In this paper, the problem of joint transmission and computation resource allocation for probabilistic semantic communication (PSC) system with rate splitting multiple access (RSMA) is investigated. In the considered model, the base station (BS) needs to transmit a large amount of data to multiple users with RSMA. Due to limited communication resources, the BS is required to utilize semantic communication techniques to compress the large-sized data. The semantic communication is enabled by shared probability graphs between the BS and the users. The probability graph can be used to further compress the transmission data at the BS, while the received compressed semantic information can be recovered through using the same shared probability graph at each user side. The semantic information compression progress consumes additional computation power at the BS, which inevitably decreases the transmission power due to limited total power budget. Considering both the effect of semantic compression ratio and computation power, the semantic rate expression for RSMA is first obtained. Then, based on the obtained rate expression, an optimization problem is formulated with the aim of maximizing the sum of semantic rates of all users under total power, semantic compression ratio, and rate allocation constraints. To tackle this problem, an iterative algorithm is proposed, where the rate allocation and transmit beamforming design subproblem is solved using a successive convex approximation method, and the semantic compression ratio subproblem is addressed using a greedy algorithm. Numerical results validate the effectiveness of the proposed scheme.

翻译：本文研究了基于速率分割多址接入的概率语义通信系统中联合传输与计算资源分配问题。在所考虑模型中，基站需通过RSMA向多用户传输大量数据。受限于通信资源，基站需利用语义通信技术对大规模数据进行压缩。该语义通信通过基站与用户间共享概率图实现：概率图可在基站端进一步压缩传输数据，而各用户端可通过相同的共享概率图恢复接收的压缩语义信息。语义信息压缩过程会消耗基站额外的计算功率，由于总功率预算有限，这不可避免地降低了传输功率。综合考虑语义压缩比与计算功率的影响，首先推导了RSMA的语义速率表达式。基于该表达式，构建了以总功率、语义压缩比及速率分配为约束条件，最大化所有用户语义速率之和的优化问题。为解决该问题，提出了一种迭代算法：其中速率分配与发射波束成形设计子问题采用逐次凸近似方法求解，语义压缩比子问题则通过贪心算法处理。数值结果验证了所提方案的有效性。