arXiv subjects

Wali Ullah Khan

Publications and source records attributed to Wali Ullah Khan.

At least 19 recordsLinked to original sources

arXiv2026

Joint Average Contiguous Duration of Correlated Fading Envelopes

Average contiguous duration (ACD) measures the mean time for which a fading envelope remains continuously inside a bounded amplitude interval. This letter extends the concept to two correlated observations by introducing joint average contiguous duration (JACD) and joint average fade duration (JAFD). Both metrics are expressed as joint-region occupancy probabilities divided by the corresponding inward boundarycrossing rates. For correlated Rayleigh fading, closed-form JACD and JAFD expressions are derived using the bivariate Rayleigh cumulative distribution function (CDF), Rayleigh level-crossing rates, and conditional Rician probabilities. As an application, reciprocal secret-key generation (SKG) is considered through JACD-based multilevel quantization and raw key generation rate (KGR) expressions. Numerical results show that JACD-balanced quantization improves the worst-bin joint duration, same-bin occupancy, and sample-wise raw KGR compared with marginalACD balancing.

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arXiv2026

One-Shot Beam Tracking for Stacked Intelligent Metasurfaces-Assisted LEO Broadcasting

This letter develops a physics-informed one-shot beam tracking method for stacked intelligent metasurface (SIM)-enabled low-Earth-orbit (LEO) links with $K$ users and an $L$-layer SIM with $N$ meta-atoms per layer. The predictable orbital motion is propagated through the line-of-sight (LoS) geometry to forecast the finite-interval variation of the user signal-to-noise ratio (SNR) profile, and an analytical multilayer Jacobian relates this variation to the $LN$ SIM phase coefficients. Beam tracking is formulated as normalized SNR-profile preservation and solved through a single regularized Gauss--Newton correction that requires one Jacobian evaluation and a $K\times K$ linear solve, thereby avoiding iterative reoptimization. A tracking-error bound separates the regularization residual from the nonlinear Taylor remainder and establishes a second-order local error under a full-row-rank Jacobian. Numerical results show that the proposed method retains approximately $94\%$ and $92\%$ of the iterative-reoptimization rate for $L=2$ and $L=4$, respectively, while running about $350\times$ and $260\times$ faster at $N=225$, and confirm the predicted second-order residual error behavior.

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arXiv2026

Movable-Element STAR-RIS for 6G Non-Terrestrial Networks: Architectures, Enabling Technologies, and Open Challenges

Non-terrestrial networks (NTNs) are emerging as a key component of 6G systems by extending ubiquitous and resilient connectivity across satellite, aerial, and terrestrial layers. However, severe propagation loss, rapidly varying geometry, Doppler, blockage, and stringent payload and energy constraints make efficient beam and propagation control particularly challenging. Movable-element STAR-RIS (ME-STAR-RIS) offers a new approach by combining full-space transmission/reflection control with reconfigurable surface geometry, thereby introducing an additional spatial degree of freedom for geometry-aware NTN operation. In this article, we first describe the operating principle, movement constraints, and potential hardware realizations of ME-STAR-RIS, and then present representative satellite-borne, aerial-relay, and cross-tier NTN architectures. We discuss the key enabling mechanisms, including joint geometry--electromagnetic optimization, mobility-aware channel acquisition, multi-timescale control, and predictive configuration. A LEO-centered numerical case study compares ME-STAR-RIS with an otherwise identical fixed STAR-RIS and demonstrates the benefit of element mobility across different transmit powers, movement ranges, and surface sizes, while revealing diminishing returns from increasingly large displacements. Finally, we discuss the main hardware, CSI, scalability, near-field, sensing, security, reliability, and standardization challenges, and highlight promising directions toward practical ME-STAR-RIS-enabled NTNs

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arXiv2026

Movable-Element STAR-RIS for Integrated Sensing and Communication: Architectures, Opportunities, and Practical Challenges

Simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RISs) extend conventional reflecting-only surfaces by enabling controllable full-space propagation. Yet, once deployed, the physical locations of their elements remain fixed, leaving the surface geometry unable to adapt to users, sensing targets, blockage, or near-field focusing conditions. This article develops a system-level perspective on movable-element STAR-RIS (ME--STAR--RIS) for integrated sensing and communication (ISAC), where the surface jointly reconfigures its electromagnetic response and the physical positions of its elements. We explain how geometric reconfiguration can reshape the effective aperture, spatial correlation, interference nulls, and sensing illumination while preserving STAR-RIS full-space operation. A two-timescale control architecture separates relatively slow element motion from fast beamforming and transmission/reflection control. A 100-realization illustrative case study compares ME--STAR--RIS with an otherwise identical fixed STAR-RIS under a passive coupled transmission/reflection response. The results show a substantially improved sampled communication--sensing tradeoff and, importantly, a rapid saturation of the rate gain with modest element travel. We conclude with representative use cases, implementation constraints, and a research roadmap covering mobility overhead, channel acquisition, mutual coupling, near-field operation, hardware impairments, and learning-assisted predictive control.

cs.ET↗

arXiv2026

Movable-Element STAR-RIS for 6G: From Programmable Propagation to Programmable Geometry

Reconfigurable intelligent surfaces (RISs) make the wireless propagation environment programmable, while simultaneously transmitting and reflecting RISs (STAR-RISs) extend this capability to users located on both sides of a surface. However, conventional STAR-RIS architectures retain a fixed physical geometry after deployment. Movable-element STAR-RIS (ME-STAR-RIS) introduces an additional spatial degree of freedom by allowing the surface elements to reposition within prescribed regions while maintaining electronic control of their transmission and reflection responses. This combination of electromagnetic and geometric reconfiguration can alter propagation distances, multipath combinations, spatial correlation, interference, near-field focusing, and sensing geometry. This article presents a system-level perspective on ME-STAR-RIS through the concept of programmable geometry. We discuss its operating principles, movement architectures, and promising applications in communications, security, near-field systems, sensing, and high-mobility networks. A representative case study comparing optimized fixed and movable STAR-RIS architectures illustrates measurable spectral-efficiency gains from limited local displacement and the resulting saturation behavior. Finally, key hardware, channel-acquisition, electromagnetic, energy, reliability, and control challenges are discussed toward practical ME-STAR-RIS deployment.

cs.ET↗

arXiv2026

Battery-Aware Rate-Splitting Multiple Access for Solar-Powered Cell-Free LEO Satellite Networks

Cell-free low Earth orbit (LEO) satellite downlinks improve coverage and macro-diversity, but intermittent solar harvesting and finite onboard batteries can make communication-only resource allocation energy-aggressive. We develop battery-aware one-layer rate-splitting multiple access (BA-RSMA) for a fixed-cluster solar-powered cell-free LEO downlink. A perturbed physical-battery Lyapunov queue couples common/private power allocation to stored energy, while robust energy causality protects against bounded harvesting uncertainty and allows harvest curtailment at battery saturation. Under a fixed-precoder scalar effective-channel model, dual and quadratic transforms yield convex fixed-auxiliary resource-allocation subproblems and monotonic alternating updates. Numerical cross-validation against a direct nonlinear-programming reference gives a maximum relative objective gap below $2.8\times10^{-7}$ over 12 representative slot--state instances. In a 20-seed battery-stressed experiment, BA-RSMA achieves 1.631~Mbit/J and reduces mean near-depletion from 24.84\% under Myopic-RSMA to 6.82\%, at only a 1.7\% EE penalty.

