论文标题
在高斯渠道中集成感测和通信的确定性随机权衡：利率延伸的观点
Deterministic-Random Tradeoff of Integrated Sensing and Communications in Gaussian Channels: A Rate-Distortion Perspective
论文作者
论文摘要
集成传感和通信（ISAC）被公认为是未来无线网络的关键启用技术。为了阐明ISAC系统的基本绩效限制，本文从矢量高斯渠道下的速率延伸角度研究了传感与通信（S＆C）之间的确定性随机权衡。我们将ISAC信号建模为带有信息的随机矩阵，其实现是传感接收器完全知道的，但通信接收器未知。我们表征了以随机ISAC信号为条件的传感相互信息，并表明它为传感的失真指标提供了通用下限。此外，我们证明，如果ISAC信号的样品协方差矩阵是确定性的，那么下限的失真下限将最小化。然后，我们通过将无线传感解释为非合作源通道编码来提供对主要结果的理解，并揭示ISAC系统S＆C的确定性随机权衡。最后，通过分析目标响应矩阵估计的特定示例，我们为失真的实现提供了足够的条件。
Integrated sensing and communications (ISAC) is recognized as a key enabling technology for future wireless networks. To shed light on the fundamental performance limits of ISAC systems, this paper studies the deterministic-random tradeoff between sensing and communications (S&C) from a rate-distortion perspective under vector Gaussian channels. We model the ISAC signal as a random matrix that carries information, whose realization is perfectly known to the sensing receiver, but is unknown to the communication receiver. We characterize the sensing mutual information conditioned on the random ISAC signal, and show that it provides a universal lower bound for distortion metrics of sensing. Furthermore, we prove that the distortion lower bound is minimized if the sample covariance matrix of the ISAC signal is deterministic. We then offer our understanding of the main results by interpreting wireless sensing as non-cooperative source-channel coding, and reveal the deterministic-random tradeoff of S&C for ISAC systems. Finally, we provide sufficient conditions for the achievability of the distortion bound by analyzing a specific example of target response matrix estimation.
