Fair Resource Allocation With Noise DDPG for UAV Enabled ISAC Systems

ABSTRACT Integrated sensing and communication (ISAC) is considered one of the key technologies for the 6G network. In this letter, we propose a fair resource allocation method for the unmanned aerial vehicle (UAV) enabled communication network, where UAV are equipped with ISAC equipment to serve multiple users and targets. In order to achieve both fair communications and sensing, the resource allocation problem is formulated as maximizing the fairness index under the total power constraint, which is a typical non‐convex optimization problem. Then, we propose the modified noise DDPG method to derive the power allocation. Finally, the simulation results verify the effectiveness of the proposed method compared with the benchmarks.

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Publication Details

Journal
Electronics Letters
Published
2025-01-01
DOI
https://doi.org/10.1049/ell2.70277
Primary Topic
Radar Systems and Signal Processing
Type
article
Field-Weighted Citation Impact
0.00

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article

Fair Resource Allocation With Noise DDPG for UAV Enabled ISAC Systems

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Electronics Letters
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article

Fair Resource Allocation With Noise DDPG for UAV Enabled ISAC Systems

Zhaowei Wang, Jianwei Zhao, Ye Yu, Wei Jin, Weimin Jia
article en

Abstract

ABSTRACT Integrated sensing and communication (ISAC) is considered one of the key technologies for the 6G network. In this letter, we propose a fair resource allocation method for the unmanned aerial vehicle (UAV) enabled communication network, where UAV are equipped with ISAC equipment to serve multiple users and targets. In order to achieve both fair communications and sensing, the resource allocation problem is formulated as maximizing the fairness index under the total power constraint, which is a typical non‐convex optimization problem. Then, we propose the modified noise DDPG method to derive the power allocation. Finally, the simulation results verify the effectiveness of the proposed method compared with the benchmarks.

Electronics LettersVol. 61(1)
PLA Rocket Force University of Engineering (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 82%
Radar Systems and Signal Processing
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