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arXiv2026

Performance Analysis of RSMA-Enabled Bistatic ISAC in LEO Networks with Holographic Apertures and Fluid-Antenna Users

This paper develops an ergodic performance framework for rate-splitting multiple access (RSMA)-enabled bistatic integrated sensing and communication (ISAC) in a low-Earth-orbit (LEO) satellite network with an amplitude-constrained reconfigurable holographic surface (RHS) and fluid-antenna-system (FAS) users. Deterministic angle-based common and zero-forcing private reference beams are realized through one shared multi-feed RHS amplitude state and stream-specific feed-domain precoders, and the resulting self-, leakage-, and target-direction gains are retained explicitly. Conservative private- and common-rate lower bounds are derived for both reference-port and best-of-$P$ FAS reception while preserving the same-port selection coupling. For sensing, a closed-form average bistatic sensing signal-to-noise ratio (SNR) is obtained under nearest-receiver association and a finite target--receiver guard distance, with extensions to angle-conditioned footprint averaging and angular scheduling. Monte Carlo results confirm the tightness of the analytical rate bounds and validate the sensing expressions. Benchmarks show that scalar RHS-efficiency models can miss strong direction-dependent effects and that nearest-ground-receiver bistatic sensing provides a $17.7$--$25.7$~dB mean SNR advantage over a favorable monostatic LEO reference for $N_{\rm RHS}=16384$ over LEO altitudes of $400$--$1000$~km. FAS gains are largest in scattering-rich regimes, while the realized shared-state RHS target gain need not vary monotonically with aperture size.

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arXiv2026

Terahertz Inter-Satellite Links: Motivation, Challenges and Opportunities

Inter-satellite links (ISLs) are essential to the evolution of next-generation satellite constellations, providing the foundation for low-latency, resilient, and globally scalable connectivity. While low radio-frequency (RF)-based ISLs offer technological maturity, they are increasingly constrained by spectrum scarcity, congestion, and interference. Optical ISLs, on the other hand, deliver unprecedented capacity but demand ultra-precise pointing, suffer from narrow-beam limitations, and are limited to point-to-point links, all of which hinder large-scale deployment, including point-to-multi-point capability. To overcome these limitations, we propose very-high RF terahertz (THz) inter-satellite links (ISLs) as a promising middle-ground solution, merging the ultra-high data rates of optical links with the adaptability, reliability, and relaxed pointing requirements of lower-frequency RF ISLs. However, despite growing interest, research on THz ISLs remains at an early stage, fragmented across isolated studies, and lacking a clear roadmap for practical realization. This paper aims to address this gap by examining the fundamentals of THz ISLs, assessing their potential advantages and key challenges, and identifying the most promising research directions to transform them into a cornerstone of future interconnected mega constellations.

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arXiv2026

Transmissive RIS-Assisted Vehicular Direct-to-Satellite Communications: Opportunities, Limitations, and Comparison with Phased Arrays

This article studies transmissive reconfigurable intelligent surface (RIS)-assisted architectures. It compares them with electronically steered phased arrays for the deployment of vehicular direct-to-satellite (D2S) communications in future satellite networks. Rather than treating RIS as a direct replacement for phased arrays, we clarify the operating regimes in which RIS can serve as a low-power wavefront-shaping aperture and those in which phased arrays remain preferable because of their high gain and mature beam-tracking capability. Moreover, phased arrays can support multi-beam operation, which is particularly beneficial for dual connectivity and seamless handover. We distinguish analog, digital, and hybrid phased arrays, discuss the relationship between transmissive RIS and reconfigurable transmitarrays, and highlight practical profile, tracking, and link-budget constraints for mobile terminals. The comparison shows that passive RIS offers attractive power efficiency and aperture scalability, active RIS can partially improve the link budget, and phased arrays remain preferable for high-throughput.

cs.IT↗

arXiv2026

Energy Efficient Multi-User Beamforming and 3D Position Optimization for SIM-Assisted UAVs

