计算机与现代化 ›› 2021, Vol. 0 ›› Issue (04): 68-73.

• 网络与通信 • 上一篇    下一篇

基于空中智能表面的毫米波通信性能分析

  

  1. (河海大学计算机与信息学院无线通信与智能系统研究所,江苏南京211100)
  • 出版日期:2021-04-22 发布日期:2021-04-25
  • 作者简介:程吟轩(1995—),男,江苏南京人,硕士研究生,研究方向:随机几何,无线通信理论,E-mail: yxcheng@hhu.edu.cn; 周思源(1985—),男,副教授,博士,研究方向:随机几何,无线通信理论,物联网,智能交通,E-mail: syzhou@hhu.edu.cn; 谭国平(1975—),男,教授,博士,研究方向:无线多媒体通信,随机网络优化与控制,E-mail: gptan@hhu.edu.cn。
  • 基金资助:
    国家自然科学基金资助项目(61701168, 61832005, 61571303); 中央高校基本科研业务费专项资金资助项目(2019B15614); 中国博士后科学基金资助项目(2019M651546); 江苏省交通运输科技项目(2018Y45)

Performance Analysis of mmWave Communication via Aerial Large Intelligent Surfaces

  1. (Institute of Wireless Communications and Intelligent Systems, College of Computer and Information, 
    Hohai University, Nanjing 211100, China)
  • Online:2021-04-22 Published:2021-04-25

摘要: 作为一种新型的反射材料,大型智能表面将在下一代通信网络中扮演重要的角色。通过采取将智能反射面部署在无人机上的策略,空中智能表面可以显著提高大型智能表面的网络覆盖率。本文提出一种基于空中智能表面的通信网络模型并且分析毫米波下行通信的双跳传输过程。具体来说,使用泊松点过程来描述在基站周围巡航的空中智能反射面所服务的用户的位置,在此基础上推导出地面用户到空中智能表面距离的概率密度函数,得到系统覆盖率的解析表达式并且通过仿真结果进行验证。结果表明,大型智能表面与无人机的结合可以大大提高城市毫米波通信系统的覆盖性能。本文所提供的网络框架及模型有助于选取正确的网络参数以获得最佳的系统性能。

关键词: 大型智能表面, 无人机, 覆盖率, 城市无线通信

Abstract: As a new type of reflective materials, large intelligent surface (LIS) will play a vital role in the next generation networks. By deploying LISs mounted on unmanned aerial vehicle (UAV), UAV-LIS can be used to further enhance the network coverage of LIS. In this paper, we propose a communication network model based on UAV-LIS and analyze the dual-hop transmission of millimeter wave downlink communication. Specifically, we use Poisson point process to depict the locations of users served by UAV-LIS which cruises around a base station. Then we derive the probability density function of the distance from the ground users to UAV-LIS. The analytical expression of system coverage probability can be obtained and verified by the simulation results. It turns out that the combination of LIS and UAV can greatly improve the coverage performance of millimeter wave communication system in urban areas. The developed framework is insightful for determining the network configuration by which the optimum system performance can be achieved.

Key words: large intelligent surface, unmanned aerial vehicle, coverage probability, urban wireless communication