Integrated Sensing and Communication in 6G: Motivations, Use Cases, Requirements, Challenges and Future Directions

被引:249
作者
Tan, Danny Kai Pin [1 ]
He, Jia [1 ]
Li, Yanchun [1 ]
Bayesteh, Alireza [1 ]
Chen, Yan [1 ]
Zhu, Peiying [1 ]
Tong, Wen [1 ]
机构
[1] Huawei Technol Co Ltd, Shenzhen, Peoples R China
来源
2021 1ST IEEE INTERNATIONAL ONLINE SYMPOSIUM ON JOINT COMMUNICATIONS & SENSING (JC&S) | 2021年
关键词
Integrated Sensing and Communication (ISAC); 6G; sensing assisted communication; localization; imaging; simultaneous localization and mapping (SLAM); augmented human senses; gesture and activity recognition;
D O I
10.1109/JCS52304.2021.9376324
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In 6G, it is envisaged that the function of sensing and communication will coexist and be fully integrated in one system, sharing the same resources in time, frequency and space domains, as well as key elements including waveform, signal processing, hardware, etc. This paper discusses novel applications, key performance requirements, challenges and future research directions for Integrated Sensing and Communication (ISAC) design in 6G. First, four categories of ISAC use cases are described as new services in 6G together with their corresponding performance requirements on 6G design. In addition, it is demonstrated how the information obtained through sensing can significantly improve the performance of communication. Thereafter, the challenges in the design and evaluation of a practical ISAC system are discussed, including sensing and communication performance tradeoffs, hardware imperfections, as well as the investigation of an appropriate channel model. Finally, future research directions are presented to set the path for designing an efficient ISAC network.
引用
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页数:6
相关论文
共 18 条
[1]  
Ahmed UT, 2014, 2014 MAKASSAR INTERNATIONAL CONFERENCE ON ELECTRICAL ENGINEERING AND INFORMATICS (MICEEI), P46, DOI 10.1109/MICEEI.2014.7067308
[2]   Survey of channel and radio propagation models for wireless MIMO systems [J].
Almers, P. ;
Bonek, E. ;
Burr, A. ;
Czink, N. ;
Debbah, M. ;
Degli-Esposti, V. ;
Hofstetter, H. ;
Kyoesti, P. ;
Laurenson, D. ;
Matz, G. ;
Molisch, A. F. ;
Oestges, C. ;
Oezcelik, H. .
EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING, 2007, 2007 (1)
[3]  
[Anonymous], 2019, RP193142
[4]   Full-Duplex OFDM Radar With LTE and 5G NR Waveforms: Challenges, Solutions, and Measurements [J].
Barneto, Carlos Baquero ;
Riihonen, Taneli ;
Turunen, Matias ;
Anttila, Lauri ;
Fleischer, Marko ;
Stadius, Kari ;
Ryynanen, Jussi ;
Valkama, Mikko .
IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES, 2019, 67 (10) :4042-4054
[5]   Maximum Likelihood Speed and Distance Estimation for OFDM Radar [J].
Braun, Martin ;
Sturm, Christian ;
Jondral, Friedrich K. .
2010 IEEE RADAR CONFERENCE, 2010, :256-261
[6]   Inner Bounds on Performance of Radar and Communications Co-Existence [J].
Chiriyath, Alex R. ;
Paul, Bryan ;
Jacyna, Garry M. ;
Bliss, Daniel W. .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2016, 64 (02) :464-474
[7]  
Feng Z, 2018, 018 IEEE INT C COMMU
[8]   Using Deep Learning in Infrared Images to Enable Human Gesture Recognition for Autonomous Vehicles [J].
Geng, Keke ;
Yin, Guodong .
IEEE ACCESS, 2020, 8 :88227-88240
[9]  
Gonzalez-Prelcic Nuria, 2016, 2016 INFORM THEORY A, DOI 10.1109/ITA.2016. 7888145
[10]   Joint wireless communication and radar sensing systems - state of the art and future prospects [J].
Han, Liang ;
Wu, Ke .
IET MICROWAVES ANTENNAS & PROPAGATION, 2013, 7 (11) :876-885