arXiv subjects

Noor Ul Ain

Publications and source records attributed to Noor Ul Ain.

6 recordsLinked to original sources

arXiv2026

Beyond the Use-and-then-Forget (UatF) Bound: Fixed Point Algorithms for Statistical Max-Min Power Control

We introduce mathematical tools and fixed point algorithms for optimal statistical max-min power control in cellular and cell-less massive MIMO systems. Unlike previous studies that rely on the use-and-then-forget (UatF) lower bound on Shannon achievable (ergodic) rates, our proposed framework can deal with alternative bounds that explicitly consider perfect or imperfect channel state information (CSI) at the decoder. In doing so, we address limitations of UatF-based power control algorithms, which inherit the shortcomings of the UatF bound. For example, the UatF bound can be overly conservative: in extreme cases, under fully statistical (nonadaptive) beamforming in zero-mean channels, the UatF bound produces trivial (zero) rate bounds. It also lacks scale invariance: a realization-dependent random scaling of the beamformers can change the bound drastically. In contrast, our framework is compatible with information-theoretic bounds that do not suffer from the above drawbacks. We illustrate the framework by solving a max-min power control problem considering a standard bound that exploits instantaneous CSI at the decoder.

eess.SP↗

arXiv2026

Z1 oscillations and charge state in electronic stopping power from first principles

The energy transfer rate from a projectile nucleus to the electrons of the matter it traverses depends on the charge of that projectile, Q= e Z1. At low projectile velocities the friction coefficient is known to oscillate with atomic number Z1, since core electrons travel with the projectile screening its charge. The effective charge increases with velocity and oscillations disappear. That effect is studied here calculating electronic stopping power from first principles for O and Mg projectiles shooting through bulk Al, using real-time time-dependent density-functional theory. Both projectiles represent maximum and minimum of the first Z1 oscillation, respectively. The oscillation is found to be very sensitive to the direction of propagation, in spite of Al being quite an ideal metal for many purposes. The critical velocity for the oscillation disappearance ranges between below 0.1 a.u. and beyond 1 a.u. for the explored trajectories. The charge state is independently quantified with Hirshfeld and Voronoi analyses, offering remarkably consistent results in spite of their very different partition methods, as well as with an effective definition based on the stopping power itself. They display a gradual undressing of the projectile's core electrons with increasing velocity in qualitative accordance with expectations. However, electron density plots in real space present a richer picture in which the undressing is partly due to the electrons trailing behind the projectile, suggesting possible phenomenological descriptions correcting for the deformation of the density in terms of multipoles beyond the net charge. The plots also offer insights into dissipation by core electrons.

cond-mat.mtrl-sci↗

arXiv2026

Performance Analysis of Cell-Free Massive MIMO under Imperfect LoS Phase Tracking

We study the impact of imperfect line-of-sight (LoS) phase tracking on the uplink performance of cell-free massive MIMO networks. Unlike prior works that assume perfectly known or completely unknown phases, we consider a realistic regime where LoS phases are estimated with residual uncertainty due to hardware impairments, mobility, and synchronization errors. To this end, we propose a Rician fading model where LoS components are rotated by imperfect phase estimates and attenuated by a deterministic \textit{phase-error penalty factor}. We derive a linear MMSE channel estimator that accounts for statistical phase errors and unifies prior results, reducing to the Bayesian MMSE estimator when phase is perfectly known and to a zero-mean model when no phase information is available. To address the non-Gaussian setting, we introduce a virtual uplink model that preserves second-order statistics of channel estimation, enabling the derivation of tractable virtual centralized and distributed MMSE beamformers. To ensure fair assessment of network performance, we apply these virtual beamformers to the operational uplink model that reflects the actual physical channel and compute the spectral efficiency bounds available in the literature. Numerical results show that our framework bridges idealized assumptions and practical tracking limitations, providing rigorous performance benchmarks and design insights for 6G cell-free networks.

cs.IT↗

arXiv2025

On the Optimal Performance of Distributed Cell-Free Massive MIMO with LoS Propagation

In this study, we revisit the performance analysis of distributed beamforming architectures in dense user-centric cell-free massive multiple-input multiple-output (mMIMO) systems in line-of-sight (LoS) scenarios. By incorporating a recently developed optimal distributed beamforming technique, called the team minimum mean square error (TMMSE) technique, we depart from previous studies that rely on suboptimal distributed beamforming approaches for LoS scenarios. Supported by extensive numerical simulations that follow 3GPP guidelines, we show that such suboptimal approaches may often lead to significant underestimation of the capabilities of distributed architectures, particularly in the presence of strong LoS paths. Considering the anticipated ultra-dense nature of cell-free mMIMO networks and the consequential high likelihood of strong LoS paths, our findings reveal that the team MMSE technique may significantly contribute in narrowing the performance gap between centralized and distributed architectures.

cs.IT↗

arXiv2024

QoS prediction in radio vehicular environments via prior user information

Reliable wireless communications play an important role in the automotive industry as it helps to enhance current use cases and enable new ones such as connected autonomous driving, platooning, cooperative maneuvering, teleoperated driving, and smart navigation. These and other use cases often rely on specific quality of service (QoS) levels for communication. Recently, the area of predictive quality of service (QoS) has received a great deal of attention as a key enabler to forecast communication quality well enough in advance. However, predicting QoS in a reliable manner is a notoriously difficult task. In this paper, we evaluate ML tree-ensemble methods to predict QoS in the range of minutes with data collected from a cellular test network. We discuss radio environment characteristics and we showcase how these can be used to improve ML performance and further support the uptake of ML in commercial networks. Specifically, we use the correlations of the measurements coming from the radio environment by including information of prior vehicles to enhance the prediction of the target vehicles. Moreover, we are extending prior art by showing how longer prediction horizons can be supported.

cs.LG↗

arXiv2015

Secure and authenticated quantum secret sharing

We propose here a quantum secret sharing scheme that works for both quantum and classical secrets. The proposed scheme is based on both entanglement swapping and teleportation together. It allows sender to encrypt his/her secret and simultaneously distribute decryption information of the encrypted secret among distant parties where decryption shares are nonlocally correlated with each other. Two-fold quantum non-local correlations, generated through entanglement swapping and then teleporting quantum states over swapped maximally entangled pairs, guarantee both authentication and secrecy of the secret from internal as well as external eavesdroppers. For classical secrets, we demonstrate a direct (2,2) quantum secret sharing scheme where neither pre-shared key nor physically secure quantum/classical channel are required. The same scheme turns out to be a (5,5) quantum secret sharing scheme for quantum secrets if sender and receivers have private quantum/classical channels among them.

quant-ph↗