arXiv subjects

Thanh Luan Nguyen

Publications and source records attributed to Thanh Luan Nguyen.

12 recordsLinked to original sources

arXiv2026

Polyurethane Scintillators for High-Energy Physics Detectors: Optimization, Scale-up, and Radiation Response

Plastic scintillators remain attractive for large-area particle detectors because of their fast response, mechanical flexibility, and relatively simple fabrication. Motivated by future applications including the ALICE~3 Muon Identifier (MID) and the upgrade of the ALICE Fast Interaction Trigger (FIT), this work investigates polyurethane (PU)-based plastic scintillators doped with 2,5-diphenyloxazole (PPO) and 1,4-bis(5-phenyloxazol-2-yl)benzene (POPOP). Systematic information on the optimization and radiation response of this material system remains limited. A series of compositions was therefore fabricated and characterized using minimum-ionizing particles (MIP), optical spectroscopy, and time-correlated single-photon counting. The measurements show that the scintillation response is governed primarily by the PPO concentration, while POPOP mainly modifies the spectral response, and fast effective decay times of approximately 1.6--1.75~ns are maintained across the doped samples. The best-performing formulation was subsequently scaled to 20-$cm$ and 1-m scintillator bars and successfully operated with a single embedded wavelength-shifting fiber and SiPM readout, demonstrating its suitability for meter-scale light collection. Proton-irradiation measurements at the CERN IRRAD facility further revealed systematic degradation of the optical and scintillation responses with increasing exposure, together with substantial recovery after approximately two months. These results demonstrate that optimized PU--PPO--POPOP scintillators can combine fast timing, high light output, scalable detector geometry, and recoverable radiation response, supporting their further development for future large-area particle-detector systems.

physics.ins-det↗

arXiv2026

New Approximations of Non-Separable MIMO Channels by Separable Channels for Accurate Ergodic Capacity Analysis

In recent years, owing to the high accuracy in characterizing non-separable channels prevalent in next-generation wireless applications, the classical Weichselberger channel model has gained widespread adoption in multiple-input multiple-output (MIMO) systems. However, its non-separable structure also introduces severe analytical complexity, leading to a lack of tractable mathematical frameworks in the literature and thus raises an urgent need for further research. To address the aforementioned analytical complexity, we first derive the nearest separable (double-correlated Rayleigh) fading model to the Weichselberger model under the Kullback-Leibler divergence (KLD), a problem equivalent to rank-1 nonnegative matrix factorization under the Itakura-Saito (IS) distance criterion. The results of our asymptotic analysis in the high-SNR regime reveal that the KLD-enabled approximation achieves a tighter capacity estimate than the conventional Kronecker model, especially in sparse and non-regular scattering environments. Yet, a key limitation of the KLD-enabled model is its tendency to mischaracterize the channel capacity in the low-SNR regime due to its inability to preserve total channel power. As a more robust alternative, we introduce a novel moment matching method (MMM) aimed at mapping the exact channel statistics to those of a Wishart distribution. Both the KLD-enabled and MMM-enabled separable channel directly enable the use of exact closed-form expressions for the ergodic capacity. Numerical results demonstrate that the MMM-enabled model consistently improves upon the capacity accuracy of the conventional Kronecker model across all SNR regimes.

cs.IT↗

arXiv2025

Beyond Diagonal RIS for ISAC Network: Statistical Analysis and Network Parameter Estimation

This paper investigates the use of beyond diagonal reconfigurable intelligent surface (BD-RIS) with $N$ elements to advance integrated sensing and communication (ISAC). We address a key gap in the statistical characterizations of the radar signal-to-noise ratio (SNR) and the communication signal-to-interference-plus-noise ratio (SINR) by deriving tractable closed-form cumulative distribution functions (CDFs) for these metrics. Our approach maximizes the radar SNR by jointly configuring radar beamforming and BD-RIS phase shifts. Subsequently, zero-forcing is adopted to mitigate user interference, enhancing the communication SINR. To meet ISAC outage requirements, we propose an analytically-driven successive non-inversion sampling (SNIS) algorithm for estimating network parameters satisfying network outage constraints. Numerical results illustrate the accuracy of the derived CDFs and demonstrate the effectiveness of the proposed SNIS algorithm.

eess.SP↗

arXiv2024

Fluctuating Line-of-Sight Fading Distribution: Statistical Characterization and Applications

We introduce the fluctuating Line-of-Sight (fLoS) fading model, characterized by parameters $K$, $k$, $λ$, and $Ω$. The fLoS fading distribution is expressed in terms of the multivariate confluent hypergeometric functions $Ψ_2$, $Φ_3^{(n)}$, and $Φ_3 = Φ_3^{(2)}$ and encompasses well-known distributions, such as the Nakagami-$m$, Hoyt, Rice, and Rician shadowed fading distributions as special cases. An efficient method to numerically compute the fLoS fading distribution is also addressed. Notably, for a positive integer $k$, the fLoS fading distribution simplifies to a finite mixture of $κ$-$μ$ distributions. Additionally, we analyze the outage probability and Ergodic capacity, presenting a tailored Prony's approximation method for the latter. Numerical results are presented to show the impact of the fading parameters and verify the accuracy of the proposed approximation. Moreover, we illustrate an application of the proposed fLoS fading distribution for characterizing wireless systems affected by channel aging.

