人工智能在移动通信中的应用：挑战与实践

doi:10.11959/j.issn.1000-436x.2020167

摘要/Abstract

摘要：

对人工智能在移动通信领域学术界和产业界的研究与应用现状进行了总结，指出了人工智能在提升移动通信系统性能方面的挑战和瓶颈。创造性地提出性能外环与性能内环协同减小实际网络性能与理想网络性能间距离的新思路和新方法：对性能外环部分进行人工智能重构，对性能内环部分进行传统自适应或最优化，形成与性能外环部分的最佳协同。若干成功应用的实例证明了该思路和方法的有效性。最后指出，为了满足移动通信系统对人工智能解决方案“稳”“准”“快”的严苛需求，使能移动网络的自动化、智能化、智慧化，除了使人工智能重构的方案本身具有优异的性能外，还必须有基于大数据分析和模拟系统的反馈闭环系统架构，而架构中模拟器的构建——模拟系统是实现“稳”“准”“快”严苛需求的关键路径。

关键词: 移动通信, 人工智能, 机器学习, 网络性能

Abstract:

The research and application progress in mobile communication,and points out its obstacle for improving the performance of mobile communication system were summarized.A new approach for reducing the gap between the practical and the ideal network performance was put forward creatively,which included the artificial intelligence reconstruction for performance outer loop part,the traditional adaptation or optimization for performance inner loop part,and the optimal cooperation between the two parts.The effectiveness of this approach was proved by the several successful applications.Finally,it pointed out that in order to meet the severe demands of mobile communication system for the “stable” “accurate” and “fast” artificial intelligence solution,and make the mobile network automatic,intelligent and wise,in addition to the excellent performance of the artificial intelligence reconstruction scheme itself,there must also be a feedback closed-loop system architecture based on the big data analysis and analog system,which is the key path to achieve this target.

Key words: mobile communication, artificial intelligence, machine learning, network performance

中图分类号:

TN929.5

伏玉笋,杨根科. 人工智能在移动通信中的应用：挑战与实践[J]. 通信学报, 2020, 41(9): 190-201.

Yusun FU,Genke YANG. Application of artificial intelligence in mobile communication:challenge and practice[J]. Journal on Communications, 2020, 41(9): 190-201.

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维度	性能内环	性能外环
信息特征	无记忆	有记忆
处理粒度	小尺度（TTI+ 级）	大尺度（话统+ 级）
数据特征	时间序列特征	统计特征
处理对象	一般用户级	一般小区级或者簇级
结果	感知用户，无法感知网络	感知网络，无法感知用户
示例：链路自适应	基于ACK/NACK反馈的链路自适应	链路自适应的初始值