1.
Singh, Jitendra; Srivastava, Suraj; Yadav, Surya P.; Jagannatham, Aditya K.; Hanzo, Lajos
Joint Hybrid Transceiver and Reflection Matrix Design for RIS-Aided mmWave MIMO Cognitive Radio Systems Journal Article
In: IEEE Transactions on Cognitive Communications and Networking, vol. 11, no. 1, pp. 391–407, 2025, ISSN: 2332-7731.
Abstract | Links | BibTeX | Tags: Array signal processing, cognitive radio, Downlink, hybrid beamforming, Interference, Millimeter wave communication, MIMO communication, mmWave, Quality of service, Radio frequency, Riemannian conjugate gradient, RIS
@article{singh_joint_2025,
title = {Joint Hybrid Transceiver and Reflection Matrix Design for RIS-Aided mmWave MIMO Cognitive Radio Systems},
author = {Jitendra Singh and Suraj Srivastava and Surya P. Yadav and Aditya K. Jagannatham and Lajos Hanzo},
url = {https://ieeexplore.ieee.org/document/10561503},
doi = {10.1109/TCCN.2024.3415620},
issn = {2332-7731},
year = {2025},
date = {2025-02-01},
urldate = {2025-10-08},
journal = {IEEE Transactions on Cognitive Communications and Networking},
volume = {11},
number = {1},
pages = {391–407},
abstract = {In this work, a reconfigurable intelligent surface (RIS)-aided millimeter wave (mmWave) multiple-input multiple-output (MIMO) cognitive radio (CR) downlink operating in the underlay mode is investigated. The cognitive base station (CBS) communicates with multiple secondary users (SUs), each having multiple RF chains in the presence of a primary user (PU). We conceive a joint hybrid transmit precoder (TPC), receiver combiner (RC), and RIS reflection matrix (RM) design, which maximizes the sum spectral efficiency (SE) of the secondary system while maintaining the interference induced at the PU below a specified threshold. To this end, we formulate the sum-SE maximization problem considering the total transmit power (TP), the interference power (IP), and the non-convex unity modulus constraints of the RF TPC, RF RC, and RM. To solve this highly non-convex problem, we propose a two-stage hybrid transceiver design in conjunction with a novel block coordinate descent (BCD)-successive Riemannian conjugate gradient (SRCG) algorithm. We initially decompose the RF TPC, RC, and RM optimization problem into a series of sub-problems and subsequently design pairs of RF TPC and RC vectors, followed by successively optimizing the elements of the RM using the iterative BCD-SRCG algorithm. Furthermore, based on the effective baseband (BB) channel, the BB TPC and BB RC are designed using the proposed direct singular value decomposition (D-SVD) and projection based SVD (P-SVD) methods. Subsequently, the proportional water-filling solution is proposed for optimizing the power, which maximizes the weighted sum-SE of the system. Finally, simulation results are provided to compare our proposed schemes to several benchmarks and quantify the impact of other parameters on the sum-SE of the system.},
keywords = {Array signal processing, cognitive radio, Downlink, hybrid beamforming, Interference, Millimeter wave communication, MIMO communication, mmWave, Quality of service, Radio frequency, Riemannian conjugate gradient, RIS},
pubstate = {published},
tppubtype = {article}
}
In this work, a reconfigurable intelligent surface (RIS)-aided millimeter wave (mmWave) multiple-input multiple-output (MIMO) cognitive radio (CR) downlink operating in the underlay mode is investigated. The cognitive base station (CBS) communicates with multiple secondary users (SUs), each having multiple RF chains in the presence of a primary user (PU). We conceive a joint hybrid transmit precoder (TPC), receiver combiner (RC), and RIS reflection matrix (RM) design, which maximizes the sum spectral efficiency (SE) of the secondary system while maintaining the interference induced at the PU below a specified threshold. To this end, we formulate the sum-SE maximization problem considering the total transmit power (TP), the interference power (IP), and the non-convex unity modulus constraints of the RF TPC, RF RC, and RM. To solve this highly non-convex problem, we propose a two-stage hybrid transceiver design in conjunction with a novel block coordinate descent (BCD)-successive Riemannian conjugate gradient (SRCG) algorithm. We initially decompose the RF TPC, RC, and RM optimization problem into a series of sub-problems and subsequently design pairs of RF TPC and RC vectors, followed by successively optimizing the elements of the RM using the iterative BCD-SRCG algorithm. Furthermore, based on the effective baseband (BB) channel, the BB TPC and BB RC are designed using the proposed direct singular value decomposition (D-SVD) and projection based SVD (P-SVD) methods. Subsequently, the proportional water-filling solution is proposed for optimizing the power, which maximizes the weighted sum-SE of the system. Finally, simulation results are provided to compare our proposed schemes to several benchmarks and quantify the impact of other parameters on the sum-SE of the system.
