On the Fundamental Limits of Bistatic ISAC Over Vector Channels
Abstract
This paper studies the fundamental limits of bistatic integrated sensing and communications (ISAC) systems over vector channels. We first consider a class of parallel channels in which, on each component channel, the channel from the transmitter (Tx) to the communication receiver (Rx) is degraded with respect to the channel from the Tx to the sensing Rx, or vice versa, where the direction of degradation may vary across component channels. For this class of channels, we establish matching achievability and converse results, which yield a single-letter characterization of the capacity-distortion function C(D). For parallel Gaussian channels with additive Gaussian states, the evaluation of the capacity-distortion-power function C(D,P) under the squared error distortion measure reduces to a joint power and distortion allocation problem across the component channels. We then extend the analysis to general vector channels and derive single-letter lower and upper bounds on C(D). In particular, for vector Gaussian channels with additive Gaussian states, we prove the optimality of Gaussian superposition coding without requiring a global degradation order between the communication and sensing channels, by combining the channel enhancement technique with a matrix extremal inequality based on Fisher information. This leads to an exact characterization of C(D,P).
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BibTeX
@misc{peng2026fundamental,
title = {{On the Fundamental Limits of Bistatic ISAC Over Vector Channels}},
author = {Dongsheng Peng and Lei Yu and Ping Chen and Jun Chen},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.36351},
eprint = {2610.36351},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.36351},
}
RIS
TY - UNPB
TI - On the Fundamental Limits of Bistatic ISAC Over Vector Channels
AU - Dongsheng Peng
AU - Lei Yu
AU - Ping Chen
AU - Jun Chen
PY - 2026
DA - 2026/10/26
PB - arXiv
DO - 10.48550/arxiv.2610.36351
UR - https://arxiv.org/abs/2610.36351
AB - This paper studies the fundamental limits of bistatic integrated sensing and communications (ISAC) systems over vector channels. We first consider a class of parallel channels in which, on each component channel, the channel from the transmitter (Tx) to the communication receiver (Rx) is degraded with respect to the channel from the Tx to the sensing Rx, or vice versa, where the direction of degradation may vary across component channels. For this class of channels, we establish matching achievability and converse results, which yield a single-letter characterization of the capacity-distortion function C(D). For parallel Gaussian channels with additive Gaussian states, the evaluation of the capacity-distortion-power function C(D,P) under the squared error distortion measure reduces to a joint power and distortion allocation problem across the component channels. We then extend the analysis to general vector channels and derive single-letter lower and upper bounds on C(D). In particular, for vector Gaussian channels with additive Gaussian states, we prove the optimality of Gaussian superposition coding without requiring a global degradation order between the communication and sensing channels, by combining the channel enhancement technique with a matrix extremal inequality based on Fisher information. This leads to an exact characterization of C(D,P).
ER -