This paper studies energy-efficient downlink multi-user transmissions with unmanned aerial vehicle (UAV) communication systems equipped with stacked intelligent metasurfaces (SIM), enabling wave-domain analog beamforming through multiple cascaded metasurface layers, while low-dimensional digital precoding is carried out using a limited number of transmit radio-frequency chains. This architecture enables flexible electromagnetic wave manipulation with reduced hardware complexity, making it particularly suitable for energy-constrained aerial platforms. We formulate a hardware-aware energy-efficiency (EE) maximization problem aiming to jointly optimize the digital precoder, the phase shifts of all SIM layers, and the three-dimensional UAV position under transmit-power, SIM operation, and UAV deployment constraints. The resulting problem is highly non-convex due to the fractional objective, the cascaded SIM structure and the unit-modulus phase constraints of the constituent metasurface layers, as well as the non-linear UAV-dependent channel. To address these challenges, we develop a transform-based alternating optimization framework that combines Dinkelbach's method, dual and quadratic transforms, to enable closed-form digital beamforming, Riemannian manifold optimization for SIM phase shifts, and successive convex approximation (SCA) for UAV positioning. Convergence and complexity analyses are provided to characterize the proposed algorithm. The presented numerical results showcase that the proposed joint design significantly improves EE compared with fully digital and maximum ratio transmission benchmark schemes, while revealing important design trade-offs among transmit power, SIM size, and the number of its constituent stacked layers.

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arXiv2026

Stacked Intelligent Metasurfaces Assisted UAV Communications

In this paper, we investigate an unmanned aerial vehicle (UAV) communication system assisted by stacked intelligent metasurfaces (SIMs), which enable programmable wave-domain signal processing through multiple cascaded metasurface layers. By shifting part of the beamforming functionality from the RF/digital domain to the electromagnetic domain, SIMs allow the realization of energy-efficient hybrid beamforming architectures suitable for aerial platforms. We formulate the joint design of digital precoding, SIM phase configuration, and UAV positioning for multi-user downlink sum-rate maximization. To solve the resulting non-convex problem, we develop an alternating optimization framework that guarantees monotonic improvement of the objective. Numerical results demonstrate that the proposed SIM-assisted architecture significantly improves spectral efficiency while maintaining low hardware complexity, and highlight the impact of the number of metasurface layers and size of each layer on system performance.

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arXiv2026

Adaptive UAV Communications for URLLC: From Preplanned Designs to Real-Time Intelligence

Unmanned aerial vehicles (UAVs) are emerging as a key enabler of next-generation wireless networks, particularly for applications that require ultra-reliable and low-latency communication (URLLC), such as emergency response, industrial automation, and autonomous systems. In these scenarios, maintaining reliable connectivity under strict transmission time constraints is challenging due to dynamic environments, mobility, and limited onboard energy. In particular, communication performance and energy are closely coupled with UAV movement, making trajectory design a critical component of system operation. Most existing approaches rely on offline joint communication and trajectory optimization, where the UAV trajectory and communication parameters are optimized prior to execution based on assumed system information. Although effective under ideal assumptions, such designs cannot adapt to real-time variations in user demand, channel conditions, or environmental disturbances, which are particularly critical in URLLC settings. To address these challenges, this article investigates model predictive control (MPC) as an adaptive framework for UAV-enabled communications. Using a receding-horizon strategy, MPC enables the UAV to continuously update its trajectory based on real-time information, improving reliability and robustness in dynamic environments. Representative application scenarios are discussed to highlight the role of MPC in UAV-enabled URLLC systems. Furthermore, a case study is presented to illustrate key design trade-offs and performance insights under finite blocklength-based URLLC transmission, followed by a discussion on open challenges and future research directions for practical and scalable MPC-enabled UAV communication systems.

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arXiv2026

Two-Stage Coded-Sliding Beam Training and QoS-Constrained Sum-Rate Maximization for SIM-Assisted Wireless Communications

