arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2004.06935cs.ITcs.NImath.IT
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蜂窝IoT无线资源控制层智能切片的设计与实现

Intelligent Slicing of Radio Resource Control Layer for Cellular IoT: Design and Implementation

Lian Cao, Rongpeng Li, Jon Crowcroft, Zhifeng Zhao, Honggang Zhang

摘要:

蜂窝物联网(CIoT)已经成为满足物联网设备的各种应用的重要分支。在CIoT内,无线电资源控制(RRC)层负责基本功能,诸如无线电接入网络(RAN)中的连接控制和承载建立。各种物联网场景的出现和多样化的业务需求使得RRC层的RAN切片和智能控制都成为迫切的需求。本文旨在通过设计和实现一种新的架构来增强CIoT RRC层的标准化能力,该架构包含RRC切片和智能控制器。该架构旨在实现RRC层切片的创建、修改和删除功能,同时增加智能控制器,以智能地满足不同物联网设备的多样化和动态的业务需求。在开源软件平台OpenAirInterface(OAI)上进一步实现了所提出的架构,在此基础上验证了RRC切片的有效性,并给出了一个采用强化学习来动态调整其中的非连续接收参数的概念验证案例。仿真结果证明了所提出的智能RRC切片架构的有效性。

英文摘要:

The cellular internet of things (CIoT) has become an important branch to cater various applications of IoT devices. Within CIoT, the radio resource control (RRC) layer is responsible for fundamental functionalities such as connection control and bearer establishment in radio access network (RAN). The emergence of various IoT scenarios and diversified service requirements have made both RAN slicing and intelligent control imperative requirement in RRC layer. This paper focuses on enhancing standardized capabilities of CIoT RRC layer, by designing and implementing a new architecture which accommodate RRC slicing and intelligent controller. The architecture aims to realize functionalities of creating, modifying, and deleting slices in RRC layer, while the intelligent controller is added to satisfy various and dynamic service requirements of different IoT devices smartly. The proposed architecture is further implemented on an open-source software platform OpenAirInterface (OAI), on top of which the effectiveness of RRC slicing is validated and one proof-of-concept case to adopt reinforcement learning to dynamically tune discontinuous reception parameters therein is presented. Simulation results have demonstrated the effectiveness of the proposed intelligent RRC slicing architecture.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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