Environment-aware based access point deployment optimization for cell-free massive MIMO system

Jing JIANG; Yongqiang LIU; Fengyang YAN; Sha TAO; Sutthiphan WORAKRIN

doi:10.11959/j.issn.1000-0801.2024022

您当前的位置：

首页 >

文章列表页 >

Environment-aware based access point deployment optimization for cell-free massive MIMO system

Research and Development | 更新时间：2024-06-05

- Environment-aware based access point deployment optimization for cell-free massive MIMO system
- Telecommunications Science Vol. 40, Issue 2, Pages: 11-21(2024)
- 作者机构：
  
  1. 西安邮电大学陕西省信息通信网络及安全重点实验室，陕西西安 710121
  2. 泰国国家电信有限公司，泰国曼谷 10700
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.1000-0801.2024022
  CLC： TN929.5
- Published Online：2024-02，
  
  Published：20 February 2024
- 稿件说明：
移动端阅览
Jing JIANG, Yongqiang LIU, Fengyang YAN, et al. Environment-aware based access point deployment optimization for cell-free massive MIMO system[J]. Telecommunications science, 2024, 40(2): 11-21.
DOI：

Jing JIANG, Yongqiang LIU, Fengyang YAN, et al. Environment-aware based access point deployment optimization for cell-free massive MIMO system[J]. Telecommunications science, 2024, 40(2): 11-21. DOI： 10.11959/j.issn.1000-0801.2024022.

摘要

无蜂窝大规模多输入多输出（MIMO）系统通过在覆盖区域内部署大量的接入点（AP），可以为用户提供均匀、可靠的服务。传统的无蜂窝大规模MIMO系统采用随机部署，未考虑AP周围的路径损耗、阴影衰落散射物以及环境遮挡对覆盖质量的影响。为了考虑实际环境下无蜂窝大规模MIMO能实现均匀、一致的覆盖，提出了基于无线传播环境的AP部署方案。首先，通过混合概率路径损耗模型对无线传播环境进行表征，其次构建了以最大化平均吞吐量为目标的AP部署优化问题，最后将问题转化为马尔可夫博弈过程，并且基于多智能体深度确定性策略梯度（MADDPG）算法得出最优的AP部署策略。仿真结果表明，相比于传统的随机部署和现有AP部署策略，所提方案可明显改善复杂环境下的非均匀覆盖问题，为用户提供良好一致的均匀覆盖。

Abstract

Cell-free massive multiple-input multiple-output (MIMO) systems deploy a large number of access point (AP) across the coverage area which can provide uniform high-rate services to users.However

the quality of coverage would be affected by path loss

shadow fading scatters

and environmental occlusions around the randomly placed AP in conventional cell-free massive MIMO systems that do not consider their impact.Considering the impact of actual wireless propagation environments

an AP deployment scheme was proposed to acquire uniform and consistent coverage.Firstly

a hybrid probabilistic path loss model was utilized to characterize various wireless propagation environments.Then

the AP deployment optimization problem was solved with the objective of maximizing the average throughput.Finally

the problem was transformed into a Markov game process and solved by the multi-agent deep deterministic policy gradient (MADDPG) algorithm.The simulation results demonstrate that the proposed scheme can provide more uniform coverage in complex environments and serve users with reliable and consistent service compared to random AP deployment and existing AP deployment methods.

关键词

Keywords

references

CHEN S F , ZHANG J Y , JIN Y , et al . Wireless powered IoE for 6G:Massive access meets scalable cell-free massive MIMO [J ] . China Communications , 2020 , 17 ( 12 ): 92 - 109 .

NGO H Q , ASHIKHMIN A , YANG H , et al . Cell-free massive MIMO versus small cells [J ] . IEEE Transactions on Wireless Communications , 2017 , 16 ( 3 ): 1834 - 1850 .

NAYEBI E , ASHIKHMIN A , MARZETTA T L , et al . Cell-Free Massive MIMO systems [C ] // Proceedings of the 49th Asilomar Conference on Signals,Systems and Computers . Piscataway:IEEE Press , 2015 : 695 - 699 .

BJÖRNSON E , SANGUINETTI L . Making cell-free massive MIMO competitive with MMSE processing and centralized implementation [J ] . IEEE Transactions on Wireless Communications , 2020 , 19 ( 1 ): 77 - 90 .

