通信感知一体化原型验证的研究现状与发展趋势

doi:10.11959/j.issn.1000-436x.2023205

通信学报 ›› 2023, Vol. 44 ›› Issue (11): 43-54.doi: 10.11959/j.issn.1000-436x.2023205

• 专题：面向泛在物联的普适感知与智能识别关键技术 • 上一篇

通信感知一体化原型验证的研究现状与发展趋势

杨杰¹^,², 黄艺璇³, 杜涛³, 阙杭³, 夏树强⁴^,⁵, 金石¹^,³

¹ 东南大学移动信息通信与安全前沿科学中心，江苏南京 210096
² 东南大学复杂工程系统测量与控制教育部重点实验室，江苏南京 210096
³ 东南大学移动通信全国重点实验室，江苏南京 210096
⁴ 中兴通讯股份有限公司，广东深圳 518055
⁵ 移动网络和移动通讯多媒体技术国家重点实验室，广东深圳 518055

修回日期:2023-10-16 出版日期:2023-11-01 发布日期:2023-11-01
作者简介:杨杰（1993− ），女，安徽六安人，博士，东南大学讲师、硕士生导师，主要研究方向为移动通信、智能感知、通信感知一体化等
黄艺璇（1999− ），男，河南驻马店人，东南大学博士生，主要研究方向为通信感知一体化、可重构智能超表面等
杜涛（1995− ），男，江苏句容人，东南大学博士生，主要研究方向为通信感知一体化、大规模MIMO天线校准技术等
阙杭（1997− ），男，江苏南通人，东南大学博士生，主要研究方向为毫米波通信、通信感知一体化技术等
夏树强（1976− ），男，河南鹤壁人，中兴通讯股份有限公司正高级工程师，主要研究方向为载波聚合、低时延高可靠、通信感知一体化的关键算法设计和标准预研等
金石（1974− ），男，安徽黄山人，博士，东南大学教授、博士生导师，主要研究方向为5G/B5G移动通信理论与关键技术、物联网理论与关键技术、机器学习与大数据处理在移动通信中的应用等
基金资助:
国家自然科学基金资助项目(62301156);国家自然科学基金资助项目(62261160576);国家自然科学基金资助项目(62341107);中央高校基本科研业务费专项资金资助项目(2242022k60004);东南大学至善青年学者基金资助项目(2242023R40042)

Prototype verification for integrated sensing and communications:current status and development trends

Jie YANG¹^,², Yixuan HUANG³, Tao DU³, Hang QUE³, Shuqiang XIA⁴^,⁵, Shi JIN¹^,³

¹ Frontiers Science Center for Mobile Information Communication and Security, Southeast University, Nanjing 210096, China
² Key Laboratory of Measurement and Control of Complex Systems of Engineering, Ministry of Education, Southeast University, Nanjing 210096, China
³ National Mobile Communications Research Laboratory, Southeast University, Nanjing 210096, China
⁴ ZTE Corporation, Shenzhen 518055, China
⁵ State Key Laboratory of Mobile Network and Mobile Multimedia Technology, Shenzhen 518055, China

Revised:2023-10-16 Online:2023-11-01 Published:2023-11-01
Supported by:
The National Natural Science Foundation of China(62301156);The National Natural Science Foundation of China(62261160576);The National Natural Science Foundation of China(62341107);The Fundamental Research Funds for the Central Universities(2242022k60004);The “Zhishan” Scholars Programs of Southeast University(2242023R40042)

摘要/Abstract

摘要：

针对技术落地面临的实际挑战，对通信感知一体化原型验证的研究现状和发展趋势进行了阐述和总结。首先，概括基于单节点的通信感知一体化原型系统在定位、环境制图、成像、波形设计和波束追踪等方面的研究进展和实测性能。接着，从车联网和物联网场景入手，分析基于多点协作的通信感知一体化原型系统的实际增益。然后，聚焦基于跨设备的通信感知一体化原型验证，总结各传感器的优劣势和实测融合效果。最后，针对现有原型验证遇到的问题和挑战，指出通信感知一体化系统实现和技术验证的研究趋势。

关键词: 通信感知一体化, 原型验证, 定位, 环境制图, 成像, 波形设计, 波束追踪

Abstract:

Considering the practical challenges faced by the commercialization of integrated sensing and communication (ISAC), the implementation progress and future trends of ISAC were elaborated and summarized.First, the research progress and empirical performance of single node-based ISAC prototype systems were summarized, including positioning, environmental mapping, imaging, waveform design, and beam tracking.Next, the actual gain of multi-nodes cooperation-based ISAC prototype systems in the scenarios of the Internet of vehicles and the Internet of things were analyzed.Then, focusing on cross-sensor-based ISAC prototype systems, the advantages and disadvantages of each kind of sensor and the experimental fusion performance were overviewed.Finally, the future trends in the system implementation and technical validation of ISAC were highlighted, addressing the challenges encountered in existing ISAC prototype systems.

