Energy-Efficient Hybrid Beamfocusing for Near-Field Integrated Sensing and Communication

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Main Authors: Hu, Wenhao, He, Zhenyao, Xu, Wei, Huang, Yongming, Ng, Derrick Wing Kwan, Al-Dhahir, Naofal
Format: Preprint
Published: 2025
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author Hu, Wenhao
He, Zhenyao
Xu, Wei
Huang, Yongming
Ng, Derrick Wing Kwan
Al-Dhahir, Naofal
author_facet Hu, Wenhao
He, Zhenyao
Xu, Wei
Huang, Yongming
Ng, Derrick Wing Kwan
Al-Dhahir, Naofal
contents Integrated sensing and communication (ISAC) is a pivotal component of sixth-generation (6G) wireless networks, leveraging high-frequency bands and massive multiple-input multiple-output (M-MIMO) to deliver both high-capacity communication and high-precision sensing. However, these technological advancements lead to significant near-field effects, while the implementation of M-MIMO \mbox{is associated with considerable} hardware costs and escalated power consumption. In this context, hybrid architecture designs emerge as both hardware-efficient and energy-efficient solutions. Motivated by these considerations, we investigate the design of energy-efficient hybrid beamfocusing for near-field ISAC under two distinct target scenarios, i.e., a point target and an extended target. Specifically, we first derive the closed-form Cramér-Rao bound (CRB) of joint angle-and-distance estimation for the point target and the Bayesian CRB (BCRB) of the target response matrix for the extended target. Building on these derived results, we minimize the CRB/BCRB by optimizing the transmit beamfocusing, while ensuring the energy efficiency (EE) of the system and the quality-of-service (QoS) for communication users. To address the resulting \mbox{nonconvex problems}, we first utilize a penalty-based successive convex approximation technique with a fully-digital beamformer to obtain a suboptimal solution. Then, we propose an efficient alternating \mbox{optimization} algorithm to design the analog-and-digital beamformer. \mbox{Simulation} results indicate that joint distance-and-angle estimation is feasible in the near-field region. However, the adopted hybrid architectures inevitably degrade the accuracy of distance estimation, compared with their fully-digital counterparts. Furthermore, enhancements in system EE would compromise the accuracy of target estimation, unveiling a nontrivial tradeoff.
format Preprint
id arxiv_https___arxiv_org_abs_2508_04627
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Energy-Efficient Hybrid Beamfocusing for Near-Field Integrated Sensing and Communication
Hu, Wenhao
He, Zhenyao
Xu, Wei
Huang, Yongming
Ng, Derrick Wing Kwan
Al-Dhahir, Naofal
Information Theory
Signal Processing
Integrated sensing and communication (ISAC) is a pivotal component of sixth-generation (6G) wireless networks, leveraging high-frequency bands and massive multiple-input multiple-output (M-MIMO) to deliver both high-capacity communication and high-precision sensing. However, these technological advancements lead to significant near-field effects, while the implementation of M-MIMO \mbox{is associated with considerable} hardware costs and escalated power consumption. In this context, hybrid architecture designs emerge as both hardware-efficient and energy-efficient solutions. Motivated by these considerations, we investigate the design of energy-efficient hybrid beamfocusing for near-field ISAC under two distinct target scenarios, i.e., a point target and an extended target. Specifically, we first derive the closed-form Cramér-Rao bound (CRB) of joint angle-and-distance estimation for the point target and the Bayesian CRB (BCRB) of the target response matrix for the extended target. Building on these derived results, we minimize the CRB/BCRB by optimizing the transmit beamfocusing, while ensuring the energy efficiency (EE) of the system and the quality-of-service (QoS) for communication users. To address the resulting \mbox{nonconvex problems}, we first utilize a penalty-based successive convex approximation technique with a fully-digital beamformer to obtain a suboptimal solution. Then, we propose an efficient alternating \mbox{optimization} algorithm to design the analog-and-digital beamformer. \mbox{Simulation} results indicate that joint distance-and-angle estimation is feasible in the near-field region. However, the adopted hybrid architectures inevitably degrade the accuracy of distance estimation, compared with their fully-digital counterparts. Furthermore, enhancements in system EE would compromise the accuracy of target estimation, unveiling a nontrivial tradeoff.
title Energy-Efficient Hybrid Beamfocusing for Near-Field Integrated Sensing and Communication
topic Information Theory
Signal Processing
url https://arxiv.org/abs/2508.04627