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CRC-Aided Sparse Regression Codes for Unsourced Random Access

delete2023-08-01
delete7
PRE
AI
H
Haiwen Cao
J
Jiongyue Xing *
S
Shansuo Liang
DOI:10.1109/LCOMM.2023.3281495delete
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Abstract

Abstract

En 中文
This letter considers a coding scheme for unsourced random access (URA) based on sparse regression codes (SPARCs). In particular, an efficient concatenated coding scheme is proposed, which concatenates SPARCs and cyclic redundancy check-based block Markov superposition transmission (CRC-BMST) codes. A hybrid decoder consisting of a successive cancellation algorithm and a simplified approximated message passing (AMP) algorithm is presented for inner SPARCs, and an improved tree decoder is proposed for outer CRC-BMST codes by introducing a pruning technique. Simulation results show the proposed coding scheme outperforms the coded compressed sensing (CCS) scheme with lower computational complexity.
Keywords:
Unsourced random access
sparse regression codes
CRC codes
block Markov superposition transmission

Journal

IEEE Communications Letters cover
IEEE Communications Letters
IF:
4.4
Papers:
1.3W
Citations:
2.2W

Organization

H
huawei technologies
Scholars:
3.3K
Papers: 2.9K
Citations: 1
C
Chinese University of Hong Kong
Scholars:
3.4W
Papers: 3.2W
Citations: 5.6W