ZHENG J K , ZHANG J Y , ZHANG L M , et al . Efficient receiver design for uplink cell-free massive MIMO with hardware impairments [J ] . IEEE Transactions on Vehicular Technology , 2020 , 69 ( 4 ): 4537 - 4541 .

章嘉懿 . 去蜂窝大规模 MIMO 系统研究进展与发展趋势 [J ] . 重庆邮电大学学报(自然科学版) , 2019 , 31 ( 3 ): 285 - 292 .

ZHANG J Y . Overview of cell-free massive MIMO system [J ] . Journal of Chongqing University of Posts and Telecommunications (Natural Science Edition) , 2019 , 31 ( 3 ): 285 - 292 .

REN Z H , DOUFEXI A , BEACH M A . Scalable pilot assignment for user-centric cell-free massive MIMO networks [C ] // Proceedings of IEEE International Conference on Communications . Piscataway:IEEE Press , 2022 : 2555 - 2560 .

CHOI T , KANNO I , ITO M , et al . A realistic path loss model for cell-free massive MIMO in urban environments [C ] // Proceedings of IEEE Global Communications Conference . Piscataway:IEEE Press , 2022 : 2468 - 2473 .

LIU H , ZHANG J Y , JIN S , et al . Graph coloring based pilot assignment for cell-free massive MIMO systems [J ] . IEEE Transactions on Vehicular Technology , 2020 , 69 ( 8 ): 9180 - 9184 .

WANG Z , ZHANG J Y , AI B , et al . Uplink performance of cell-free massive MIMO with multi-antenna users over jointly-correlated Rayleigh fading channels [J ] . IEEE Transactions on Wireless Communications , 2022 , 21 ( 9 ): 7391 - 7406 .

PAPAZAFEIROPOULOS A , KOURTESSIS P , DI RENZO M , et al . Performance analysis of cell-free massive MIMO systems:a stochastic geometry approach [J ] . IEEE Transactions on Vehicular Technology , 2020 , 69 ( 4 ): 3523 - 3537 .

PAPAZAFEIROPOULOS A , NGO H Q , KOURTESSIS P , et al . Optimal energy efficiency in cell-free massive MIMO systems:a stochastic geometry approach [C ] // Proceedings of the 31st Annual International Symposium on Personal,Indoor and Mobile Radio Communications . Piscataway:IEEE Press , 2020 : 1 - 7 .

SHEN K , DE PESSEMIER T , MARTENS L , et al . Genetic algorithm combined with ray tracer for optimizing cell-free mMIMO topology in a confined environment [C ] // Proceedings of the 15th European Conference on Antennas and Propagation (EuCAP) . Piscataway:IEEE Press , 2021 : 1 - 5 .

NAYEBI E , RAO B D . Access point location design in cell-free massive MIMO systems [C ] // Proceedings of the 52nd Asilomar Conference on Signals,Systems,and Computers . Piscataway:IEEE Press , 2018 : 985 - 989 .

JIANG J , YAN F Y , YE Y H , et al . Traffic demand-oriented cell-free massive MIMO network [J ] . IEEE Wireless Communications Letters , 2023 , 12 ( 11 ): 1861 - 1865 .

ZHANG J Y , ZHANG J , BJÖRNSON E , , et al . Local partial zero-forcing combining for cell-free massive MIMO systems [J ] . IEEE Transactions on Communications , 2021 , 69 ( 12 ): 8459 - 8473 .

MUKHERJEE S , CHOPRA R . Performance analysis of cell-free massive MIMO systems in LoS/NLoS channels [J ] . IEEE Transactions on Vehicular Technology , 2022 , 71 ( 6 ): 6410 - 6423 .

LOWE R , WU Y , TAMAR A , et al . Multi-agent actor-critic for mixed cooperative-competitive environments [C ] // Proceedings of the 31st International Conference on Neural Information Processing Systems , 2017 : 6379 - 6390 .

CHERIDITO P , KAWAGUCHI H , MAEJIMA M . Fractinal ornstein-uhlenbeck processes [J ] . Electronic Journal of Probability , 2003 , 8 ( 3 ): 1 - 14 .

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Coordinated air-ground scheduling for UAV-assisted cell-free massive MIMO

Related Author

Danhao DENG

Chaowei WANG

Fan JIANG

Weidong WANG

Related Institution

School of Electronic Engineering, Beijing University of Posts and Telecommunications

School of Communication and Information Engineering, Xi’an University of Posts and Telecommunications

⁰