TY - GEN
T1 - A Unified Tensor-Based Joint Communication and Sensing Parameter Estimation for ISAC with Large-Scale User Access
AU - Yang, Tiancheng
AU - He, Dongxuan
AU - Hou, Huazhou
AU - Wang, Hua
AU - Huang, Yongming
AU - Wang, Zhaocheng
AU - Quek, Tony Q.S.
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - The combination of active user detection (AUD) and integrated sensing and communication (ISAC) can be utilized to realize communication and sensing functionalities over one hardware platform in the ultra-massive machine-type communications (umMTC). However, due to the received signals are typically coupled in both AUD and ISAC, it is hard to obtain the communication and sensing parameters. To solve this problem, the actual channel model is first converted into a unified form through CANDECOMP/PARAFAC decomposition (CPD) to mitigate the interference between communication and radar signals. Then, by utilizing the matrix subspace-based method, the factor matrices are accurately estimated, where the equivalent path parameters can be extracted. Furthermore, to estimate the coupled path parameters, an alternating iterative estimation algorithm is proposed. Simulation results verify the superiority of our proposed joint communication and sensing parameter estimation algorithm in AUD, channel estimation, and radar sensing.
AB - The combination of active user detection (AUD) and integrated sensing and communication (ISAC) can be utilized to realize communication and sensing functionalities over one hardware platform in the ultra-massive machine-type communications (umMTC). However, due to the received signals are typically coupled in both AUD and ISAC, it is hard to obtain the communication and sensing parameters. To solve this problem, the actual channel model is first converted into a unified form through CANDECOMP/PARAFAC decomposition (CPD) to mitigate the interference between communication and radar signals. Then, by utilizing the matrix subspace-based method, the factor matrices are accurately estimated, where the equivalent path parameters can be extracted. Furthermore, to estimate the coupled path parameters, an alternating iterative estimation algorithm is proposed. Simulation results verify the superiority of our proposed joint communication and sensing parameter estimation algorithm in AUD, channel estimation, and radar sensing.
KW - Active user detection
KW - CPD
KW - integrated sensing and communication
KW - joint communication and sensing parameter estimation
KW - tensor decomposition
UR - https://www.scopus.com/pages/publications/86000027246
U2 - 10.1109/ICSIDP62679.2024.10868366
DO - 10.1109/ICSIDP62679.2024.10868366
M3 - Conference contribution
AN - SCOPUS:86000027246
T3 - IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2024
BT - IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2nd IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2024
Y2 - 22 November 2024 through 24 November 2024
ER -