Key words: integrated sensing and communication, prototype verification, localization, environmental mapping, imaging, waveform design, beam tracking

中图分类号:

TN92

杨杰, 黄艺璇, 杜涛, 阙杭, 夏树强, 金石. 通信感知一体化原型验证的研究现状与发展趋势[J]. 通信学报, 2023, 44(11): 43-54.

Jie YANG, Yixuan HUANG, Tao DU, Hang QUE, Shuqiang XIA, Shi JIN. Prototype verification for integrated sensing and communications:current status and development trends[J]. Journal on Communications, 2023, 44(11): 43-54.

图/表 9

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文献	工作频段/GHz	工作带宽/MHz	天线配置	波形	工作方式	实测参数	平均定位误差
文献[9]	5.1	80	4 × 1均匀线阵	啁啾	自发自收	角度	—
文献[10]	2.35	40	BS：单天线	任意	上行定位	TDOA	0.42 m（100 m²暗室）
			UE：矢量信号分析仪
文献[11]	77	2 000	les[J].IEEE Internet 单喇叭天线模拟29天线）	单载波Zadoff-Chu	自发自收	距离角度图	—
文献[12]	27.2	400	BS：16×24均匀面阵	OFDM	下行定位	AOA AOD TOA	24.82 m（10⁵m²室外）
			UE：2 × 8均匀面阵

文献	工作频段/ GHz	工作带宽/ MHz	天线配置	波形	工作方式	实测参数	环境制图精度
文献[13]	27.2	400	BS：16 × 24均匀面阵	OFDM	下行	AOA、AOD（模拟RTT）	2 m（10⁵m²室外）
			UE：2 × 8均匀面阵
文献[14]	28	400	UE：2个喇叭天线	OFDM	自发自收	距离角度图	2 m（50 m长室内走廊）

文献	工作频段/ GHz	成像技术	实测效果
文献[19]	220～300	SAR成像	2D同时用户定位和反射面成像
文献[20]	3～19.5	SAR成像	3D目标散射系数图像
文献[21]	30～36	SAR成像	3D目标散射系数图像
文献[22]	140	压缩感知辅助的SAR成像	3D目标散射系数图像
文献[23]	28～29	基于波束成形的雷达测距	3D测距深度图，测距精度15 cm
文献[24]	9.2	基于RIS的线性逆散射求解	2D金属贴片成像
文献[25]	3.198	基于RIS的线性逆散射求解	2D空间点云成像

设备类型	输出数据	特点	文献	实现功能	所提方案	预测效果
毫米波通信系统	毫米波接收信号	与电磁波传输环境高度耦合，但路径损耗高且易受阻挡	文献[33]	阻隔预测	无线指纹提取+RNN	20 ms内阻隔遮挡预测成功率高于85%
GPS	目标经纬坐标	室外实现粗略定位，但室内通常失效	文献[37]	波束预测	神经网络	相比穷举算法，波束训练开销降低70%
			文献[36]	阻隔预测	MIRNet+深度神经网络	1 s内阻隔遮挡预测成功率约为80%
相机	RGB图像	包含丰富环境信息，但易受光线条件影响	文献[40]	波束预测	自编码器网络	相比穷举算法，波束训练开销降低99%
			文献[41]	波束预测	语义信息提取+神经网络	相比直接使用RGB图像，网络参数量降低约83%
			文献[42]	波束预测	离线预测+在线追踪	相比使用离线方案，波束预测精度提升约15%
FMCW雷达	雷达回波信号	检测目标范围广，但易受射频干扰影响	文献[35]	阻隔预测	CNN	1 s内阻隔遮挡预测成功率高于90%
			文献[38]	波束预测	深度神经网络	相比穷举算法，波束训练开销降低93%
LiDAR	激光点云	检测目标精度高，但易受雨雾天气影响	文献[34]	阻隔预测	CNN	1 s内阻隔遮挡预测成功率相比无LiDAR提升45%
			文献[39]	波束预测	RNN	相比穷举算法，波束训练开销降低90%

通信感知一体化原型验证的研究现状与发展趋势

Prototype verification for integrated sensing and communications:current status and development trends

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