@article{ihsan_energy-efficient_2025,

title = {Energy-Efficient TDMA-NOMA for RIS-Assisted Ultra-Dense VLC Networks},

author = {Asim Ihsan and Muhammad Asif and Wali Ullah Khan and Isaac N. O. Osahon and Sujan Rajbhandari},

doi = {10.1109/tgcn.2024.3511114},

issn = {2473-2400},

year  = {2025},

date = {2025-09-01},

journal = {IEEE Transactions on Green Communications and Networking},

volume = {9},

number = {3},

pages = {1239–1253},

abstract = {This paper proposes an energy-efficient optimization technique for downlink indoor visible light communication (VLC) systems using hybrid non-orthogonal multiple access (NOMA) and reconfigurable intelligent surfaces (RIS). The approach considers a hybrid time division multiple access-NOMA (TDMA-NOMA) to provide massive connectivity to multi-clusters. Clusters of users are formed using NOMA while TDMA is used to allocate a specific time slot within a communication frame. The proposed technique optimizes the precoding at the multi-LED transmitter, RIS tuning parameters, and time-slot allocation parameters for each cluster to maximize the system’s energy efficiency (EE). The EE optimization problem is solved through the block coordinate descent (BCD) framework, which splits the optimization problem into two blocks. An alternating optimization (AO) framework is used in the first block to optimize the transmit precoding through conic quadratic programming (CQP) and RIS tuning parameters through a semidefinite programming (SDP) technique based on the surrogate optimization method. The second block allocates energy-efficient time-slot for each cluster through linear programming (LP) approach to further improve the EE of the system. The simulation results indicate that the proposed BCD framework achieves fast convergence and excellent performance in terms of the EE of the system while maintaining low computational complexity.},

keywords = {Energy Efficiency, Hybrid TDMA-NOMA Systems, Reconfigurable Intelligent Surfaces, Resource Allocations, Visible Light Communication},

pubstate = {published},

tppubtype = {article}

}

@article{rai_spectral_2025,

title = {The Spectral Versus Energy Efficiency Trade-Off in Dynamic User Clustering Aided mmWave NOMA Networks},

author = {Sudhakar Rai and Ekant Sharma and Aditya K. Jagannatham and Lajos Hanzo},

url = {https://ieeexplore.ieee.org/document/10769478},

doi = {10.1109/TCOMM.2024.3506920},

issn = {1558-0857},

year  = {2025},

date = {2025-06-01},

urldate = {2025-10-08},

journal = {IEEE Transactions on Communications},

volume = {73},

number = {6},

pages = {4503–4519},

abstract = {The spectral efficiency (SE) and global energy efficiency (GEE) trade-off encountered in the design of millimeter-wave (mmWave)-based massive multi-input multi-output (MIMO) non-orthogonal multiple access (NOMA) networks is investigated with a particular focus on user clustering. By exploiting the similarity among user channels a pair of spectral and energy-efficient user clustering algorithms are proposed for dynamically selecting both the number of clusters and the number of users in each cluster. Subsequently, a joint analog precoder/combiner and user clustering technique is developed, followed by a multi-objective optimization (MOO) framework for flexibly balancing the GEE and SE objectives in a mmWave NOMA network subject to specific constraints. The MOO objective is initially transformed to a weighted sum rate maximization problem, followed by a quadratic-transform (QT)-based approach conceived for maximizing the non-convex objective by approximating it as a concave-convex function. Our simulation results demonstrate that the user clustering techniques designed attain a 85% performance gain over random clustering technique and demonstrating the benefits of the algorithm designed for mmWave NOMA networks.},

keywords = {Array signal processing, Clustering algorithms, Energy Efficiency, fractional programming, Heuristic algorithms, Hybrid power systems, hybrid precoding, Interference cancellation, Millimeter wave communication, MIMO, mmWave, NOMA, Optimization, Resource management, Spectral efficiency, user clustering},

pubstate = {published},

tppubtype = {article}

}

@article{sui_ris-assisted_2025,

title = {RIS-Assisted Cell-Free Massive MIMO Relying on Reflection Pattern Modulation},

author = {Zeping Sui and Hien Quoc Ngo and Trinh Van Chien and Michail Matthaiou and Lajos Hanzo},

