1.
Mobini, Zahra; Mohammadi, Mohammadali; He, Jiajun; Ngo, Hien Quoc; Matthaiou, Michail
Cell-Free Massive MIMO-Assisted ISAC with Beam Scanning Proceedings Article
In: 2025 IEEE 26th International Workshop on Signal Processing and Artificial Intelligence for Wireless Communications (SPAWC), pp. 1–5, 2025, ISSN: 1948-3252, (ISSN: 1948-3252).
Abstract | Links | BibTeX | Tags: Conferences, Copper, Integrated sensing and communication, Optimization, Programming, Protocols, Signal processing, Spectral efficiency, Three-dimensional displays, Transmitters
@inproceedings{mobini_cell-free_2025,
title = {Cell-Free Massive MIMO-Assisted ISAC with Beam Scanning},
author = {Zahra Mobini and Mohammadali Mohammadi and Jiajun He and Hien Quoc Ngo and Michail Matthaiou},
url = {https://ieeexplore.ieee.org/document/11143371},
doi = {10.1109/SPAWC66079.2025.11143371},
issn = {1948-3252},
year = {2025},
date = {2025-07-01},
urldate = {2025-10-08},
booktitle = {2025 IEEE 26th International Workshop on Signal Processing and Artificial Intelligence for Wireless Communications (SPAWC)},
pages = {1–5},
abstract = {This paper proposes a comprehensive framework for a cell-free massive multiple-input multiple-output (CF-mMIMO) integrated sensing and communication (ISAC) system, where the access points (APs) are partitioned into communication APs (CAPs) and the sensing APs (SAPs) to simultaneously support downlink (DL) communications and multi-static sensing. A dedicated sensing transmitter (ST) and the SAPs cooperatively sense a target within a designated zone, while the CAPs serve multiple communication users (CUs). To enable practical 3-dimensional (3D) target localization, we develop a novel beam scanning protocol and derive closed-form expressions for the DL spectral efficiency (SE), mainlobe-to-average sensing ratio (MASR), and the Cramer-Rao lower bound (CRLB) of target estimation. Moreover, we formulate a power optimization problem to improve the sensing performance under SE constraints for CUs, solving it efficiently using fractional programming (FP) techniques. Numerical results demonstrate that our approach achieves sensing performance gains of up to 20 dB and significantly reduces the CRLB.},
note = {ISSN: 1948-3252},
keywords = {Conferences, Copper, Integrated sensing and communication, Optimization, Programming, Protocols, Signal processing, Spectral efficiency, Three-dimensional displays, Transmitters},
pubstate = {published},
tppubtype = {inproceedings}
}
This paper proposes a comprehensive framework for a cell-free massive multiple-input multiple-output (CF-mMIMO) integrated sensing and communication (ISAC) system, where the access points (APs) are partitioned into communication APs (CAPs) and the sensing APs (SAPs) to simultaneously support downlink (DL) communications and multi-static sensing. A dedicated sensing transmitter (ST) and the SAPs cooperatively sense a target within a designated zone, while the CAPs serve multiple communication users (CUs). To enable practical 3-dimensional (3D) target localization, we develop a novel beam scanning protocol and derive closed-form expressions for the DL spectral efficiency (SE), mainlobe-to-average sensing ratio (MASR), and the Cramer-Rao lower bound (CRLB) of target estimation. Moreover, we formulate a power optimization problem to improve the sensing performance under SE constraints for CUs, solving it efficiently using fractional programming (FP) techniques. Numerical results demonstrate that our approach achieves sensing performance gains of up to 20 dB and significantly reduces the CRLB.