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Rate-MSE Tradeoff in Integrated Sensing and Communication via the Asymptotically Tight Bayesian Cramer-Rao Bound

An exact information-theoretic characterization of the tradeoff between Shannon information rate and mean-squared estimation error in ISAC systems with a fixed random channel state, replacing the loose Bayesian Cramer-Rao bound proxy with the asymptotically tight BCRB and achieving it via constant composition codes with ML/MAP estimation.

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Integrated Communication and Bayesian Estimation of Fixed Channel States Daewon Seo Abstract—This

This work studies an information-theoretic performance limit of an integrated sensing and communication (ISAC) system where the goal of sensing is to estimate a random continuous state. Considering t…