A Unified Channel Model for Both Communication and Sensing in Integrated Sensing and Communication Systems

被引:2
|
作者
Lou, Junpeng [1 ,2 ]
Liu, Ruiqi [1 ,2 ]
Jiang, Chuangxin [1 ,2 ]
Han, Xianghui [1 ,2 ]
Han, Zhiqiang [1 ,2 ]
Yang, Qi [1 ,2 ]
Wang, Zhongbin [1 ,2 ]
机构
[1] ZTE Corp, Wireless Res Inst, Xian 710114, Peoples R China
[2] State Key Lab Mobile Network & Mobile Multimedia, Shenzhen 518055, Peoples R China
关键词
Integrated sensing and communication; channel model; 6G; pathloss; Doppler;
D O I
10.1109/VTC2023-Fall60731.2023.10333766
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Integrated sensing and communication (lSAC) is envisaged to playa prominent role in the next generation wireless networks. Developing generic and accurate channel models for ISAC to characterize signal propagation is critical towards its successful research, standardization and deployment. In this paper, a unified approach to model an ISAC channel is proposed, which is intended to be applicable for both communication and sensing purposes. To generate the channel coefficients for sensing channels, differences from traditional communication channels including pathloss, line of sight probability, the Doppler effect and the fast fading effect are analyzed systematically. Implementations of the proposed model are carried out through simulations to demonstrate the feasibility and the accuracy.
引用
收藏
页数:6
相关论文
共 50 条
  • [21] A Unified Hardware and Channel Noise Model for Communication Systems
    Khajeh, Amin
    Amiri, Kiarash
    Khairy, Muhammed S.
    Eltawil, Ahmed M.
    Kurdahi, Fadi J.
    2010 IEEE GLOBAL TELECOMMUNICATIONS CONFERENCE GLOBECOM 2010, 2010,
  • [22] A Novel Geometry-Based Stochastic Channel Model in Integrated Sensing and Communication Scenarios
    Jin, Yunwei
    He, Ruisi
    Ai, Bo
    Wu, Tong
    Zhang, Haoxiang
    Liu, Bincheng
    Li, Yujian
    Li, Jing
    IEEE WIRELESS COMMUNICATIONS LETTERS, 2024, 13 (07) : 2018 - 2022
  • [23] Channel Sharing Aided Integrated Sensing and Communication: An Energy-Efficient Sensing Scheduling Approach
    Dou, Chenglong
    Huang, Ning
    Wu, Yuan
    Qian, Liping
    Quek, Tony Q. S.
    IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2024, 23 (05) : 4802 - 4814
  • [24] A Weighted Mahalanobis Distance Target Sensing Strategy for Underwater Integrated Sensing and Communication Systems
    Wang, Jiale
    Lian, Jie
    Zhu, Guolei
    IEEE WIRELESS COMMUNICATIONS LETTERS, 2024, 13 (01) : 79 - 83
  • [25] A modified deep learning based MIMO communication for integrated sensing, communication and computing systems
    Duan, Chaowei
    Zhang, Jian
    DIGITAL SIGNAL PROCESSING, 2023, 142
  • [26] Constant Modulus Waveform Design for Integrated Sensing and Communication Systems
    Zhong, Kai
    Hu, Jinfeng
    Cong, Yang
    Wu, Jie
    Pei, Yaya
    2022 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2022), 2022, : 3736 - 3739
  • [27] Optimizing the Sum Rate and SER of Integrated Sensing and Communication Systems
    Liu, Shiyun
    Zhang, Jinfeng
    He, Yejun
    IEEE CONFERENCE ON GLOBAL COMMUNICATIONS, GLOBECOM, 2023, : 2493 - 2498
  • [28] Beamforming in Integrated Sensing and Communication Systems With Reconfigurable Intelligent Surfaces
    Sankar, R. S. Prasobh
    Chepuri, Sundeep Prabhakar
    Eldar, Yonina C.
    IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2024, 23 (05) : 4017 - 4031
  • [29] FDA-OFDM for Integrated Navigation, Sensing, and Communication Systems
    Huang, He
    Wang, Wen-Qin
    IEEE AEROSPACE AND ELECTRONIC SYSTEMS MAGAZINE, 2018, 33 (5-6) : 34 - 42
  • [30] Integrated Sensing and Communication Systems With Simultaneous Public and Confidential Transmission
    Xu, Shanfeng
    Liu, Peng
    Wang, Xinyi
    Huang, Jingxuan
    Fei, Zesong
    IEEE INTERNET OF THINGS JOURNAL, 2024, 11 (23): : 38113 - 38125