Dual time scale resource allocation for RAN slicing in software-defined oriented polymorphic IoV

Weijing QI; Qingyang SONG; Lei GUO

doi:10.11959/j.issn.1000-436x.2022067

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Dual time scale resource allocation for RAN slicing in software-defined oriented polymorphic IoV

Topics: Key Technologies of the Polymorphic Network Environment | 更新时间：2024-06-05

- Dual time scale resource allocation for RAN slicing in software-defined oriented polymorphic IoV
- Journal on Communications Vol. 43, Issue 4, Pages: 60-70(2022)
- 作者机构：
  
  重庆邮电大学通信与信息工程学院智能通信与网络安全研究院，重庆 400065
- 作者简介：
- 基金信息：
  
  The National Natural Science Foundation of China(62025105);The Natural Science Foundation of Chongqing(cstc2020jcyj-msxmX0918)
- DOI：10.11959/j.issn.1000-436x.2022067
  CLC： TN92
- Online First：2022-04，
  
  Published：25 April 2022
- 稿件说明：
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Weijing QI, Qingyang SONG, Lei GUO. Dual time scale resource allocation for RAN slicing in software-defined oriented polymorphic IoV[J]. Journal on Communications, 2022, 43(4): 60-70.
DOI：

Weijing QI, Qingyang SONG, Lei GUO. Dual time scale resource allocation for RAN slicing in software-defined oriented polymorphic IoV[J]. Journal on Communications, 2022, 43(4): 60-70. DOI： 10.11959/j.issn.1000-436x.2022067.

摘要

为了有效满足不同车载应用的差异化服务质量需求，针对软件定义多模态车联网提出了一种双时间尺度的无线接入网切片资源分配算法。考虑增强型移动宽带切片用户最小速率约束、车到车链路可靠性约束、节点最大功率约束、RB 约束等，以最小化超可靠低时延切片用户的平均时延为目标，建立缓存、频谱、功率联合资源分配模型。基于匈牙利算法、线性整数规划方法和DDQN算法，将原NP-hard问题在双时间尺度内求解。仿真结果表明，所提算法在保证不同切片用户服务质量需求和提高频谱利用率方面优于传统算法。

Abstract

To effectively meet the differentiated quality of service (QoS) requirements of various vehicular applications

a dual time scale resource allocation algorithm for radio access network (RAN) slicing in software-defined polymorphic Internet of vehicles (IoV) was proposed.Considering the constraints of the minimum rate requirement of enhanced mobile broadband (eMBB) slice users

vehicle-to-vehicle (V2V) link reliability

the maximum power of nodes

the maximum number of RBs

a joint optimization problem of caching

spectrum

power allocation was formulated

with the aim of minimizing the average delay of ultra-reliable and low-latency communication (URLLC) slice users.By using the Hungarian algorithm

linear integer programming method and the double deep Q-Learning network (DDQN) algorithm

the original NP-hard problem was solved in dual time scales.The simulation results show that the proposed algorithm is superior to the traditional algorithm in ensuring the QoS requirements of different slice users and improving the spectrum utilization.

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Keywords

references

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