Stacked intelligent metasurfaces (SIM) provide a cost-effective and scalable solution for large-scale antenna communications.However, efficient channel state information acquisition and phase shift optimization remain critical challenges. In this paper, we develop a unified framework of low-complexity algorithms for SIM-assisted communication systems to address these issues. Specifically, we propose a generalized two-step codebook construction (TSCC) method that leverages two-dimensional angular-domain decoupling to transform planar array beamformer design into two independent one-dimensional linear array beamformer design problems, efficiently solved via the Gerchberg-Saxton algorithm and our proposed majorization-minimization-based proximal distance (PDMM) algorithm. We further develop a two-stage coded-sliding beam training (TSCSBT) method for low-overhead and high-accuracy beam training, where error-correcting codes are embedded in the first-stage training to enhance robustness against noise, and sliding sampling is subsequently performed around the matched angular samples to improve angular resolution. The proposed framework is further extended to multi-path user channels. Finally, a variable decoupling-based block successive upper bound minimization (VD-BSUM) algorithm is proposed to directly solve the QoS-constrained sum-rate maximization problem through closed-form iterative updates with substantially reduced computational complexity. Simulation results demonstrate the effectiveness of the proposed methods in achieving precise beam pattern realization, improved beam training accuracy and angular resolution, and enhanced sum-rate performance.

cs.IT↗

arXiv2026

Online Model Predictive Control for Trajectory and Beamforming Optimization in UAV-Enabled URLLC

This paper investigates joint trajectory and active beamforming design for unmanned aerial vehicle (UAV)-enabled ultra-reliable low-latency communication (URLLC) systems under finite blocklength (FBL) transmission. Unlike conventional Shannon-capacity formulations, the FBL regime introduces a signal-to-interference-plus-noise ratio (SINR)-dependent dispersion penalty that increases the sensitivity of reliability to mobility-induced channel variations. To address this challenge, we develop a propulsion-aware model predictive control (MPC) framework that performs receding-horizon joint trajectory and multi-user beamforming optimization while enforcing FBL-based rate constraints. The resulting long-horizon nonconvex problem is decomposed into beamforming and trajectory subproblems using alternating optimization. Concave surrogate is constructed for the Shannon-capacity term, while convex approximations are derived for the dispersion term and the nonlinear propulsion power model, yielding tractable convex subproblems solved iteratively. Compared with an offline MPC baseline, where the predictive problem is solved once over the entire mission horizon without feedback updates, and a conventional offline trajectory-beamforming optimization, the proposed closed-loop framework achieves disturbance-resilient mission completion under UAV position disturbances. Simulation results show that, compared with maximum ratio transmission (MRT) and equal-power allocation, the proposed interference-aware design significantly improves URLLC reliability under stringent minimum rate constraints. The results also quantify the impact of antenna scaling, transmit power, and transmission time on FBL performance, providing insights for reliability-centric UAV-enabled wireless networks in 5G and beyond.

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arXiv2026

STAR Beyond Diagonal RISs with Amplification: Modeling and Optimization

This paper develops a physically consistent signal model with hardware constraints for a simultaneous transmitting and reflecting beyond-diagonal RIS (STAR BD-RIS) endowed with per-element amplification and lossless power splitting. We explicitly decouple (i) amplification via a diagonal gain matrix, (ii) element-wise reflection/transmission splitting, and (iii) passive beyond-diagonal coupling on each branch, while enforcing practical feasibility through per-element emission caps and an aggregate RIS power budget under the operating covariance. Building on this model, we cast downlink sum-rate maximization as an equivalent weighted minimum mean-square error (WMMSE) problem and propose an alternating optimization framework with provable monotonic descent. The method admits closed-form updates for MMSE combiners and weights, waterfilling-like beamformer updates via a single dual variable, a per-element amplification update that satisfies emission constraints, and a STAR power-splitting update based on cyclic coordinate descent with a global acceptance test. For the beyond-diagonal coupling matrices, we derive Riemannian gradient steps on the complex Stiefel manifold with QR/polar retraction method, preserving passivity at every iterate. Furthermore, the proposed approach decouples the optimization of the reflective and transmissive responses of the BD-RIS, enabling efficient distributed implementation. Numerical results demonstrate substantial sum-rate gains compared to the conventional passive BD-RIS.

cs.IT↗

arXiv2026

A Survey on Stacked Intelligent Metasurfaces: Fundamentals, Recent Advances, and Challenges

