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Bibliographic Details
Main Author: Yang, Yifei
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2405.02891
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author Yang, Yifei
author_facet Yang, Yifei
contents Sparse Vector Coding (SVC) has long been considered an encoding method that meets the URLLC QOS requirements. This encoding method has been widely studied and applied due to its low encoding and decoding complexity, no pilot transmission, resistance to inter-carrier interference, and low power consumption. However, due to the use of position indexing, the encoding essentially reduces the signal-to-noise ratio requirements by increasing the communication bandwidth, which also leads to low encoding efficiency and strong rigidity in decoding. Based on the sparse representation characteristics of SVC, we propose a joint sparse representation encoding, namely Sparse Matrix Coding (SMC). This encoding method utilizes multi-user information joint encoding, and the sparsity and sparse locations between users are shared.
format Preprint
id arxiv_https___arxiv_org_abs_2405_02891
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Sparse Matrix Coding for URLLC
Yang, Yifei
Signal Processing
Sparse Vector Coding (SVC) has long been considered an encoding method that meets the URLLC QOS requirements. This encoding method has been widely studied and applied due to its low encoding and decoding complexity, no pilot transmission, resistance to inter-carrier interference, and low power consumption. However, due to the use of position indexing, the encoding essentially reduces the signal-to-noise ratio requirements by increasing the communication bandwidth, which also leads to low encoding efficiency and strong rigidity in decoding. Based on the sparse representation characteristics of SVC, we propose a joint sparse representation encoding, namely Sparse Matrix Coding (SMC). This encoding method utilizes multi-user information joint encoding, and the sparsity and sparse locations between users are shared.
title Sparse Matrix Coding for URLLC
topic Signal Processing
url https://arxiv.org/abs/2405.02891