Multi-agent reinforcement learning based dynamic optimization algorithm of CRE offset for heterogeneous networks
To cope with the high throughput demand caused by the proliferation of wireless network users, a multi-agent reinforcement learning based dynamic optimization algorithm of cell range expansion (CRE) offset was proposed for interference scenarios in macro-pico heterogeneous networks.Based on the valu...
Saved in:
Main Authors: | , , , |
---|---|
Format: | Article |
Language: | zho |
Published: |
Editorial Department of Journal on Communications
2023-12-01
|
Series: | Tongxin xuebao |
Subjects: | |
Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2023235/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
_version_ | 1841540015355592704 |
---|---|
author | Cheng ZHANG Jiaye ZHU Zening LIU Yongming HUANG |
author_facet | Cheng ZHANG Jiaye ZHU Zening LIU Yongming HUANG |
author_sort | Cheng ZHANG |
collection | DOAJ |
description | To cope with the high throughput demand caused by the proliferation of wireless network users, a multi-agent reinforcement learning based dynamic optimization algorithm of cell range expansion (CRE) offset was proposed for interference scenarios in macro-pico heterogeneous networks.Based on the value decomposition network framework of collaborative multi-agent reinforcement learning, a personalized online local decision of CRE offset for all pico-base stations was achieved by reasonably utilizing and interacting the intra-system user distribution and their interference levels among pico-base stations.Simulation results show that the proposed algorithm has significant advantages in increasing system throughput, balancing the throughput of each base station and improving edge-user throughput, compared to CRE=5 dB and distributed Q-learning algorithms. |
format | Article |
id | doaj-art-09d0987957c44f829cbb6777ba75e428 |
institution | Kabale University |
issn | 1000-436X |
language | zho |
publishDate | 2023-12-01 |
publisher | Editorial Department of Journal on Communications |
record_format | Article |
series | Tongxin xuebao |
spelling | doaj-art-09d0987957c44f829cbb6777ba75e4282025-01-14T06:22:28ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2023-12-0144869859384534Multi-agent reinforcement learning based dynamic optimization algorithm of CRE offset for heterogeneous networksCheng ZHANGJiaye ZHUZening LIUYongming HUANGTo cope with the high throughput demand caused by the proliferation of wireless network users, a multi-agent reinforcement learning based dynamic optimization algorithm of cell range expansion (CRE) offset was proposed for interference scenarios in macro-pico heterogeneous networks.Based on the value decomposition network framework of collaborative multi-agent reinforcement learning, a personalized online local decision of CRE offset for all pico-base stations was achieved by reasonably utilizing and interacting the intra-system user distribution and their interference levels among pico-base stations.Simulation results show that the proposed algorithm has significant advantages in increasing system throughput, balancing the throughput of each base station and improving edge-user throughput, compared to CRE=5 dB and distributed Q-learning algorithms.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2023235/heterogeneous networkcell range expansionmulti-agent reinforcement learningvalue decomposition network algorithm |
spellingShingle | Cheng ZHANG Jiaye ZHU Zening LIU Yongming HUANG Multi-agent reinforcement learning based dynamic optimization algorithm of CRE offset for heterogeneous networks Tongxin xuebao heterogeneous network cell range expansion multi-agent reinforcement learning value decomposition network algorithm |
title | Multi-agent reinforcement learning based dynamic optimization algorithm of CRE offset for heterogeneous networks |
title_full | Multi-agent reinforcement learning based dynamic optimization algorithm of CRE offset for heterogeneous networks |
title_fullStr | Multi-agent reinforcement learning based dynamic optimization algorithm of CRE offset for heterogeneous networks |
title_full_unstemmed | Multi-agent reinforcement learning based dynamic optimization algorithm of CRE offset for heterogeneous networks |
title_short | Multi-agent reinforcement learning based dynamic optimization algorithm of CRE offset for heterogeneous networks |
title_sort | multi agent reinforcement learning based dynamic optimization algorithm of cre offset for heterogeneous networks |
topic | heterogeneous network cell range expansion multi-agent reinforcement learning value decomposition network algorithm |
url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2023235/ |
work_keys_str_mv | AT chengzhang multiagentreinforcementlearningbaseddynamicoptimizationalgorithmofcreoffsetforheterogeneousnetworks AT jiayezhu multiagentreinforcementlearningbaseddynamicoptimizationalgorithmofcreoffsetforheterogeneousnetworks AT zeningliu multiagentreinforcementlearningbaseddynamicoptimizationalgorithmofcreoffsetforheterogeneousnetworks AT yongminghuang multiagentreinforcementlearningbaseddynamicoptimizationalgorithmofcreoffsetforheterogeneousnetworks |