1.
Fu, Jiafei; Mobini, Zahra; Ngo, Hien Quoc; Zhu, Pengcheng; Matthaiou, Michail
WMMSE-Based Processing in Cell-Free Massive MIMO Systems Journal Article
In: IEEE Wireless Communications Letters, vol. 14, no. 2, pp. 330–334, 2025, ISSN: 2162-2345.
Abstract | Links | BibTeX | Tags: Approximation algorithms, Cell-free massive MIMO, Channel estimation, Data communication, Downlink, Optimization, Power control, Precoding, Quality of service, Uplink, Vectors, weighted minimum mean square error, weighted sum-rate maximization
@article{fu_wmmse-based_2025,
title = {WMMSE-Based Processing in Cell-Free Massive MIMO Systems},
author = {Jiafei Fu and Zahra Mobini and Hien Quoc Ngo and Pengcheng Zhu and Michail Matthaiou},
url = {https://ieeexplore.ieee.org/document/10755172},
doi = {10.1109/LWC.2024.3501156},
issn = {2162-2345},
year = {2025},
date = {2025-02-01},
urldate = {2025-10-08},
journal = {IEEE Wireless Communications Letters},
volume = {14},
number = {2},
pages = {330–334},
abstract = {In this letter, we address the weighted sum-rate maximization problem in a cell-free massive multi-input multi-output (CF-mMIMO) system, subject to constraints on the minimum individual quality of service (QoS), maximum power consumption at each access point (AP), and maximum fronthaul capacity. By harnessing the low computational complexity weighted minimum mean square error (WMMSE) framework, two algorithms are proposed to solve the formulated mixed integer nonlinear programming (MINLP) problems with instantaneous/statistical channel state information (CSI). Our instantaneous CSI-based approach can be applied to jointly optimize the power control, precoding, and user association, while the statistical CSI-based approach can be utilized to jointly optimize the power control and user association. Simulation results demonstrate that the proposed instantaneous CSI-based algorithm can provide approximately 66.72% sum-rate gain compared to the scheme with random user association, equal power allocation, and fixed local MMSE-based precoding design. Additionally, the statistical CSI-based algorithm offers competitive performance compared with the instantaneous CSI-based algorithm.},
keywords = {Approximation algorithms, Cell-free massive MIMO, Channel estimation, Data communication, Downlink, Optimization, Power control, Precoding, Quality of service, Uplink, Vectors, weighted minimum mean square error, weighted sum-rate maximization},
pubstate = {published},
tppubtype = {article}
}
In this letter, we address the weighted sum-rate maximization problem in a cell-free massive multi-input multi-output (CF-mMIMO) system, subject to constraints on the minimum individual quality of service (QoS), maximum power consumption at each access point (AP), and maximum fronthaul capacity. By harnessing the low computational complexity weighted minimum mean square error (WMMSE) framework, two algorithms are proposed to solve the formulated mixed integer nonlinear programming (MINLP) problems with instantaneous/statistical channel state information (CSI). Our instantaneous CSI-based approach can be applied to jointly optimize the power control, precoding, and user association, while the statistical CSI-based approach can be utilized to jointly optimize the power control and user association. Simulation results demonstrate that the proposed instantaneous CSI-based algorithm can provide approximately 66.72% sum-rate gain compared to the scheme with random user association, equal power allocation, and fixed local MMSE-based precoding design. Additionally, the statistical CSI-based algorithm offers competitive performance compared with the instantaneous CSI-based algorithm.
2.
Mobini, Zahra; Ngo, Hien Quoc; Matthaiou, Michail; Hanzo, Lajos
Cell-Free Massive MIMO Surveillance of Multiple Untrusted Communication Links Journal Article
In: IEEE Internet of Things Journal, vol. 11, no. 20, pp. 33010–33026, 2024, ISSN: 2327-4662.
Abstract | Links | BibTeX | Tags: Cell-free massive multiple-input-multiple-output (CF-mMIMO), Communication system security, Interference, Jamming, Massive MIMO, monitoring node (MN) mode assignment, monitoring success probability (MSP), Power control, proactive monitoring, Surveillance, Technological innovation, Wireless communication, wireless information surveillance
@article{mobini_cell-free_2024,
title = {Cell-Free Massive MIMO Surveillance of Multiple Untrusted Communication Links},
author = {Zahra Mobini and Hien Quoc Ngo and Michail Matthaiou and Lajos Hanzo},
url = {https://ieeexplore.ieee.org/document/10584102},
doi = {10.1109/JIOT.2024.3422676},
issn = {2327-4662},
year = {2024},
date = {2024-10-01},
urldate = {2025-10-08},
journal = {IEEE Internet of Things Journal},
volume = {11},
number = {20},
pages = {33010–33026},
abstract = {A cell-free massive multiple-input-multiple-output (CF-mMIMO) system is considered for enhancing the monitoring performance of wireless surveillance, where a large number of distributed multiantenna aided legitimate monitoring nodes (MNs) proactively monitor multiple distributed untrusted communication links. We consider two types of MNs whose task is to either observe the untrusted transmitters or jam the untrusted receivers. We first analyze the performance of CF-mMIMO surveillance relying on both maximum ratio (MR) and partial zero-forcing (PZF) combining schemes and derive closed-form expressions for the monitoring success probability (MSP) of the MNs. We then propose a joint optimization technique that designs the MN mode assignment, power control, and MN-weighting coefficient control to enhance the MSP based on the long-term statistical channel state information knowledge. This challenging problem is effectively transformed into tractable forms and efficient algorithms are proposed for solving them. Numerical results show that our proposed CF-mMIMO surveillance system considerably improves the monitoring performance with respect to a full-duplex co-located massive multiple-input-multiple-output (MIMO) proactive monitoring system. More particularly, when the untrusted pairs are distributed over a wide area and use the MR combining, the proposed solution provides nearly a thirty-fold improvement in the minimum MSP over the co-located massive MIMO baseline, and forty-fold improvement, when the PZF combining is employed.},
keywords = {Cell-free massive multiple-input-multiple-output (CF-mMIMO), Communication system security, Interference, Jamming, Massive MIMO, monitoring node (MN) mode assignment, monitoring success probability (MSP), Power control, proactive monitoring, Surveillance, Technological innovation, Wireless communication, wireless information surveillance},
pubstate = {published},
tppubtype = {article}
}
A cell-free massive multiple-input-multiple-output (CF-mMIMO) system is considered for enhancing the monitoring performance of wireless surveillance, where a large number of distributed multiantenna aided legitimate monitoring nodes (MNs) proactively monitor multiple distributed untrusted communication links. We consider two types of MNs whose task is to either observe the untrusted transmitters or jam the untrusted receivers. We first analyze the performance of CF-mMIMO surveillance relying on both maximum ratio (MR) and partial zero-forcing (PZF) combining schemes and derive closed-form expressions for the monitoring success probability (MSP) of the MNs. We then propose a joint optimization technique that designs the MN mode assignment, power control, and MN-weighting coefficient control to enhance the MSP based on the long-term statistical channel state information knowledge. This challenging problem is effectively transformed into tractable forms and efficient algorithms are proposed for solving them. Numerical results show that our proposed CF-mMIMO surveillance system considerably improves the monitoring performance with respect to a full-duplex co-located massive multiple-input-multiple-output (MIMO) proactive monitoring system. More particularly, when the untrusted pairs are distributed over a wide area and use the MR combining, the proposed solution provides nearly a thirty-fold improvement in the minimum MSP over the co-located massive MIMO baseline, and forty-fold improvement, when the PZF combining is employed.