High-Throughput Software-Defined LDPC Encoder and Decoder With x86-Based Data-Level Parallelism

In order to realize the high-throughput software-defined low-density parity-check (SD-LDPC) encoder and decoder for 5G communication systems, this paper presents various algorithm-software co-optimization techniques allowing advanced data-level parallelism. We first develop efficient mapping schemes...

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Vydáno v:IEEE transactions on vehicular technology Ročník 74; číslo 1; s. 50 - 60
Hlavní autoři: Yun, Sangbu, Choe, Jeongwon, Lee, Youngjoo
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 01.01.2025
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
5G mobile communication
5G new radio
Algorithms
Coders
Coding
Communications systems
Decoding
Encoding
Error correcting codes
Error-correction code
Iterative decoding
LDPC decoding
Optimization
SDR
SIMD
SIMD (computers)
Single instruction multiple data
Software radio
Throughput
Vectors
wireless communication
ISSN:0018-9545, 1939-9359
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Shrnutí:In order to realize the high-throughput software-defined low-density parity-check (SD-LDPC) encoder and decoder for 5G communication systems, this paper presents various algorithm-software co-optimization techniques allowing advanced data-level parallelism. We first develop efficient mapping schemes to describe the contemporary 5G LDPC processing with recent x86 single instruction multiple data (SIMD) instructions. Then, the data rate of 5G SD-LDPC processing is remarkably improved by introducing SIMD-aware algorithm-level innovations, e.g., parallel efficient encoding, minimizing branch instructions, approximate check-node processing, and latency-oriented optimization. Compared with the state-of-the-art approaches, experimental results show that the proposed techniques successfully enhance the speed of encoding and decoding operations by 8.1 and 1.5 times, respectively, leading to the high-speed and fully-flexible software-defined radio (SDR) solutions for 5G systems.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
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ISSN:0018-9545
1939-9359
DOI:10.1109/TVT.2024.3452718