通信学报 ›› 2021, Vol. 42 ›› Issue (12): 134-143.doi: 10.11959/j.issn.1000-436x.2021234

• 学术论文 • 上一篇    下一篇

Cell-Free大规模MIMO系统中基于传输时延的缓存策略研究

王蕊1,2, 申敏1, 何云1, 刘香燕1   

  1. 1 重庆邮电大学通信与信息工程学院,重庆 400065
    2 玉溪师范学院物理与电子工程学院,云南 玉溪 653100
  • 修回日期:2021-10-06 出版日期:2021-12-01 发布日期:2021-12-01
  • 作者简介:王蕊(1988- ),女,云南玉溪人,重庆邮电大学博士生,主要研究方向为Cell-Free大规模MIMO系统的资源分配、动态协作和预编码
    申敏(1963- ),女,贵州湄潭人,重庆邮电大学教授、博士生导师,主要研究方向为通信核心芯片、协议与系统应用技术
    何云(1979- ),女,湖北武汉人,重庆邮电大学博士生,主要研究方向为协作通信、大规模MIMO 系统能效优化
    刘香燕(1992- ),女,四川资阳人,重庆邮电大学博士生,主要研究方向为移动边缘计算、资源分配和D2D通信
  • 基金资助:
    国家科技重大专项基金资助项目(2018ZX03001026-002);云南省地方本科高校(部分)基础研究联合专项资金资助项目(2018FH001-120);重庆邮电大学博士研究生创新人才基金资助项目(BYJS202102)

Research on caching strategy based on transmission delay in Cell-Free massive MIMO systems

Rui WANG1,2, Min SHEN1, Yun HE1, Xiangyan LIU1   

  1. 1 School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
    2 School of Physics and Electronic Engineering, Yuxi Normal University, Yuxi 653100, China
  • Revised:2021-10-06 Online:2021-12-01 Published:2021-12-01
  • Supported by:
    The National Science and Technology Major Project of China(2018ZX03001026-002);The Joint Special Fund Project for Basic Research of Local Undergraduate Universities (part of) in Yunnan Province(2018FH001-120);Chongqing University of Posts and Telecommunications Ph.D.Innovative Talents Project(BYJS202102)

摘要:

为了满足未来移动互联网中用户的超低时延和超高可靠需求,将无线缓存技术与无小区大规模多输入多输出系统相结合,设计了基于AP间协作缓存及区域流行度评估的缓存模型。推导出涉及AP分簇、协作缓存以及区域流行度的传输时延表达式,并将内容放置问题表述为最小化总内容传输时延问题。通过对优化问题的NP-hard 和拟阵约束下次模单调性的证明,提出了基于贪婪算法的缓存部署优化策略。仿真结果表明,所提策略可有效降低系统内容传输时延和提升缓存命中率。

关键词: Cell-Free大规模MIMO系统, 缓存部署, 协作缓存, 内容传输时延

Abstract:

To meet the ultra-low latency and ultra-high reliability requirements of users in the future mobile Internet, the wireless caching technology was combined with Cell-Free massive MIMO systems.The caching model was designed based on AP cooperative caching and regional popularity evaluation.The transmission delay expression involving AP clustering, cooperative caching, and regional popularity was derived, and the content placement problem was expressed as total content transmission delay minimization.Through the demonstration of the NP-hard and submodular monotony of the optimization problem, the greedy algorithm-based optimization strategy was proposed.Simulation results show that the proposed strategy can effectively reduce the content transmission delay and improve the cache hit rate.

Key words: Cell-Free massive MIMO system, caching placement, cooperative caching, content transmission delay

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