@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{trinh_optical_2025,

title = {Optical RISs Improve the Secret Key Rate of Free-Space QKD in HAP-to-UAV Scenarios},

author = {Phuc V. Trinh and Shinya Sugiura and Chao Xu and Lajos Hanzo},

url = {https://ieeexplore.ieee.org/document/10993364},

doi = {10.1109/JSAC.2025.3568050},

issn = {1558-0008},

year  = {2025},

date = {2025-08-01},

urldate = {2025-10-08},

journal = {IEEE Journal on Selected Areas in Communications},

volume = {43},

number = {8},

pages = {2747–2764},

abstract = {Large optical reconfigurable intelligent surfaces (ORISs) are proposed for employment on building rooftops to facilitate free-space quantum key distribution (QKD) between high-altitude platforms (HAPs) and low-altitude platforms (LAPs). Due to practical constraints, the communication terminals can only be positioned beneath the LAPs, preventing direct upward links to HAPs. By deploying ORISs on rooftops to reflect the beam arriving from HAPs towards LAPs from below, reliable HAP-to-LAP links can be established. To accurately characterize the optical beam propagation, we develop an analytical channel model based on extended Huygens-Fresnel principles for representing both the atmospheric turbulence effects and the hovering fluctuations of LAPs. This model facilitates adaptive ORIS beam-width control through linear, quadratic, and focusing phase shifts, which are capable of effectively mitigating the detrimental effects of beam broadening and pointing errors (PE). Consequently, the information-theoretic bound of the secret key rate and the security performance of a decoy-state QKD protocol are analyzed. Our findings demonstrate that quadratic phase shifts enhance the SKR at high HAP-ORIS zenith angles or mild PE conditions by narrowing the beam to optimal sizes. By contrast, linear phase shifts are advantageous at low HAP-ORIS zenith angles or moderate-to-high PE by diverging the beam to mitigate LAP fluctuations.},

keywords = {Atmospheric modeling, Drones, Fluctuations, Free-space optics (FSO), Global Positioning System, high-altitude platforms (HAPs), Laser beams, low-altitude platforms (LAPs), Optical beams, Optical reflection, Power distribution, quantum key distribution (QKD), reconfigurable intelligent surface (RIS), Reconfigurable Intelligent Surfaces, Satellites},

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{chien_improved_2025,

title = {Improved Differential Evolution for Enhancing the Aggregated Channel Estimation of RIS-Aided Cell-Free Massive MIMO},

author = {Trinh Van Chien and Nguyen Hoang Viet and Symeon Chatzinotas and Lajos Hanzo},

url = {https://ieeexplore.ieee.org/document/11080325},

doi = {10.1109/TVT.2025.3589240},

issn = {1939-9359},

year  = {2025},

date = {2025-01-01},

urldate = {2025-10-08},

journal = {IEEE Transactions on Vehicular Technology},

pages = {1–6},

abstract = {Cell-Free Massive multiple-input multiple-output (MIMO) systems are investigated with the support of a reconfigurable intelligent surface (RIS). The RIS phase shifts are designed for improved channel estimation in the presence of spatial correlation. Specifically, we formulate the channel estimate and estimation error expressions using linear minimum mean square error (LMMSE) estimation for the aggregated channels. An optimization problem is then formulated to minimize the average normalized mean square error (NMSE) subject to practical phase shift constraints. To circumvent the problem of inherent nonconvexity, we then conceive an enhanced version of the differential evolution algorithm that is capable of avoiding local minima by introducing an augmentation operator applied to some high-performing Diffential Evolution (DE) individuals. Numerical results indicate that our proposed algorithm can significantly improve the channel estimation quality of the state-of-the-art benchmarks.},

keywords = {Cell-free massive MIMO, Channel estimation, Closed-form solutions, Contamination, Correlation, differential evolution, Massive MIMO, Optimization, Rayleigh channels, reconfigurable intelligent surface, Reconfigurable Intelligent Surfaces, Training, Vectors},

pubstate = {published},

tppubtype = {article}

}

@article{li_indoor_2025,

title = {Indoor Localization and Tracking in Reconfigurable Intelligent Surface Aided mmWave Systems},

