  The paper characterizes the fundamental limits of integrated sensing and
communication (ISAC) systems with a bi-static radar, where the radar receiver
is located close to the transmitter and estimates or detects the state based on
the transmitter's channel inputs and the backscattered signals. Two models are
considered. In the first model, the memoryless state sequence is distributed
according to a fixed distribution and the goal of the radar receiver is to
reconstruct this state-sequence with smallest possible distortion. In the
second model, the memoryless state is distributed either according to $P_S$ or
to $Q_S$ and the radar's goal is to detect this underlying distribution so that
the missed-detection error probability has maximum exponential decay-rate
(maximum Stein exponent). Similarly to previous results, our fundamental limits
show that the tradeoff between sensing and communication solely stems from the
empirical statistics of the transmitted codewords which influences both
performances. The main technical contribution are two strong converse proofs
that hold for all probabilities of communication error $\epsilon$ and
excess-distortion probability or false-alarm probability $\delta$ summing to
less than 1, $\epsilon+\delta < 1$. These proofs are based on two parallel
change-of-measure arguments on the sets of typical sequences, one
change-of-measure to obtain the desired bound on the communication rate, and
the second to bound the sensing performance.
