Joint user association and bandwidth allocation in semantic communication networks

Xia, L. , Sun, Y. , Niyato, D., Li, X. and Imran, M. (2024) Joint user association and bandwidth allocation in semantic communication networks. IEEE Transactions on Vehicular Technology, 73(2), pp. 2699-2711. (doi: 10.1109/TVT.2023.3318510)

Abstract

Semantic communication (SemCom) has recently been considered a promising solution to guarantee high resource utilization and transmission reliability for future wireless networks. Nevertheless, the unique demand for background knowledge matching makes it challenging to achieve efficient wireless resource management for multiple users in SemCom-enabled networks (SC-Nets). To this end, this article investigates SemCom from a networking perspective, where two fundamental problems of user association (UA) and bandwidth allocation (BA) are systematically addressed in the SC-Net. First, considering varying knowledge matching states between mobile users and associated base stations, we identify two general SC-Net scenarios, namely perfect knowledge matching-based SC-Net and imperfect knowledge matching-based SC-Net. Afterward, for each SC-Net scenario, we describe its distinctive semantic channel model from the semantic information theory perspective, whereby a concept of bit-rate-to-message-rate transformation is developed along with a new semantics-level metric, namely system throughput in message (STM), to measure the overall network performance. In this way, we then formulate a joint STM-maximization problem of UA and BA for each SC-Net scenario, followed by a corresponding optimal solution proposed. Numerical results in both scenarios demonstrate significant superiority and reliability of our solutions in the STM performance compared with two benchmarks.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Xia, Le and Imran, Professor Muhammad and Sun, Dr Yao
• Authors: Xia, L., Sun, Y., Niyato, D., Li, X., and Imran, M.
• College/School: College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity
• Journal Name: IEEE Transactions on Vehicular Technology
• Publisher: IEEE
• ISSN: 0018-9545
• ISSN (Online): 1939-9359
• Published Online: 22 September 2023
• Copyright Holders: Copyright © 2023 IEEE
• First Published: First published in IEEE Transactions on Vehicular Technology 73(2):2699 - 2711
• Publisher Policy: Reproduced in accordance with publisher policy