NDLI: Early-Pruned K-Best Sphere Decoding Algorithm Based on Radius Constraints

Content Provider	IEEE Xplore Digital Library
Author	Yi Hsuan Wu Yu Ting Liu Hsiu-Chi Chang Yen-Chin Liao Hsie-Chia Chang
Copyright Year	2008
Description	Author affiliation: Dept. of Electron. Eng., Nat. Chiao Tung Univ., Hsinchu (Yi Hsuan Wu; Yu Ting Liu; Hsiu-Chi Chang; Yen-Chin Liao; Hsie-Chia Chang)
Abstract	A technique to prune the paths for K-best sphere decoding algorithm (SDA) based on radius constraint is presented. The proposed scheme preserves breadth-first searching nature, and the distinct radii for each decoding layer are theoretically derived from the system model with the noise statistics. In addition, based on the data range provided by the radius, a low complexity sorting strategy is proposed. The proposed method can apply to SDA with various path cost functions. Euclidean norm and sum of absolute difference are demonstrated in this paper. With SNR degradation less than 0.2 dB, more than 47% and 90% computation complexity can be reduced in 16-QAM and 64-QAM 4times4 MIMO detection, respectively.
Starting Page	4496
Ending Page	4500
File Size	195834
Page Count	5
File Format	PDF
ISBN	9781424420759
DOI	10.1109/ICC.2008.843
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-05-19
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Maximum likelihood decoding MIMO Sorting Transmitting antennas Degradation Maximum likelihood detection Hardware Signal detection Computational modeling Receiving antennas
Content Type	Text
Resource Type	Article

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