1.
Xiao, Yun; Wang, Enhao; Chen, Yunfei
Integrated Sensing and Communications With Multiple Targets and Multiple Users in Mixed Field Proceedings Article
In: 2024 IEEE 24th International Conference on Communication Technology (ICCT), pp. 1288–1292, 2024, ISSN: 2576-7828, (ISSN: 2576-7828).
Abstract | Links | BibTeX | Tags: Antenna arrays, Array signal processing, Beamforming, far-filed, Integrated sensing and communication, integrated sensing and communications, Interference, mixed field, model mismatch, multiple-target, near-field, Next generation networking, Numerical models, Optimization, Propagation losses, Signal to noise ratio, Wireless communication
@inproceedings{xiao_integrated_2024,
title = {Integrated Sensing and Communications With Multiple Targets and Multiple Users in Mixed Field},
author = {Yun Xiao and Enhao Wang and Yunfei Chen},
url = {https://ieeexplore.ieee.org/document/10946468},
doi = {10.1109/ICCT62411.2024.10946468},
issn = {2576-7828},
year = {2024},
date = {2024-10-01},
urldate = {2025-10-08},
booktitle = {2024 IEEE 24th International Conference on Communication Technology (ICCT)},
pages = {1288–1292},
abstract = {Integrated sensing and communications (ISAC) plays a crucial role in the next-generation wireless systems. Owing to the deployment of high carrier frequencies and/or large-scale antenna arrays, targets and communications users in the ISAC systems may follow different propagation models. However, most existing works assume the same propagation model for both communications and sensing. This work considers a practical scenario where multiple targets and communications users are in different fields. Beamforming design is proposed to optimize the sensing signal-to-clutter-plus-noise ratio (SCNR) of each target. Specifically, a sensing performance fairness profile optimization (FPO) problem is formulated, and a Dinkelbach-type algorithm is proposed to solve the problem. Numerical results show the tradeoff between mixed-field communications and sensing, the effects of antenna size and model mismatch between near field and far field on the sensing performance of the mixed-field ISAC.},
note = {ISSN: 2576-7828},
keywords = {Antenna arrays, Array signal processing, Beamforming, far-filed, Integrated sensing and communication, integrated sensing and communications, Interference, mixed field, model mismatch, multiple-target, near-field, Next generation networking, Numerical models, Optimization, Propagation losses, Signal to noise ratio, Wireless communication},
pubstate = {published},
tppubtype = {inproceedings}
}
Integrated sensing and communications (ISAC) plays a crucial role in the next-generation wireless systems. Owing to the deployment of high carrier frequencies and/or large-scale antenna arrays, targets and communications users in the ISAC systems may follow different propagation models. However, most existing works assume the same propagation model for both communications and sensing. This work considers a practical scenario where multiple targets and communications users are in different fields. Beamforming design is proposed to optimize the sensing signal-to-clutter-plus-noise ratio (SCNR) of each target. Specifically, a sensing performance fairness profile optimization (FPO) problem is formulated, and a Dinkelbach-type algorithm is proposed to solve the problem. Numerical results show the tradeoff between mixed-field communications and sensing, the effects of antenna size and model mismatch between near field and far field on the sensing performance of the mixed-field ISAC.