Year: 2025
Type: article
Abstract: propose an Integrated Sensing and Communication (ISAC) algorithm that exploits the structure of a hierarchical codebook of beamforming vectors using a best-arm identification Multi-Armed Bandit (MAB) approach for initial alignment and tracking of a Mobile Entity (ME). The algorithm, called Dynamic Beam Zooming (DBZ), performs beam adjustments that mitigate the severe outages associated with wireless mmWave systems and allow for adaptive control of the parameters governing communications. We analyze the sample complexity of DBZ and use it to inform how the algorithm adapts to the non-stationary MAB statistics based on ME motion and Signal-to-Noise Ratio (SNR). We perform extensive simulations to validate the approach and demonstrate that DBZ is competitive against existing Bayesian algorithms, without requiring channel multi-path or fading knowledge. In particular, DBZ outperforms other low-complexity algorithms in the low SNR regime. We also illustrate the efficacy of DBZ in standardized rural and urban scenarios using NYU Sim.
Authors: Nathan Blinn, Matthieu Bloch
Institution: Georgia Institute of Technology
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4409917101