基于时隙ALOHA与自适应接入类禁止混合的大规模终端接入算法

朱振宇; 朱晓荣; 蔡艳; 朱洪波

doi:10.11959/j.issn.2096-3750.2021.00164

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基于时隙ALOHA与自适应接入类禁止混合的大规模终端接入算法

理论与技术 | 更新时间：2024-06-05

- 基于时隙ALOHA与自适应接入类禁止混合的大规模终端接入算法
- Large-scale terminal access algorithm based on slot ALOHA and adaptive access class barring
- 物联网学报 2021年5卷第1期页码：90-98
- 作者机构：
- 作者简介：
  
  [ "朱振宇（1995- ），男，南京邮电大学硕士生，主要研究方向为物联网大规模终端接入算法" ]
  [ "朱晓荣（1977- ），女，南京邮电大学教授、博士生导师，主要研究方向为下一代无线网络、物联网等" ]
  [ "蔡艳（1974- ），女，南京邮电大学副教授、硕士生导师，主要研究方向为无线通信与电磁兼容、移动通信与宽带无线通信技术等" ]
  [ "朱洪波（1956- ），男，南京邮电大学教授、博士生导师，南京邮电大学原副校长，物联网研究院院长，江苏省“泛在无线通信与物联网”科技创新团队带头人，主要研究方向为物联网、移动通信网络等" ]
- 基金信息：
  
  国家自然科学基金资助项目;The National Natural Science Foundation of China(61871237);江苏省重点研发计划;The Jiangsu Province Key R＆D Plan(BE2019017)
- DOI：10.11959/j.issn.2096-3750.2021.00164
  中图分类号： TN929.5
- 纸质出版日期：2021-03-30，
  
  网络出版日期：2021-03，
- 稿件说明：
移动端阅览
朱振宇, 朱晓荣, 蔡艳, 等. 基于时隙ALOHA与自适应接入类禁止混合的大规模终端接入算法[J]. 物联网学报, 2021,5(1):90-98.

ZHENYU ZHU, XIAORONG ZHU, YAN CAI, et al. Large-scale terminal access algorithm based on slot ALOHA and adaptive access class barring. [J]. Chinese journal on internet of things, 2021, 5(1): 90-98.
朱振宇, 朱晓荣, 蔡艳, 等. 基于时隙ALOHA与自适应接入类禁止混合的大规模终端接入算法[J]. 物联网学报, 2021,5(1):90-98. DOI： 10.11959/j.issn.2096-3750.2021.00164.

ZHENYU ZHU, XIAORONG ZHU, YAN CAI, et al. Large-scale terminal access algorithm based on slot ALOHA and adaptive access class barring. [J]. Chinese journal on internet of things, 2021, 5(1): 90-98. DOI： 10.11959/j.issn.2096-3750.2021.00164.

摘要

为了解决物联网环境中大规模终端接入碰撞率高、时效性低的问题，提出了一种基于时隙ALOHA与自适应接入类禁止（ACB

access class barring）混合的大规模终端接入算法。该算法首先以各终端所处理业务的数据量及对时延的要求对业务进行分类，对于时延不敏感且有效数据部分小于 1 000 bit 的业务，采用基于时隙ALOHA的竞争接入方式；对于时延敏感型业务或者有效数据部分大于1 000 bit的业务，采用基于ACB的随机接入方式。在此基础上，提出了一种基于定量估计的接入申请量预测方法，并依据此预测值动态调整 ACB 控制参数。仿真结果表明，与现有的其他接入算法相比，在保证高优先级业务时延要求的前提下，所提出的算法有效降低了碰撞率，提高了系统接入成功率。

Abstract

In order to solve the problem of high collision rate and low timeliness of large-scale terminals access in the Internet of things

a large-scale terminal access algorithm based on slot ALOHA and adaptive access class barring (ACB) was proposed.Firstly

the services were classified based on the data from each terminal by the volume of the services processed and the requirements for delay.For the services that were not time-sensitive and whose effective data portion was less than 1 000 bit

a slot-based ALOHA-based competitive access method was used.ACB-based random access was used for the services that were time-sensitive or whose data portion was greater than 1 000 bit.On this basis

a method was proposed for predicting the access application volume based on the quantitative estimation

and dynamically adjusting the ACB control parameters based on this predicted value.Simulation results show that compared with other existing access algorithms

the proposed algorithm reduces the collision rate and improves the system access success rate under the premise of ensuring the high priority service delay requirements.

关键词

物联网大规模接入时间序列预测自适应接入类禁止

Keywords

Internet of thingsmassive accesstime series predictionadaptive access class barring

references

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