工业物联网中URLLC的关键问题分析

doi:10.11959/j.issn.1000-0801.2022110

电信科学 ›› 2022, Vol. 38 ›› Issue (Z1): 77-92.doi: 10.11959/j.issn.1000-0801.2022110

工业物联网中URLLC的关键问题分析

汪晗¹, 刁磊¹, 王梦玲¹, 荣欣¹, 李佳珉¹^,², 尤肖虎¹^,²

¹ 东南大学移动通信国家重点实验室，江苏南京 210096
² 紫金山实验室，江苏南京 211111

修回日期:2022-03-09 出版日期:2022-05-31 发布日期:2022-05-01
作者简介:汪晗（1998- ），女，东南大学信息科学与工程学院硕士生，主要研究方向为高可靠低时延的通信接入
刁磊（1996- ），男，东南大学信息科学与工程学院硕士生，主要研究方向为高可靠低时延通信下的活跃用户检测
王梦玲（1997- ），女，东南大学信息科学与工程学院硕士生，主要研究方向为高可靠低时延通信下的导频分配
荣欣（2000- ），女，东南大学信息科学与工程学院硕士生，主要研究方向为高可靠低时延的通信接入
李佳珉（1983- ），男，博士，东南大学信息科学与工程学院副教授，主要研究方向为密集分布式 MIMO 技术、毫米波大规模MIMO技术、卫星通信技术（空天地海一体化）、基于多目标优化及人工智能的未来移动通信理论
尤肖虎（1962- ），男，博士，东南大学移动通信国家重点实验室主任，紫金山实验室副主任，主要研究方向为无线与移动通信系统、现代数字信号处理等
基金资助:
国家重点研发计划项目(2021YFB2900300);国家自然科学基金资助项目(61971127);国家自然科学基金资助项目(61871465);国家自然科学基金资助项目(61871122)

A survey of key issues of URLLC in industrial internet of things

Han WANG¹, Lei DIAO¹, Mengling WANG¹, Xin RONG¹, Jiamin LI¹^,², Xiaohu YOU¹^,²

¹ National Mobile Communications Research Laboratory, Southeast University, Nanjing 210096, China
² Purple Mountain Laboratories, Nanjing 211111, China

Revised:2022-03-09 Online:2022-05-31 Published:2022-05-01
Supported by:
The National Key Research and Development Program(2021YFB2900300);The National Natural Science Foundation of China(61971127);The National Natural Science Foundation of China(61871465);The National Natural Science Foundation of China(61871122)

摘要/Abstract

摘要：

在6G物联网时代，海量终端设备智慧互联，发掘环境信息提高生活质量，创造更加智能的世界。随着经济社会和工业的发展，工业物联网（industrial internet of things，IIoT）中工业节点的数量以惊人的速度增长，这些工业节点间实时传输交换信息，对通信的时延和可靠性提出了更高要求。在有限的时频资源和严格的通信质量要求下，为保证IIoT中海量终端的超可靠超低时延通信（ultra-reliable and low-latency communication，URLLC），需要从低时延、可靠性、能量效率、频谱效率和可拓展性等方面对存在的关键问题进行分析。在工业物联网场景下，结合URLLC的特点和需求，研究了工业物联网中通信的关键问题：活跃用户检测、随机接入、资源分配和通算融合中的挑战和机遇，对关键问题以及现有技术进行总结分析后，提出了未来的研究方向。

关键词: 工业物联网, URLLC, 随机接入, 资源分配, 通算融合

Abstract:

In the age of 6G internet of things, massive terminal devices are connected intelligently to explore environmental information to improve life quality and create a more intelligent world.With the development of economic society and industry, the number of industrial nodes in the industrial internet of things (IIoT) grows at an significant speed.The real-time transmission and exchange of information between these industrial nodes puts forward higher requirements for communication delay and reliability.Under limited time-frequency resources and strict communication quality requirements, in order to ensure ultra-reliable and low-latency communication (URLLC) of massive terminals in IIoT, it is necessary to analyze the existing key problems from the aspects of low delay, reliability, energy efficiency, spectrum efficiency and scalability.In the scenario of IIoT, combined with the characteristics and requirements of URLLC, the key issues of communication in IIoT were studied, including challenges and opportunities in active user detection, random access, resource allocation and convergence of communication and computation.After summarizing and analyzing the key issues and existing technologies, the future research direction was proposed.

Key words: IIoT, URLLC, random access, resource allocation, convergence of communication and computation

中图分类号:

TN914

汪晗, 刁磊, 王梦玲, 荣欣, 李佳珉, 尤肖虎. 工业物联网中URLLC的关键问题分析[J]. 电信科学, 2022, 38(Z1): 77-92.

Han WANG, Lei DIAO, Mengling WANG, Xin RONG, Jiamin LI, Xiaohu YOU. A survey of key issues of URLLC in industrial internet of things[J]. Telecommunications Science, 2022, 38(Z1): 77-92.

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算法	文献	举例	优点	缺点
协方差算法	[28]	梯度下降算法	所需导频较短	需要大量天线
CS算法	[20]	AMP、MAP	估计精度高	复杂度较高
贝叶斯算法	[22]	SBL	估计精度高	信道信息已知
深度学习算法	[37]	基于模型或数据方法	计算复杂度低	需要大量数据

RA方案	接入时延	接入成功率	能量效率	QoS保障
ACB方案	不定	较高	中等	较高
退避方案	较低	较低	较低	无
动态资源分配方案	中等	中等	中等	无
时隙随机接入方案	较低	高	高	较低
RA资源分割方案	较高	中等	中等	无
基于寻呼的方案	中等	中等	中等	无

序号	文献	优化目标	约束条件	优化算法	优势和不足
1	[69]	最大化设备加权和速率	时延、用户QoS	几何程序问题求解	算法收敛快，但对有限块长的速率表达式和SINR表达式进行了近似估计带来误差
2	[71]	最小化上行和下行总带宽	端到端时延和丢包率	两步算法	联合考虑上行和下行传输，但只考虑了本地通信场景下的优化
3	[72]	最大化频谱效率	可靠性、时延	迭代算法	针对可用频谱分布在不连续的频段这一问题，提高了系统频谱效率和用户公平性，但只适用于周期的数据包到达模型
4	[73]	最小化错误概率	时延	基于扰动的迭代算法	算法复杂度低，但考虑的无人机辅助中继的特殊场景，无人机本身的续航能力、计算和通信能力有限
5	[74-75]	最小化错误概率	可靠性、能量、时延	图论和迭代算法	对4种下行多址传输策略的资源分配进行了优化，但是在设备数多于两个时优化算法的可拓展性还有待提高
6	[76]	最大化能量效率	时延、解码错误概率	非凸问题转化	提升了的URLLC的能量效率，但是假设没有强的小区内/间干扰
8	[77]	最大化安全能量效率	最小安全可达速率	凸优化	考虑了URLLC中的安全性问题，但使用凸优化的方法复杂度较高

文献	优化目标	方法
[87]	最小化任务时延	机器学习
[88]	降低时延和能耗	3层优化框架
[89]	最小化运营成本	分布式算法
[90]	最小化任务的长期平均时延	深度强化学习
[91]	提高服务质量	深度强化学习

工业物联网中URLLC的关键问题分析

A survey of key issues of URLLC in industrial internet of things

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