2.
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.
3.
Goay, Amus Chee Yuen; Mishra, Deepak; Matthaiou, Michail; Seneviratne, Aruna
Range Maximization by Optimizing Tag-to-Tag Cooperative Backscatter Communication Journal Article
In: IEEE Transactions on Green Communications and Networking, pp. 1–1, 2025, ISSN: 2473-2400.
Abstract | Links | BibTeX | Tags: Backscatter, Backscatter communication, cooperation, green communication, Internet of Things, Protocols, Quality of service, range maximization, Reflection coefficient, Relays, Resource management, tag-to-tag network, Throughput, time allocation, Wireless communication, Wireless sensor networks
@article{goay_range_2025,
title = {Range Maximization by Optimizing Tag-to-Tag Cooperative Backscatter Communication},
author = {Amus Chee Yuen Goay and Deepak Mishra and Michail Matthaiou and Aruna Seneviratne},
url = {https://ieeexplore.ieee.org/document/11008574},
doi = {10.1109/TGCN.2025.3570568},
issn = {2473-2400},
year = {2025},
date = {2025-01-01},
urldate = {2025-10-08},
journal = {IEEE Transactions on Green Communications and Networking},
pages = {1–1},
abstract = {Backscatter communication (BackCom) is a wireless technology that transmits information wirelessly by modulating the reflection of an incident signal, offering the advantages of low power consumption and low cost. This paper introduces a novel cooperative timing protocol in a two-tag BackCom network, where a single reader communicates with two passive backscatter tags using a cooperative scheme. These tags encode their information by modulating the backscattered signal and then transmitting it back to the reader. In the considered tag-to-tag cooperative scheme, the tag closer to the reader assists the farther tag in relaying its information, effectively mitigating the doubly near-far problem commonly experienced in BackCom systems. The primary objective is to maximize the transmission range of the farther tag by jointly optimizing the proposed time allocation scheme and reflection coefficients while meeting the spectral efficiency and energy threshold constraints for the quality of service and sustainability requirements. This article formulates a non-convex optimization problem and proposes a solution methodology that efficiently approximates the optimized solution with low complexity. Numerical simulations are presented to analyze the effects of varying energy and spectral efficiency requirements on the maximized transmission range. The results demonstrate that the proposed tag-to-tag cooperative BackCom framework provides a significant performance improvement, with an average range gain of over 30% compared to the non-cooperative scheme.},
keywords = {Backscatter, Backscatter communication, cooperation, green communication, Internet of Things, Protocols, Quality of service, range maximization, Reflection coefficient, Relays, Resource management, tag-to-tag network, Throughput, time allocation, Wireless communication, Wireless sensor networks},
pubstate = {published},
tppubtype = {article}
}
Backscatter communication (BackCom) is a wireless technology that transmits information wirelessly by modulating the reflection of an incident signal, offering the advantages of low power consumption and low cost. This paper introduces a novel cooperative timing protocol in a two-tag BackCom network, where a single reader communicates with two passive backscatter tags using a cooperative scheme. These tags encode their information by modulating the backscattered signal and then transmitting it back to the reader. In the considered tag-to-tag cooperative scheme, the tag closer to the reader assists the farther tag in relaying its information, effectively mitigating the doubly near-far problem commonly experienced in BackCom systems. The primary objective is to maximize the transmission range of the farther tag by jointly optimizing the proposed time allocation scheme and reflection coefficients while meeting the spectral efficiency and energy threshold constraints for the quality of service and sustainability requirements. This article formulates a non-convex optimization problem and proposes a solution methodology that efficiently approximates the optimized solution with low complexity. Numerical simulations are presented to analyze the effects of varying energy and spectral efficiency requirements on the maximized transmission range. The results demonstrate that the proposed tag-to-tag cooperative BackCom framework provides a significant performance improvement, with an average range gain of over 30% compared to the non-cooperative scheme.