TY - GEN
T1 - An Investigation on Intelligent Relay assisted Semantic Communication Networks
AU - Ma, Shaobo
AU - Liang, Wei
AU - Zhang, Boxuan
AU - Wang, Dawei
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - With the development of sixth generation (6G) networks, semantic communication is treated as an emerging technology to provide more intelligent communication between two parties for enhance the accuracy and efficiency of communications. Whereas, it demands to merge all physical layer blocks in the conventional communications, which heavily deteriorates the spectrum sparsity problem of wireless communication networks. For this sake, we develop a novel intelligent relay assisted semantic communications, by enhancing communication efficiency, which creates a paradigm for text transmission fusion in 6G networks. In this contribution, the semantic communication system we have designed combines traditional deep learning methods with intelligent semantic relays, based on which, the protocols about minimizing the semantic errors by recovering the meaning of sentences for addressing channel variations issues. Meanwhile, our designed system could be applied in the case of wireless channel deterioration or knowledge background mismatch at the transmitter and receiver, and is also a paradigm for future applications in one-to-many and many-to-many semantic communication. At last, we propose a range of research directions and open challenges for boosting the implementations of relay assisted semantic communications.
AB - With the development of sixth generation (6G) networks, semantic communication is treated as an emerging technology to provide more intelligent communication between two parties for enhance the accuracy and efficiency of communications. Whereas, it demands to merge all physical layer blocks in the conventional communications, which heavily deteriorates the spectrum sparsity problem of wireless communication networks. For this sake, we develop a novel intelligent relay assisted semantic communications, by enhancing communication efficiency, which creates a paradigm for text transmission fusion in 6G networks. In this contribution, the semantic communication system we have designed combines traditional deep learning methods with intelligent semantic relays, based on which, the protocols about minimizing the semantic errors by recovering the meaning of sentences for addressing channel variations issues. Meanwhile, our designed system could be applied in the case of wireless channel deterioration or knowledge background mismatch at the transmitter and receiver, and is also a paradigm for future applications in one-to-many and many-to-many semantic communication. At last, we propose a range of research directions and open challenges for boosting the implementations of relay assisted semantic communications.
KW - Amplify and forward
KW - Decode and forward
KW - Deep Learning
KW - Semantic Communications
UR - http://www.scopus.com/inward/record.url?scp=85159788812&partnerID=8YFLogxK
U2 - 10.1109/WCNC55385.2023.10118657
DO - 10.1109/WCNC55385.2023.10118657
M3 - 会议稿件
AN - SCOPUS:85159788812
T3 - IEEE Wireless Communications and Networking Conference, WCNC
BT - 2023 IEEE Wireless Communications and Networking Conference, WCNC 2023 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 IEEE Wireless Communications and Networking Conference, WCNC 2023
Y2 - 26 March 2023 through 29 March 2023
ER -