Beamwidth-Adaptive ISAC Beamforming: A Joint Optimization Framework for Detection and Communication

In this paper, we study a sensing beamwidthadaptive beamforming in an integrated sensing and communication (ISAC) system, aiming to illuminate the communication user to assist in detecting adjacent targets. To this end, we consider the beamwidth variability of sensing beam as a key concept of the beamformer. The ratio of summation of beampattern gain on desired over entire angular coverage, namely effective beampattern gain ratio (EBGR), is adopted as the objective for characterizing the sensing performance. The proposed framework takes the communication signal-to-interference-plus-noise ratio (SINR), the total transmit power limit, and the beampattern matching into account. To address the intrinsic non-convexity introduced by EBGR and SINR, we employ Dinkelbach’s method to convert the objective form, and obtain a high-quality beamforming solution by applying the semidefinite relaxation (SDR)-based approach. A regularized zero-forcing (RZF)-based approach is further proposed aiming to reduce complexity. Numerical results validate the effectiveness of our beamwidth-adaptive design in various scenarios.

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Publication Details

Published
2025-08-10
DOI
https://doi.org/10.1109/iccc65529.2025.11148903
Primary Topic
Radar Systems and Signal Processing
Type
article
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article

Beamwidth-Adaptive ISAC Beamforming: A Joint Optimization Framework for Detection and Communication

Jide Yuan, Yuli Yang, Mohsen Guizani, Zhixiao Fu
Radar Systems and Signal Processing
article

Beamwidth-Adaptive ISAC Beamforming: A Joint Optimization Framework for Detection and Communication

Jide Yuan, Yuli Yang, Mohsen Guizani, Zhixiao Fu
article en

Abstract

In this paper, we study a sensing beamwidthadaptive beamforming in an integrated sensing and communication (ISAC) system, aiming to illuminate the communication user to assist in detecting adjacent targets. To this end, we consider the beamwidth variability of sensing beam as a key concept of the beamformer. The ratio of summation of beampattern gain on desired over entire angular coverage, namely effective beampattern gain ratio (EBGR), is adopted as the objective for characterizing the sensing performance. The proposed framework takes the communication signal-to-interference-plus-noise ratio (SINR), the total transmit power limit, and the beampattern matching into account. To address the intrinsic non-convexity introduced by EBGR and SINR, we employ Dinkelbach’s method to convert the objective form, and obtain a high-quality beamforming solution by applying the semidefinite relaxation (SDR)-based approach. A regularized zero-forcing (RZF)-based approach is further proposed aiming to reduce complexity. Numerical results validate the effectiveness of our beamwidth-adaptive design in various scenarios.

Soochow University (CN), Mohamed bin Zayed University of Artificial Intelligence (AE)
Openalex Percentile: Top 67%
Radar Systems and Signal Processing
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