author = {Kunlun Li and Mohammed El-Hajjar and Chao Xu and Lajos Hanzo},

url = {https://ieeexplore.ieee.org/document/11050944},

doi = {10.1109/OJVT.2025.3582885},

issn = {2644-1330},

year  = {2025},

date = {2025-01-01},

urldate = {2025-10-08},

journal = {IEEE Open Journal of Vehicular Technology},

volume = {6},

pages = {1815–1831},

abstract = {Millimeter wave (mmWave) carriers have a high available bandwidth, which can be beneficial for high-resolution localization in both the angular and temporal domains. However, the limited coverage due to severe path loss and line-of-sight (LoS) blockage are considered to be major challenges in mmWave. A promising solution is to employ reconfigurable intelligent surfaces (RIS) to circumvent the lack of line-of-sight paths, which can assist in localization. Furthermore, radio localization and tracking are capable of accurate real-time monitoring of the UE's locations and trajectories. In this paper, we propose a three-stage indoor tracking scheme. In the first stage, channel sounding is harnessed in support of the transmitter beamforming and receiver combining design. Based on the estimation in the first stage, a simplified received signal model is obtained, while using a discrete Fourier transform (DFT) matrix for the configuration of the RIS phase shifter for each time block. Based on the simplified received signal model, tracking initialization is carried out. Finally, in the third stage, Kalman filtering is employed for tracking. Our results demonstrate that the proposed scheme is capable of improving both the accuracy and robustness of tracking compared to single-shot successive localization. Additionally, we derive the position error bounds (PEB) of single-shot localization.},

keywords = {Array signal processing, Channel estimation, Covariance matrices, Estimation, Kalman filters, localization/positioning, Location awareness, Millimeter wave communication, mmWave, OFDM, Radar tracking, Reconfigurable Intelligent Surfaces, sparse Bayesian learning, tracking},

pubstate = {published},

tppubtype = {article}

}

@article{singh_geometric_2025,

title = {Geometric Mean Rate Maximization in RIS-Aided mmWave ISAC Systems Relying on a Non-Diagonal Phase Shift Matrix},

author = {Jitendra Singh and Aditya K. Jagannatham and Lajos Hanzo},

url = {https://ieeexplore.ieee.org/document/11012749/similar},

doi = {10.1109/OJCOMS.2025.3573196},

issn = {2644-125X},

year  = {2025},

date = {2025-01-01},

urldate = {2025-10-08},

journal = {IEEE Open Journal of the Communications Society},

volume = {6},

pages = {4756–4771},

abstract = {The joint optimization of the hybrid transmit precoders (HTPCs) and reflective elements of a millimeter wave (mmWave) integrated sensing and communication (ISAC) system is considered. The system also incorporates a reconfigurable intelligent surface (RIS) relying on a non-diagonal RIS (NDRIS) phase shift matrix. Specifically, we consider a hybrid architecture at the ISAC base station (BS) that serves multiple downlink communication users (CUs) via the reflected links from the RIS, while concurrently detecting multiple radar targets (RTs). We formulate an optimization problem that aims for maximizing the geometric mean (GM) rate of the CUs, subject to the sensing requirement for each RT. Additional specifications related to the limited transmit power and unit modulus (UM) constraints for both the HTPCs and the reflective elements of the NDRIS phase shift matrix make the problem challenging. To solve this problem, we first transform the intractable GM rate expression to a tractable weighted sum rate objective and next split the transformed problem into sub-problems. Consequently, we propose an iterative alternating optimization approach that leverages the majorization-minimization (MM) framework and block coordinate descent (BCD) method to solve each sub-problem. Furthermore, to tackle the UM constraints in the sub-problem of the HTPC design, we propose a penalty-based Riemannian manifold optimization (PRMO) algorithm, which optimizes the HTPCs on the Riemannian manifold. Similarly, the phases of the reflective elements of the NDRIS are optimized by employing the Riemannian manifold, and the locations of the non-zero entries of the NDRIS phase shift matrix are obtained by the maximal ratio combining (MRC) criterion. Finally, we present our simulation results, which show that deploying an NDRIS achieves additional gains for the CUs over a conventional RIS, further enhancing both the communication efficiency and sensing reliability. Furthermore, we compare the results to the pertinent benchmarks, which validate the effectiveness of our proposed algorithms.},

keywords = {and geometric mean rate, Array signal processing, Base stations, Copper, Costs, Hardware, Integrated sensing and communication, millimeter wave, Millimeter wave communication, Optimization, Radio frequency, reconfigurable intelligent surface, Reconfigurable Intelligent Surfaces},

pubstate = {published},

tppubtype = {article}

}