url = {https://ieeexplore.ieee.org/document/10640072},

doi = {10.1109/TCOMM.2024.3446589},

issn = {1558-0857},

year  = {2025},

date = {2025-02-01},

urldate = {2025-10-08},

journal = {IEEE Transactions on Communications},

volume = {73},

number = {2},

pages = {968–982},

abstract = {We propose reflection pattern modulation-aided reconfigurable intelligent surface (RPM-RIS)-assisted cell-free massive multiple-input-multiple-output (CF-mMIMO) schemes for green uplink transmission. In our RPM-RIS-assisted CF-mMIMO system, extra information is conveyed by the indices of the active RIS blocks, exploiting the joint benefits of both RIS-assisted CF-mMIMO transmission and RPM. Since only part of the RIS blocks are active, our proposed architecture strikes a flexible energy vs. spectral efficiency (SE) trade-off. We commence with introducing the system model by considering spatially correlated channels. Moreover, we conceive a channel estimation scheme subject to the linear minimum mean-square error (MMSE) constraint, yielding sufficient information for the subsequent signal processing steps. Then, upon exploiting a so-called large-scale fading decoding (LSFD) scheme, the uplink signal-to-interference-and-noise ratio (SINR) is derived based on the RIS ON/OFF statistics, where both maximum ratio (MR) and local minimum mean-square error (L-MMSE) combiners are considered. By invoking the MR combiner, the closed-form expression of the uplink SE is formulated based only on the channel statistics. Furthermore, we derive the total energy efficiency (EE) of our proposed RPM-RIS-assisted CF-mMIMO system. Additionally, we propose a chaotic sequence-based adaptive particle swarm optimization (CSA-PSO) algorithm to maximize the total EE by designing the RIS phase shifts. Specifically, the initial particle diversity is promoted by invoking chaotic sequences, and an adaptive time-varying inertia weight is developed to improve its particle search performance. Furthermore, the particle mutation and reset steps are appropriately selected to enable the algorithm to escape from local optima. Finally, our simulation results demonstrate that the proposed RPM-RIS-assisted CF-mMIMO architecture strikes an attractive SE vs. EE trade-off, while the CSA-PSO algorithm is capable of attaining a significant EE performance gain compared to conventional solutions.},

keywords = {Array signal processing, Cell-free massive MIMO, Channel estimation, Chaotic communication, Energy Efficiency, iterative optimization, Optimization, Reconfigurable Intelligent Surfaces, reflection pattern modulation, Spectral efficiency, Symbols, Technological innovation, Uplink},

pubstate = {published},

tppubtype = {article}

}

@article{yan_optimum_2025,

title = {Optimum Distance for In-Flight UAV-to-UAV Wireless Charging},

author = {Hua Yan and Yunfei Chen},

url = {https://ieeexplore.ieee.org/document/11123803/},

doi = {10.1109/ACCESS.2025.3598733},

issn = {2169-3536},

year  = {2025},

date = {2025-01-01},

urldate = {2025-10-08},

journal = {IEEE Access},

volume = {13},

pages = {143914–143924},

abstract = {Wireless charging is a promising technology for communications using battery-powered unmanned aerial vehicles (UAVs). In this paper, the optimal distance for UAV-to-UAV in-flight wireless charging and communications is studied. Considering the practical applications, two schemes are proposed. In the first scheme, the discharging UAV (D-UAV) and the charged UAV (C-UAV) are aligned during charging, which requires the D-UAV and the C-UAV to remain relatively stationary. In the second scheme, the D-UAV and the C-UAV move during charging. For both schemes, we aim to maximize the received energy at the C-UAV under the condition that the minimum achievable rate for communications is met. Numerical results show that the optimal distance exists in the Fresnel zone. They also show that the optimal distance increases with the charging frequency. This work provides useful guidance for UAV in-flight wireless charging and communications system designs.},

keywords = {Aperture antennas, Autonomous aerial vehicles, Batteries, Energy Efficiency, Energy loss, far-field, Inductive charging, near-field, Receiving antennas, RF signals, Simultaneous wireless information and power transfer, Transmitting antennas, UAV communications, Wireless communication, Wireless communications, wireless power transfer (WPT)},

pubstate = {published},

tppubtype = {article}

}

@article{mohammadi_next-generation_2024,

title = {Next-Generation Multiple Access With Cell-Free Massive MIMO},

author = {Mohammadali Mohammadi and Zahra Mobini and Hien Quoc Ngo and Michail Matthaiou},

url = {https://ieeexplore.ieee.org/document/10684238},

doi = {10.1109/JPROC.2024.3451372},

issn = {1558-2256},

year  = {2024},

date = {2024-09-01},

urldate = {2025-10-08},

journal = {Proceedings of the IEEE},

volume = {112},

number = {9},

pages = {1372–1420},

abstract = {To meet the unprecedented mobile traffic demands of future wireless networks, a paradigm shift from conventional cellular networks to distributed communication systems is imperative. Cell-free massive multiple-input multiple-output (CF-mMIMO) represents a practical and scalable embodiment of distributed/network MIMO systems. It inherits not only the key benefits of co-located massive MIMO systems but also the macro-diversity gains from distributed systems. This innovative architecture has demonstrated significant potential in enhancing network performance from various perspectives, outperforming co-located mMIMO and conventional small-cell systems. Moreover, CF-mMIMO offers flexibility in integration with emerging wireless technologies such as full-duplex (FD), nonorthogonal transmission schemes, millimeter-wave (mmWave) communications, ultrareliable low-latency communication (URLLC), unmanned aerial vehicle (UAV)-aided communication, and reconfigurable intelligent surfaces (RISs). In this article, we provide an overview of current research efforts on CF-mMIMO systems and their promising future application scenarios. We then elaborate on new requirements for CF-mMIMO networks in the context of these technological breakthroughs. We also present several current open challenges and outline future research directions aimed at fully realizing the potential of CF-mMIMO systems in meeting the evolving demands of future wireless networks.},

keywords = {5G mobile communication, 6G mobile communication, Cell-free massive multiple-input multiple-output (CF-mMIMO), Channel estimation, Energy Efficiency, energy efficiency (EE), Massive MIMO, Millimeter wave communication, Next generation networking, Signal to noise ratio, sixth-generation (6G) wireless, Spectral efficiency, spectral efficiency (SE), Surveys, Telecommunication traffic, Wireless networks},

pubstate = {published},

tppubtype = {article}

}