6G智能业务网络:愿景、架构与关键技术

移动通信业务网络负责基础网络与业务应用之间的适配.5G以前的业务网络是在建好基础网络以后,通过叠加逻辑网络方式构建.6G时代,“场景驱动”将成为移动通信发展的主要演进范式,业务网络的重要性更加突出.6G业务网络应与基础网络同步规划和建设,由6G全场景驱动设计,实现全场景全域按需服务.传统业务网络仅从独立视角设计安全认证、网络控制和能力开放等机制,难以实现细粒度、动态资源管控,无法高效适配6G全场景业务应用.为此,本文基于国家首批6G重点研发计划专项“全场景按需服务关键技术”项目成果与当前学术研究进展,梳理和总结了6G网络按需服务的挑战、6G智能业务网络的愿景和总体架构设计,设计了涵盖资源接入、能力开放与场景解析3个层次以及安全内生、智能内生和协作共享3个关键管控平面的6G智能业务网络,实现对全域资源的细粒度智能管控.最后结合大模型、元宇宙、绿色节能等技术与通信网络深度融合的趋势,展望了6G智能业务网络更加广阔的应用发展空间.

A Caching Scheme for Session Setup in IMS Network

In IP Multimedia Subsystem (IMS), the session setup delay is a critical value for Quality of Service (QoS). The existing approaches to improve this metric depend on optimization of Session Initiation Protocol (SIP) message transmitting and signaling flows. Unfortunately, some service features are missing considered al-though they have been used widely in traditional 2G networks. This paper proposes a novel session setup scheme based on caching, upon the investigation of the performance of IMS session establishment. This mechanism involves cache based local routing policy and an adaptive caching algorithm, which can decrease call setup delay effectively as cached information in the terminating Serving-Call Session Control Function (S-CSCF) hit. The analytical model is deduced, as well as the delay and cost ratio functions are presented based on the model. Moreover, the analytical model is validated through the performance simulation in which the performance of the proposed novel method is evaluated against the basic session setup mechanism in terms of cost and delay.

Network Meets ChatGPT:Intent Autonomous Management,Control and Operation

Telecommunication has undergone significant transformations due to the continuous advancements in internet technology,mobile devices,competitive pricing,and changing customer preferences.Specifically,the most recent iteration of OpenAI’s large language model chat generative pre-trained transformer(ChatGPT)has the potential to propel innovation and bolster operational performance in the telecommunications sector.Nowadays,the exploration of network resource management,control,and operation is still in the initial stage.In this paper,we propose a novel network artificial intelligence architecture named language model for network traffic(NetLM),a large language model based on a transformer designed to understand sequence structures in the network packet data and capture their underlying dynamics.The continual convergence of knowledge space and artificial intelligence(AI)technologies constitutes the core of intelligent network management and control.Multi-modal representation learning is used to unify the multi-modal information of network indicator data,traffic data,and text data into the same feature space.Furthermore,a NetLM-based control policy generation framework is proposed to refine intent incrementally through different abstraction levels.Finally,some potential cases are provided that NetLM can benefit the telecom industry.

Automated Penetration Testing with Fine-Grained Control through Deep Reinforcement Learning

Penetration testing(PT)is an active method of evaluating the security of a network by simulating various types of cyber attacks in order to identify and exploit vulnerabilities.Traditional PT involves a time-consuming and labor-intensive process that is prone to errors and cannot be easily formulated.Researchers have been investigating the potential of deep reinforcement learning(DRL)to develop automated PT(APT)tools.However,using DRL in APT is challenged by partial observability of the environment and the intractability problem of the huge action space.This paper introduces RLAPT,a novel DRL approach that directly overcomes these challenges and enables intelligent automation of the PT process with precise control.The proposed method exhibits superior efficiency,stability,and scalability in finding the optimal attacking policy on the simulated experiment scenario.

Difference-less mobility management network

Core systemtechnology is a key factor in the next generation network(NGN).Adifference-less mobility management network is proposed to better support the mobility of an IP multimedia subsystem(IMS).This kind of network can provide good service and user mobility,enabling local user access to the network anywhere.User location management and session creation are analyzed.The results show that under this network architecture,the cost of the user location registration and session creation is lower than that of the home control model employed by the IMS.