cs.IT↗

arXiv2024

Ground-to-UAV and RIS-assisted UAV-to-Ground Communication Under Channel Aging: Statistical Characterization and Outage Performance

This paper studies the statistical characterization of ground-to-air (G2A) and reconfigurable intelligent surface (RIS)-assisted air-to-ground (A2G) communications in RIS-assisted UAV networks under the impact of channel aging. A comprehensive channel model is presented, which incorporates the time-varying fading, three-dimensional (3D) mobility, Doppler shifts, and the effects of channel aging on array antenna structures. We provide analytical expressions for the G2A signal-to-noise ratio (SNR) probability density function (PDF) and cumulative distribution function (CDF), demonstrating that the G2A SNR follows a mixture of noncentral $χ^2$ distributions. The A2G communication is characterized under RIS arbitrary phase-shift configurations, showing that the A2G SNR can be represented as the product of two correlated noncentral $χ^2$ random variables (RVs). Additionally, we present the PDF and the CDF of the product of two independently distributed noncentral $χ^2$ RVs, which accurately characterize the A2G SNR's distribution. Our paper confirms the effectiveness of RISs in mitigating channel aging effects within the coherence time. Finally, we propose an adaptive spectral efficiency method that ensures consistent system performance and satisfactory outage levels when the UAV and the ground user equipments are in motion.

cs.IT↗

arXiv2024

Multi-IRS-aided Terahertz Networks: Channel Modelling and User Association With Imperfect CSI

Terahertz (THz) communication is envisioned as one of the candidate technologies for future wireless communications to enable achievable data rates of up to several terabits per second (Tbps). However, the high pathloss and molecular absorption in THz band communications often limit the transmission range. To overcome these limitations, this paper proposes intelligent reconfigurable surface (IRS)-aided THz networks with imperfect channel state information (CSI). Specifically, we present an angle-based trigonometric channel model to facilitate the performance evaluation of IRS-aided THz networks. In addition, to maximize the sum rate, we formulate the transmitter (Tx)-IRS-receiver (Rx) matching problem, which is a mixed-integer nonlinear programming (MINLP) problem. To address this non-deterministic polynomial-time hard (NP-hard) problem, we propose a Gale-Shapley algorithm-based solutions to obtain stable matching between transmitters and IRSs, and receivers and IRSs, in the first and second sub-problems, respectively. The impact of the transmission power, the number of IRS elements, and the network area on the sum rate are investigated. Furthermore, the proposed algorithm is compared to an exhaustive search, nearest association, greedy search, and random allocation to validate the proposed solution. The complexity and convergence analysis demonstrate that the computational complexity of our algorithm is lower than that of the ES method.

eess.SP↗

arXiv2024

Statistical Characterization of RIS-assisted UAV Communications in Terrestrial and Non-Terrestrial Networks Under Channel Aging

This paper studies the statistical characterization of ground-to-air (G2A) and reconfigurable intelligent surface (RIS)-assisted air-to-ground (A2G) communications with unmanned aerial vehicles (UAVs) in terrestrial and non-terrestrial networks under the impact of channel aging. We first model the G2A and A2G signal-to-noise ratios (SNRs) as non-central complex Gaussian quadratic random variables (RVs) and derive their exact probability density functions, offering a unique characterization for the A2G SNR as the product of two scaled non-central chi-square RVs. Moreover, we also find that, for a large number of RIS elements, the RIS-assisted A2G channel can be characterized as a single Rician fading channel. Our results reveal the presence of channel hardening in A2G communication under low UAV speeds, where we derive the maximum target spectral efficiency (SE) for a system to maintain a consistent required outage level. Meanwhile, high UAV speeds, exceeding 50 m/s, lead to a significant performance degradation, which cannot be mitigated by increasing the number of RIS elements.

eess.SP↗

arXiv2024

Channel Characterization of UAV-RIS-aided Systems with Adaptive Phase-shift Configuration

This letter considers a UAV aiding communication between a ground transmitter and a ground receiver in the presence of co-channel interference. A discrete-time Markov process is adopted to model the complex nature of the Air-to-Ground (A2G) channel, including the occurrence of Line-of-Sight, Non-Line-of-Sight, and blockage events. Moreover, an adaptive phase-shift-enabled Reconfigurable Intelligent Surface (RIS) is deployed to combat A2G blockage events. Novel frameworks based on the shadowed Rician distribution are proposed to derive closed-form expressions for Ground-to-Air/A2G SINR' distributions. Numerical results show that RISs with large numbers of elements, e.g., 256 RIS elements, improve end-to-end Outage Probability (OP) and reduce blockages.

