Resource Allocation for Semantic Relay Aided Wireless Networks with Probability Graph

Jiahui Zhao1; Ming Chen1; Zhaohui Yang2,3; Changsheng You4; Mingzhe Chen5

10.1109/ICC51166.2024.10622653

2024-06-13

1550-3607

978-1-7281-9055-6

ICC 2024 - IEEE International Conference on Communications

9-13 June 2024

Denver, CO, USA

In this paper, we introduce a novel uplink semantic relay (SemRelay)-aided wireless communication system, catering to multiple users by leveraging a shared probability graph between the SemRelay and the base station (BS). In this system, users transmit text information to the SemRelay through conventional bit transmission, and the SemRelay compresses this information using a knowledge based characterized by probability graph before transmitting it to the BS through semantic communication. Then, the BS recovers the information based on the shared probability graph. While the semantic information compression incurs computational resource consumption, it significantly reduces communication resource usage. This paper addresses the challenge of minimizing overall system latency through jointly optimizing communication and computation re-source allocation, considering limited wireless resources and the system's energy budget. To address this problem, we introduce an efficient iterative algorithm, which employs block coordinate descent for communication resource allocation and exhaustive searching for determining the optimal data compression scheme. In particular, both power allocation subproblem and bandwidth allocation subproblem are proved to be convex. The complexity analysis of the proposed algorithm are also provided. Numerical results validate the effectiveness of the proposed algorithm and the superior performance of semantic communication compared to the conventional bit transmission.

其他

1.National Mobile Communications Research Laboratory, Southeast University, Nanjing, China
2.College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, China
3.Zhejiang Provincial Key Laboratory of Info. Proc., Commun. & Netw. (IPCAN), Hangzhou, China
4.Department of Electronic and Electrical Engineering, Southern University of Science and Technology, Shenzhen, China
5.Department of Electrical and Computer Engineering and Institute for Data Science and Computing, University of Miami, Coral Gables, FL, USA

Jiahui Zhao,Ming Chen,Zhaohui Yang,et al. Resource Allocation for Semantic Relay Aided Wireless Networks with Probability Graph[C],2024.