Shuffled Decoding of Serial Concatenated Convolutional Codes

被引:0
作者
Bourenane, Aomar [1 ]
Arzel, Matthieu [2 ]
Guilloud, Frederic [2 ]
Thomas, Alain [1 ]
机构
[1] Space & Commun Lab Safran Data Syst, Les Ulis, France
[2] IMT Atlantique, Lab STICC, UMR CNRS 6285, F-29238 Brest, France
来源
2021-11TH INTERNATIONAL SYMPOSIUM ON TOPICS IN CODING (ISTC'21) | 2021年
关键词
Serial Concatenated Convolutional Codes (SCCC); iterative decoding; shuffled decoding; parallel implementations; PERFORMANCE ANALYSIS; TURBO; DESIGN;
D O I
10.1109/ISTC49272.2021.9594068
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Shuffled decoding enables to accelerate the extrinsic information exchange during iterative decoding of concatenated codes. It has already been applied to parallel convolutional codes or low-density parity-check codes. In this article, we propose to apply shuffled decoding to serial concatenation convolutional codes. We take advantage of their systematic encoding to propose an efficient shuffled decoding scheme. Compared to a standard iterative decoding scheme, the convergence of our shuffled implementation is obtained within fewer iterations, each one requiring also less time to be completed. This convergence acceleration yields doubling the throughput. We finally show that doubling the throughput comes at a lower cost than doubling the hardware resources, making this shuffled scheme efficient in term of implementation. For instance, the memory usage is 29% more efficient thanks to our proposal than a baseline scheme, which significantly reduces the power consumption of hardware decoders.
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页数:5
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