Integrated Sensing and Communication Exploiting Prior Information: How Many Sensing Beams are Needed?
Chan Xu, Shuowen Zhang

TL;DR
This paper investigates the optimal number of sensing beams in an integrated sensing and communication system, deriving bounds and optimizing beamforming to balance sensing accuracy and communication quality.
Contribution
It introduces a periodic PCRB for better error quantification and proves that at most one dedicated sensing beam is necessary for optimal performance.
Findings
Derives a more accurate periodic PCRB for angle estimation.
Formulates and solves a non-convex beamforming optimization problem.
Proves that only one sensing beam is needed for optimal sensing performance.
Abstract
This paper studies an integrated sensing and communication (ISAC) system where a multi-antenna base station (BS) aims to communicate with a single-antenna user in the downlink and sense the unknown and random angle parameter of a target via exploiting its prior distribution information. We consider a general transmit beamforming structure where the BS sends one communication beam and potentially one or multiple dedicated sensing beam(s). Firstly, motivated by the periodic feature of the angle parameter, we derive the periodic posterior Cram\'{e}r-Rao bound (PCRB) for quantifying a lower bound of the mean-cyclic error (MCE), which is more accurate than the conventional PCRB for bounding the mean-squared error (MSE). Then, note that more sensing beams enable higher flexibility in enhancing the sensing performance, while also generating extra interference to the communication user. To…
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Taxonomy
TopicsDistributed Sensor Networks and Detection Algorithms · Target Tracking and Data Fusion in Sensor Networks
