  Exploring the mutual benefit and reciprocity of sensing and communication
(S\&C) functions is fundamental to realizing deeper integration for integrated
sensing and communication (ISAC) systems. This paper investigates a novel
communication-assisted sensing (CAS) system within 6G perceptive networks,
where the base station actively senses the targets through device-free wireless
sensing and simultaneously transmits the estimated information to end-users. In
such a CAS system, we first establish an optimal waveform design framework
based on the rate-distortion (RD) and source-channel separation (SCT) theorems.
After analyzing the relationships between the sensing distortion, coding rate,
and communication channel capacity, we propose two distinct waveform design
strategies in the scenario of target impulse response estimation. In the
separated S\&C waveforms scheme, we equivalently transform the original problem
into a power allocation problem and develop a low-complexity one-dimensional
search algorithm, shedding light on a notable power allocation tradeoff between
the S\&C waveform. In the dual-functional waveform scheme, we conceive a
heuristic mutual information optimization algorithm for the general case,
alongside a modified gradient projection algorithm tailored for the scenarios
with independent sensing sub-channels. Additionally, we identify the presence
of both subspace tradeoff and water-filling tradeoff in this scheme. Finally,
we validate the effectiveness of the proposed algorithms through numerical
simulations.
