Semantic communications (SC) is an emerging communication paradigm in which wireless devices can send only relevant information from a source of data while relying on computing resources to regenerate missing data points. However, the design of a multi-user SC system becomes more challenging because of the computing and communication overhead required for coordination. Existing solutions for learning the semantic language and performing resource allocation often fail to capture the computing and communication tradeoffs involved in multiuser SC. To address this gap, a novel framework for decentralized computing and communication resource allocation in multiuser SC systems is proposed. The challenge of efficiently allocating communication and computing resources (for reasoning) in a decentralized manner to maximize the quality of task experience for the end users is addressed through the application of Stackelberg hyper game theory. Leveraging the concept of second-level hyper games, novel analytical formulations are developed to model misperceptions of the users about each other's communication and control strategies. Further, equilibrium analysis of the learned resource allocation protocols examines the convergence of the computing and communication strategies to a local Stackelberg equilibria, considering misperceptions. Simulation results show that the proposed Stackelberg hyper game results in efficient usage of communication and computing resources while maintaining a high quality of experience for the users compared to state-of-the-art that does not account for the misperceptions.

翻译：语义通信是一种新兴的通信范式，其中无线设备仅发送数据源中的相关信息，同时依赖计算资源来再生缺失的数据点。然而，多用户语义通信系统的设计因协调所需的计算与通信开销而更具挑战性。现有用于学习语义语言和执行资源分配的方案往往未能捕捉多用户语义通信中涉及的计算与通信权衡。为弥补这一不足，本文提出了一种用于多用户语义通信系统中去中心化计算与通信资源分配的新框架。通过应用Stackelberg超博弈理论，解决了以去中心化方式高效分配通信与计算资源（用于推理）以最大化终端用户任务体验质量的挑战。利用二级超博弈的概念，本文建立了新颖的分析模型来刻画用户对彼此通信与控制策略的误判。进一步地，通过对学习到的资源分配协议进行均衡分析，在考虑误判的情况下，考察了计算与通信策略向局部Stackelberg均衡的收敛性。仿真结果表明，与未考虑误判的现有先进方案相比，所提出的Stackelberg超博弈方案能够实现通信与计算资源的高效利用，同时为用户维持较高的体验质量。