Semantics-Division Duplexing: A Novel Full-Duplex Paradigm

Fuente: arXiv
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Hauptverfasser: Niu, Kai, Liang, Zijian, Dong, Chao, Dai, Jincheng, Si, Zhongwei, Zhang, Ping
Format: Preprint
Veröffentlicht: 2023
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author Niu, Kai
Liang, Zijian
Dong, Chao
Dai, Jincheng
Si, Zhongwei
Zhang, Ping
author_facet Niu, Kai
Liang, Zijian
Dong, Chao
Dai, Jincheng
Si, Zhongwei
Zhang, Ping
contents In-band full-duplex (IBFD) is a theoretically effective solution to increase the overall throughput for the future wireless communications system by enabling transmission and reception over the same time-frequency resources. However, reliable source reconstruction remains a great challenge in the practical IBFD systems due to the non-ideal elimination of the self-interference and the inherent limitations of the separate source and channel coding methods. On the other hand, artificial intelligence-enabled semantic communication can provide a viable direction for the optimization of the IBFD system. This article introduces a novel IBFD paradigm with the guidance of semantic communication called semantics-division duplexing (SDD). It utilizes semantic domain processing to further suppress self-interference, distinguish the expected semantic information, and recover the desired sources. Further integration of the digital and semantic domain processing can be implemented so as to achieve intelligent and concise communications. We present the advantages of the SDD paradigm with theoretical explanations and provide some visualized results to verify its effectiveness.
format Preprint
id arxiv_https___arxiv_org_abs_2312_08862
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Semantics-Division Duplexing: A Novel Full-Duplex Paradigm
Niu, Kai
Liang, Zijian
Dong, Chao
Dai, Jincheng
Si, Zhongwei
Zhang, Ping
Information Theory
Signal Processing
In-band full-duplex (IBFD) is a theoretically effective solution to increase the overall throughput for the future wireless communications system by enabling transmission and reception over the same time-frequency resources. However, reliable source reconstruction remains a great challenge in the practical IBFD systems due to the non-ideal elimination of the self-interference and the inherent limitations of the separate source and channel coding methods. On the other hand, artificial intelligence-enabled semantic communication can provide a viable direction for the optimization of the IBFD system. This article introduces a novel IBFD paradigm with the guidance of semantic communication called semantics-division duplexing (SDD). It utilizes semantic domain processing to further suppress self-interference, distinguish the expected semantic information, and recover the desired sources. Further integration of the digital and semantic domain processing can be implemented so as to achieve intelligent and concise communications. We present the advantages of the SDD paradigm with theoretical explanations and provide some visualized results to verify its effectiveness.
title Semantics-Division Duplexing: A Novel Full-Duplex Paradigm
topic Information Theory
Signal Processing
url https://arxiv.org/abs/2312.08862