Reconfigurable intelligent surfaces (RISs) enable programmable control of wireless propagation. Beyond environmental deployments, integrating metasurfaces at the antenna front end allows direct manipulation of the radiated electromagnetic field and enables wave-domain signal processing. In this context, stacked intelligent metasurfaces (SIMs) have recently been proposed as an advanced architecture in which multiple programmable metasurface layers interact through wave propagation, enabling richer and more flexible electromagnetic transformations than conventional single-layer designs. By leveraging cascaded wave-matter interactions at the transmitter or receiver front end, SIMs substantially expand the design space of programmable wireless systems. This survey provides a comprehensive overview of SIMs technologies from the electromagnetic processing perspective, covering their physical principles, modeling frameworks, hardware realizations, and emerging architectural designs. We review existing modeling approaches based on cascaded operators, multiport impedance formulations, and network parameter representations, and discuss their implications for scalable optimization and system design. The survey further examines key communication functionalities enabled by front-end metasurface processing, including communication performance optimization, near-field and wideband transmission, learning-driven control, integrated sensing and communications, and emerging architectures such as cell-free and non-terrestrial networks. Finally, we identify open research problems related to physical modeling, scalability, hardware-algorithm co-design, and network integration, and outline promising directions toward realizing SIM-based antenna front ends as fully programmable electromagnetic processors for future sixth-generation (6G) wireless systems.

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arXiv2026

A Survey on STAR-RIS Enabled Joint Communications and Sensing: Fundamentals, Recent Advances and Research Challenges

The joint communications and sensing (JCAS) paradigm is envisioned as a core capability of sixth-generation (6G) wireless networks, enabling the integration of data communication and environmental sensing within a unified system. By reusing spectrum, waveforms, and hardware resources, JCAS improves spectral efficiency, reduces system complexity, and hardware cost, while enabling new use cases. Nevertheless, the realization of JCAS is hindered by inherent trade-offs between communication and sensing objectives, limited controllability of wireless propagation, and stringent hardware and design constraints. Simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RIS) have recently emerged as a promising technology to address these challenges by enabling full-space programmable manipulation of electromagnetic waves. This survey provides a systematic and in-depth review of STAR-RIS-enabled JCAS systems. Specifically, we first introduce the fundamental principles of JCAS and STAR-RIS. We then classify and review the state-of-the-art research on STAR-RIS-assisted JCAS from multiple perspectives, encompassing system architectures, waveform and beamforming design, resource allocation, optimization frameworks, and learning-based control. Finally, we identify key open challenges that remain unsolved and outline promising future research directions toward intelligent, flexible, and perceptive 6G wireless networks.

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arXiv2026

Resource Allocation and Sharing for UAV-Assisted Integrated TN-NTN with Multi-Connectivity

Unmanned aerial vehicles (UAVs) with multi-connectivity (MC) capabilities efficiently and reliably transfer data between terrestrial networks (TNs) and non-terrestrial networks (NTNs). However, optimally sharing and allocating spectrum and power resources to maintain MC while ensuring reliable connectivity and optimal performance remains challenging in such networks. Channel variations induced by mobility in UAV networks, coupled with the varying quality of service (QoS) demands of heterogeneous devices, resource sharing, and fairness requirements in capacity distribution pose challenges to optimal resource allocation. Thus, this paper investigates resource allocation for QoS-constrained, MC-enabled, dynamic UAVs in an integrated TN-NTN environment with spectrum sharing and fairness considerations. To this end, we consider three types of links: UAV-to-radio base station (RBS), UAV-to-UAV, and UAV-to-HAP. We also assume two types of UAVs with diverse QoS requirements to reflect a practical scenario. Consequently, we propose two algorithms. The first algorithm maximizes the capacity of UAVs-RBS and UAVs-HAP links while ensuring the reliability of the UAV-UAV link. To achieve this, the algorithm maximizes the collective throughput of the UAVs by optimizing the sum capacity of all the UAV-RBS and UAV-HAP links. Next, to provide constant capacity to all links and ensure fairness, we propose another algorithm that maximizes the minimum capacity across all links. We validate the performance of both algorithms through simulation

cs.NI↗