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Related Experiment Video

Updated: Jan 11, 2026

Author Spotlight: Introduction to Active Probe Atomic Force Microscopy with Quattro-Parallel Cantilever Arrays

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Published on: June 13, 2023

Hierarchical Beamforming Optimization for ISAC-Enabled RSU Systems in Complex Urban Environments.

Zhiyuan You¹, Na Lv², Guimei Zheng³

¹The Graduate School, Air Force Engineering University, Xi'an 710038, China.

Sensors (Basel, Switzerland)

|November 13, 2025

Summary

This study introduces a hierarchical beamforming method for Integrated Sensing and Communication (ISAC) systems to balance sensing accuracy and communication reliability. The novel approach optimizes both sensing and communication performance in complex urban environments.

Keywords:

beamforming hierarchical optimization integrated sensing and communications multi-user interference semidefinite program

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Last Updated: Jan 11, 2026

Author Spotlight: Introduction to Active Probe Atomic Force Microscopy with Quattro-Parallel Cantilever Arrays

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Characterization of SiN Integrated Optical Phased Arrays on a Wafer-Scale Test Station

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Published on: April 1, 2020

Area of Science:

Electrical Engineering
Computer Science
Signal Processing

Background:

Integrated Sensing and Communication (ISAC) systems face performance trade-offs between sensing and communication in urban settings.
Conventional optimization methods struggle with local optima and sub-optimal results for joint sensing-communication problems.
Existing solutions often fail to effectively balance conflicting objectives in ISAC.

Purpose of the Study:

To propose a novel hierarchical beamforming optimization solution for ISAC-enabled Roadside Units (RSUs).
To address the performance trade-offs between target sensing and multi-user communication in complex urban environments.
To jointly optimize communication SINR and sensing SCNR for enhanced accuracy and reliability.

Main Methods:

Decomposed the joint sensing-communication problem into a two-level "leader-follower" hierarchical structure.
Employed a max-min strategy with the bisection method in the leader layer to solve communication beamforming.
Utilized Semi-Definite Programming (SDP) in the follower layer to maximize sensing SCNR, incorporating spatiotemporal resource isolation.

Main Results:

The hierarchical optimization effectively balances communication SINR and sensing SCNR.
The proposed method demonstrates simultaneous improvement in sensing accuracy and communication reliability.
Simulation results validate the effectiveness of the joint optimization strategy.

Conclusions:

The hierarchical beamforming approach offers a viable solution for ISAC systems in urban environments.
This method effectively mitigates the inherent trade-offs between sensing and communication performance.
The proposed technique enhances both the sensing capabilities and communication reliability of ISAC-enabled RSUs.