NDLI: A reduced-complexity sphere decoding algorithm for MIMO systems

Content Provider	IEEE Xplore Digital Library
Author	Ying-Jun Ni Ming-Qi Li Wen-Qiang Guo
Copyright Year	2010
Description	Author affiliation: School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu 611731, China (Ying-Jun Ni; Ming-Qi Li) \|\| School of Computer Science and Engineering, Xinjiang University of Finance & Economics, Urumqi 830012, China (Wen-Qiang Guo)
Abstract	Sphere decoding (SD), as an algorithm searching for the closest lattice point within a certain search radius, is a corrected maximum likelihood (ML) algorithm for multiple- input multiple-output (MIMO) systems, with low complexity. The sphere radius and the number of search floating points visited throughout the tree traversal searching are the decisive factors for the complexity of the algorithm. In this paper, a new reduce-complexity detection algorithm based on the complex SD for MIMO systems is presented. The algorithm performs a fixed number of total search floating points to detect the p-QAM modulation symbols independently on the noise level. Simulation results show that with 4×4 system via 4-QAM and 16-QAM, the new SD algorithm has a lower complexity than the conventional SD at low signal-noise ratio (SNR) especially.
Starting Page	431
Ending Page	435
File Size	370224
Page Count	5
File Format	PDF
ISBN	9781424480258
e-ISBN	9781424480265
DOI	10.1109/ICACIA.2010.5709935
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	MIMO systems sphere decoding Signal processing algorithms Lattices ML decoding MIMO Complexity theory p-QAM modulation Maximum likelihood decoding Noise level computational complexity
Content Type	Text
Resource Type	Article

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