)
Abstract	Multiple-input multiple-output (MIMO) systems have been proposed to attain high capacity or good performance. MIMO systems typically fall into two categories: spatial multiplexing systems (SM-systems) and space-time coding systems (STC-systems). Compared with each other, the SM-systems give the higher data rates while the STC-systems give the better performance. Joint detection (JD) techniques, as one class of multiuser detection, were originally used in CDMA systems to combat multiple-access and intersymbol interference. A novel method of combining coding and JD techniques for signal detection in MIMO systems is proposed. Compared with SM-systems, such as VBLAST, this method can attain better performance. Compared with common STC-systems, this method can achieve the full code rates even for more than two transmit antennas with complex constellations. The performances of the approaches using different JD algorithms are analyzed and compared. Simulation shows that this method performs well.
Sponsorship	Ministry of Educ. (MOE) of PR China City Univ. of Hong Kong K.C. Wong Educ. Found
Starting Page	162
Ending Page	166
File Size	250971
Page Count	5
File Format	PDF
ISBN	0780386477
DOI	10.1109/ICCCAS.2004.1345993
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-06-27
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Multiuser detection Transmitting antennas Diversity reception Receiving antennas Mean square error methods Multiple access interference MIMO Decision feedback equalizers Multiaccess communication Signal detection
Content Type	Text
Resource Type	Article

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