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A High-Performance Stochastic LDPC Decoder Architecture Designed via Correlation Analysis

delete2020-12-01
delete7
PRE
AI
Q
Qichen Zhang
Y
Yun Chen *
S
Shixian Li
X
Xiaoyang Zeng
K
Keshab K. Parhi
DOI:10.1109/TCSI.2020.3003457delete
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摘要

摘要

En 中文
This paper presents an area-efficient architecture for stochastic low-density parity-check (LDPC) decoder with high throughput and excellent bit-error-rate (BER) performance. The correlation effects of a stochastic Sum-Product Algorithm (SPA) are analyzed. Based on this analysis, a variable node (VN) structure is proposed and its similarity with a correlation divider (CORDIV) is pointed out. Based on the properties of CORDIV, the area of probability tracer in the VN is reduced significantly. In order to achieve more accurate results when the check-to-variable (C2V) messages are not strong enough, the 3-3 input grouping sub-node is replaced by an adder-based 5-1 input grouping sub-node of the degree-6 VN for (2048,1723) code. An unbiased stochastic sequence generator is adopted to get more accurate results from the smaller probability tracer. Furthermore, the soft bit-flipping prior-processing and the C2V-based hard decision updating method are combined in VN to reduce the decoding latency. A (2048,1723) stochastic LDPC decoder is designed in the TSMC 65 nm process to demonstrate the proposed decoder architecture. With the aid of early termination, the decoder occupies 2.34 mm(2) core area and can achieve 116.17 Gb/s at 4.4 dB and 461.99 Gb/s at 5.5 dB under 970 MHz with better decoding performance. Compared with the state-of-the-art stochastic IEEE 802.3an LDPC decoders, the proposed architecture can achieve the best throughput, throughput-to-area ratio, and BER performance.
Keyword:
Decoding
Parity check codes
Correlation
Throughput
Computer architecture
Stochastic processes
Logic gates
Low-density parity-check
stochastic decoder
variable node
correlation
IEEE 802
3an

期刊

IEEE Transactions on Circuits and Systems I-Regular Papers 封面图
IEEE Transactions on Circuits and Systems I-Regular Papers
IF:
5.2
论文数:
9.7K
被引数:
2.2W

机构

F
fudan university
学者数:
11.7W
论文数: 7.7W
被引数: 121