eess.SP↗

arXiv2024

User Association Optimization for IRS-aided Terahertz Networks: A Matching Theory Approach

Terahertz (THz) communication is a promising technology for future wireless communications, offering data rates of up to several terabits-per-second (Tbps). However, the range of THz band communications is often limited by high pathloss and molecular absorption. To overcome these challenges, this paper proposes intelligent reconfigurable surfaces (IRSs) to enhance THz communication systems. Specifically, we introduce an angle-based trigonometric channel model to evaluate the effectiveness of IRS-aided THz networks. Additionally, to maximize the sum rate, we formulate the source-IRS-destination matching problem, which is a mixed-integer nonlinear programming (MINLP) problem. To solve this non-deterministic polynomial-time hard (NP-hard) problem, the paper proposes a Gale-Shapley-based solution that obtains stable matches between sources and IRSs, as well as between destinations and IRSs in the first and second sub-problems, respectively.

eess.SP↗

arXiv2023

Adaptive Decoding Mechanisms for UAV-enabled Double-Uplink Coordinated NOMA

In this paper, we propose a novel adaptive decoding mechanism (ADM) for the unmanned aerial vehicle (UAV)-enabled uplink (UL) non-orthogonal multiple access (NOMA) communications. Specifically, considering a harsh UAV environment, where ground-to-ground links are regularly unavailable, the proposed ADM overcomes the challenging problem of conventional UL-NOMA systems whose performance is sensitive to the transmitter's statistical channel state information and the receiver's decoding order. To evaluate the performance of the ADM, we derive closed-form expressions for the system outage probability (OP) and system throughput. In the performance analysis section, we provide novel expressions for practical air-to-ground and ground-to-air channels, while taking into account the practical implementation of imperfect successive interference cancellation (SIC) in UL-NOMA. Moreover, the obtained expression can be adopted to characterize the OP of various systems under a Mixture of Gamma (MG) distribution-based fading channels. Next, we propose a sub-optimal Gradient Descent-based algorithm to obtain the power allocation coefficients that result in maximum throughput with respect to each location on UAV's trajectory. To determine the significance of the proposed ADM in nonstationary environments, we consider the ground users and the UAV to move according to the Random Waypoint Mobility (RWM) and Reference Point Group Mobility (RPGM) models, respectively. Accurate formulas for the distance distributions are also provided. Numerical solutions demonstrate that the ADM-enhanced NOMA not only outperforms Orthogonal Multiple Access (OMA), but also improves the performance of UAV-enabled UL-NOMA even in mobile environments.

cs.IT↗

arXiv2021

Multi-RIS-aided Wireless Systems: Statistical Characterization and Performance Analysis

In this paper, we study the statistical characterization and modeling of distributed multi-reconfigurable intelligent surface (RIS)-aided wireless systems. Specifically, we consider a practical system model where the RISs with different geometric sizes are distributively deployed, and wireless channels associated to different RISs are assumed to be independent but not identically distributed (i.n.i.d.). We propose two purpose-oriented multi-RIS-aided schemes, namely, the exhaustive RIS-aided (ERA) and opportunistic RIS-aided (ORA) schemes. A mathematical framework, which relies on the method of moments, is proposed to statistically characterize the end-to-end (e2e) channels of these schemes. It is shown that either a Gamma distribution or a Log-Normal distribution can be used to approximate the distribution of the magnitude of the e2e channel coefficients in both schemes. With these findings, we evaluate the performance of the two schemes in terms of outage probability (OP) and ergodic capacity (EC), where tight approximate closed-form expressions for the OP and EC are derived. Representative results show that the ERA scheme outperforms the ORA scheme in terms of OP and EC. In addition, under i.n.i.d. fading channels, the reflecting element settings and location settings of RISs have a significant impact on the system performance of both the ERA or ORA schemes.

cs.IT↗

arXiv2021

Aerial Reconfigurable Intelligent Surface-Aided Wireless Communication Systems

In this paper, we propose and investigate an aerial reconfigurable intelligent surface (aerial-RIS)-aided wireless communication system. Specifically, considering practical composite fading channels, we characterize the air-to-ground (A2G) links by Namkagami-m small-scale fading and inverse-Gamma large-scale shadowing. To investigate the delay-limited performance of the proposed system, we derive a tight approximate closed-form expression for the end-to-end outage probability (OP). Next, considering a mobile environment, where performance analysis is intractable, we rely on machine learning-based performance prediction to evaluate the performance of the mobile aerial-RIS-aided system. Specifically, taking into account the three-dimensional (3D) spatial movement of the aerial-RIS, we build a deep neural network (DNN) to accurately predict the OP. We show that: (i) fading and shadowing conditions have strong impact on the OP, (ii) as the number of reflecting elements increases, aerial-RIS achieves higher energy efficiency (EE), and (iii) the aerial-RIS-aided system outperforms conventional relaying systems.

cs.IT↗