这份文件提出了一种创新的多用户通信系统，旨在提升无线网络中语义通信（SemCom）的效率。该系统整合了概率知识图（PKG）和速率分割多址（RSMA）技术，以优化信息传输。通过引入语义压缩比（SCR）来连接计算和通信过程，该研究旨在最小化整体系统能耗。文章详细阐述了概率知识图的构建、语义信息的压缩以及下行RSMA语义通信模型的应用。最终，研究提出了一种交替优化算法来解决复杂的非凸优化问题，并通过模拟结果验证了其有效性和优于传统方法的性能。

Rate-Splitting Multiple Access Enabled Green Probabilistic Semantic Communication over Wireless Networks

Abstract:

In this paper, we propose a multi-user green probabilistic semantic communication (PSC) system for semantic communication (SemCom) facilitated by probabilistic knowledge graphs (PKGs), which are knowledge graphs (KGs) integrated with probability to represent semantic information. In the considered model, semantic information of different users is represented by PKGs. On this basis, we design a semantic compression model for multi-user downlink task-oriented SemCom, utilizing the semantic compression ratio (SCR) as a parameter to connect the computation and communication processes of information transmission. Utilizing rate-splitting multiple access (RSMA) technology, the transmitted messages are splitted into shared and private ones. Considering the limited wireless resources and constraint in semantic communication, an optimization problem with the goal of minimizing system energy consumption comprehensively considering the computation and communication process is formulated. In order to address the optimization problem, we propose an alternating optimization algorithm that tackles sub-problems of power allocation and beamforming design with successive convex approximation (SCA) method, semantic compression ratio optimization with variable substitution method, and computation capacity allocation with obtaining closed-form optimal solution. Simulation results verify the effectiveness of the proposed algorithm.

Published in: IEEE Transactions on Green Communications and Networking ( Early Access )

Page(s): 1 - 1

Date of Publication: 13 January 2025

Electronic ISSN: 2473-2400