The Communication and Computation Trade-off in Wireless Semantic Communications

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Chen, Xuyang, Huang, Chong, Chen, Gaojie, Feng, Daquan, Xiao, Pei
Format: Preprint
Published: 2025
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866909608401960960
author Chen, Xuyang
Huang, Chong
Chen, Gaojie
Feng, Daquan
Xiao, Pei
author_facet Chen, Xuyang
Huang, Chong
Chen, Gaojie
Feng, Daquan
Xiao, Pei
contents Semantic communications have emerged as a crucial research direction for future wireless communication networks. However, as wireless systems become increasingly complex, the demands for computation and communication resources in semantic communications continue to grow rapidly. This paper investigates the trade-off between computation and communication in wireless semantic communications, taking into consideration transmission task delay and performance constraints within the semantic communication framework. We propose a novel tradeoff metric to analyze the balance between computation and communication in semantic transmissions and employ the deep reinforcement learning (DRL) algorithm to minimize this metric, thereby reducing the cost associated with balancing computation and communication. Through simulations, we analyze the tradeoff between computation and communication and demonstrate the effectiveness of optimizing this trade-off metric.
format Preprint
id arxiv_https___arxiv_org_abs_2504_10357
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle The Communication and Computation Trade-off in Wireless Semantic Communications
Chen, Xuyang
Huang, Chong
Chen, Gaojie
Feng, Daquan
Xiao, Pei
Signal Processing
Semantic communications have emerged as a crucial research direction for future wireless communication networks. However, as wireless systems become increasingly complex, the demands for computation and communication resources in semantic communications continue to grow rapidly. This paper investigates the trade-off between computation and communication in wireless semantic communications, taking into consideration transmission task delay and performance constraints within the semantic communication framework. We propose a novel tradeoff metric to analyze the balance between computation and communication in semantic transmissions and employ the deep reinforcement learning (DRL) algorithm to minimize this metric, thereby reducing the cost associated with balancing computation and communication. Through simulations, we analyze the tradeoff between computation and communication and demonstrate the effectiveness of optimizing this trade-off metric.
title The Communication and Computation Trade-off in Wireless Semantic Communications
topic Signal Processing
url https://arxiv.org/abs/2504.10357