Sensing-Aided Beamforming: The Impact of Distributed Sensing Network Geometry
As modern wireless systems increasingly focus on high-frequency bands, accurate beamforming has become an essential component for ensuring high-rate data transmission and robust connections. To reduce the overhead and latency caused by beam training, radar sensing can be used to support beamforming by narrowing the search space. Following the concept of Integrated Sensing and Communication (ISAC), we employ a distributed sensing network with multiple bistatic links to localize the target. The estimated target position is then used to assist beamforming. In this paper, we specifically investigates the underlying sensing performance for the given network geometry. Our results show that the spatially inhomogeneous distribution of the Cram'er-Rao Lower Bound (CRLB) can influence the Angle of Departure (AoD) estimation of beamforming, which highlights the importance of beamformer placement in the sensing network. Furthermore, we present a beamforming accuracy map, which can serve as a reference for optimizing placement strategies.