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Deterministic-Random Tradeoff of Integrated Sensing and Communications in Gaussian Channels: A Rate-Distortion Perspective

Fan LiuYifeng XiongKai Wan
Dec 2022
摘要
Integrated sensing and communications (ISAC) is recognized as a key enablingtechnology for future wireless networks. To shed light on the fundamentalperformance limits of ISAC systems, this paper studies the deterministic-randomtradeoff between sensing and communications (S\&C) from a rate-distortionperspective under Gaussian ISAC channels. We model the ISAC signal as a randommatrix that carries information, whose realization is perfectly known to thesensing receiver, but is unknown to the communication receiver. We characterizethe sensing mutual information conditioned on the random ISAC signal, and showthat it provides a universal lower bound for distortion metrics of sensing.Furthermore, we prove that the distortion lower bound is minimized if thesample covariance matrix of the ISAC signal is deterministic. We then offer ourunderstanding of the main results by interpreting wireless sensing asnon-cooperative source-channel coding. Finally, we provide sufficientconditions for the achievability of the distortion lower bound by analyzing aspecific example of target response matrix estimation.
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