Integrated Sensing and Communication (ISAC) systems have garnered significant attention due to their capability to simultaneously achieve efficient communication and environmental sensing. A core objective in this field is characterizing the performance tradeoff between sensing and communication. In this paper, we consider a joint source-channel coding (JSCC) framework for the ISAC system that consists of a transmitter with a channel state estimator and a joint source-channel encoder, a state-dependent memoryless channel, and a receiver with a joint source-channel decoder. From an information-theoretic perspective, we establish the tradeoff relationships among channel capacity, distortions in both communication and sensing processes, and the estimation cost. We prove that the separate source and channel coding can achieve joint optimality in this setting. An illustrative example of a binary setting is also provided to validate our theoretical results.

翻译：集成感知与通信（ISAC）系统因其能够同时实现高效通信与环境感知的能力而受到广泛关注。该领域的一个核心目标是刻画感知与通信之间的性能权衡关系。本文针对ISAC系统提出一种联合信源信道编码（JSCC）框架，该框架包含一个配备信道状态估计器与联合信源信道编码器的发射机、一个状态相关的无记忆信道，以及一个配备联合信源信道解码器的接收机。从信息论视角出发，我们建立了信道容量、通信与感知过程中的失真以及估计代价之间的权衡关系。我们证明了在此设定下，分离的信源与信道编码能够实现联合最优性。文中还提供了一个二进制场景的示例以验证我们的理论结果。