基于AI和O-RAN架构的5G网络容量自适应算法

移动运营商目前正面临流量爆发式增长和增量不增收的双重困境,需求、投资和效能三者处于不均衡状态。5G的到来为网络能力与用户需求的匹配提供了新的解决方案,O-RAN新架构可以有效引入近年来人工智能领域的各项研究成果,在有限的资源下更好地为用户提供服务。基于AI大数据技术对基站容量空时特征分析形成的精准预测,可以指导网络建设、优化和维护资源的投放、形成容量自适应的弹性网络,使得网络能力和用户需求紧密耦合,达到提高资源配置精准性和提升网络资源利用率的目标。

Traffic adaptive algorithms for 5G networks based on AI and O-RAN architectures

Mobile operators are facing the dual dilemma of explosive traffi c growth and incremental revenue growth.Demand,investment and effi ciency are unbalanced.The arrival of 5G provides a new solution for the matching of network capabilities and user demands.Due to new O-RAN architecture,various research results in the field of artificial intelligence in recent years could be introduced,which provide better services to users with limited resources.Based on AI big data technology,accurate traffic prediction based on spatio-temporal features in cellular networks leading to effi cient resource deployment,which makes network capacity and user demands closely coupled,and improves the accuracy of resource allocation and the utilization of network resources.