NDLI: Efficient approximate ML decoding units for polar list decoders

Content Provider	IEEE Xplore Digital Library
Author	Chenrong Xiong Jun Lin Zhiyuan Yan
Copyright Year	2015
Description	Author affiliation: Dept. of Electr. & Comput. Eng., Lehigh Univ., Bethlehem, PA, USA (Chenrong Xiong; Jun Lin; Zhiyuan Yan)
Abstract	Polar codes are of great interest since they are the first provably capacity-achieving forward error correction codes. To improve throughput of polar decoders, maximum likelihood (ML) decoding units are used by successive cancellation list (SCL) decoders as well as successive cancellation (SC) decoders. In this paper, an approximate ML (AML) decoding unit with reduced complexity for SCL decoders is proposed. In particular, we investigate the distribution of frozen bits of polar codes designed for the binary erasure channel and additive white Gaussian noise channel, and take advantage of the distribution to reduce the complexity of the AML decoding unit. Simulation and synthesis results show that the proposed AML decoding unit has much lower complexity.
Starting Page	1
Ending Page	6
File Size	1755783
Page Count	6
File Format	PDF
e-ISBN	9781467396042
DOI	10.1109/SiPS.2015.7344981
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-10-14
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Maximum likelihood decoding Probability Throughput AWGN channels Computational complexity ML decoding Error control codes polar codes successive cancellation list decoding
Content Type	Text
Resource Type	Article

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