摘要
随着5G技术的迅速发展,室内分布系统(Indoor Distribution System,IDS)在满足高数据传输需求和提供优质用户体验方面显得尤为重要。然而,由于楼宇环境的复杂性,传统的规划方法难以精确识别弱覆盖区域并进行有效部署。本文提出了一种基于人工智能(AI)的5G室内分布系统规划方法,通过结合大数据分析方法和机器学习技术,更加精准地识别弱覆盖楼宇,评估楼宇价值,并制定优先覆盖策略。相关研究旨在为5G室分网络的规划提供有力支持,提升网络性能和用户体验。
With the rapid development of 5G technology,Indoor Distribution Systems(IDS)have become particularly important in meeting high data transmission demands and providing high-quality user experiences.However,due to the complexity of building environments,traditional planning methods are difficult to accurately identify weak coverage areas and effectively deploy them.This article proposes a 5G indoor distribution system planning method based on artificial intelligence(AI),which combines big data analysis methods and machine learning techniques to more accurately identify weak coverage buildings,evaluate building value,and develop priority coverage strategies.The relevant research aims to provide strong support for the planning of 5G indoor distribution networks,improve network performance and user experience.
作者
孙开宇
王晓楠
SUN Kaiyu;WANG Xiaonan(Liaoning Postal and Telecommunications Planning and Design Institute Co.,Ltd.,Shenyang 110179,China;Software College of Shenyang University of Technology,Shenyang 110000,China)
出处
《数字通信世界》
2025年第2期33-35,共3页
Digital Communication World
关键词
5G
室内分布系统
人工智能
弱覆盖识别
楼宇价值评估
5G
indoor distribution system
artificial intelligence
weak coverage recognition
building calue assessment
作者简介
孙开宇(1985-),男,汉族,辽宁沈阳人,高级工程师,硕士研究生,研究方向为无线通信;王晓楠(1980-),女,汉族,辽宁沈阳人,助理研究员,硕士,研究方向为信息通信。
