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Main Authors: Gengtian, Shi, Koshimizu, Takashi, Saito, Megumi, Zhenni, Pan, Jiang, Liu, Shimamoto, Shigeru
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2511.00767
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author Gengtian, Shi
Koshimizu, Takashi
Saito, Megumi
Zhenni, Pan
Jiang, Liu
Shimamoto, Shigeru
author_facet Gengtian, Shi
Koshimizu, Takashi
Saito, Megumi
Zhenni, Pan
Jiang, Liu
Shimamoto, Shigeru
contents In device-to-device (D2D) communication under a cell with resource sharing mode the spectrum resource utilization of the system will be improved. However, if the interference generated by the D2D user is not controlled, the performance of the entire system and the quality of service (QOS) of the cellular user may be degraded. Power control is important because it helps to reduce interference in the system. In this paper, we propose a reinforcement learning algorithm for adaptive power control that helps reduce interference to increase system throughput. Simulation results show the proposed algorithm has better performance than traditional algorithm in LTE (Long Term Evolution).
format Preprint
id arxiv_https___arxiv_org_abs_2511_00767
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Power Control Based on Multi-Agent Deep Q Network for D2D Communication
Gengtian, Shi
Koshimizu, Takashi
Saito, Megumi
Zhenni, Pan
Jiang, Liu
Shimamoto, Shigeru
Networking and Internet Architecture
In device-to-device (D2D) communication under a cell with resource sharing mode the spectrum resource utilization of the system will be improved. However, if the interference generated by the D2D user is not controlled, the performance of the entire system and the quality of service (QOS) of the cellular user may be degraded. Power control is important because it helps to reduce interference in the system. In this paper, we propose a reinforcement learning algorithm for adaptive power control that helps reduce interference to increase system throughput. Simulation results show the proposed algorithm has better performance than traditional algorithm in LTE (Long Term Evolution).
title Power Control Based on Multi-Agent Deep Q Network for D2D Communication
topic Networking and Internet Architecture
url https://arxiv.org/abs/2511.00767