arXiv subjects

George K. Karagiannidis

Publications and source records attributed to George K. Karagiannidis.

At least 19 recordsLinked to original sources

arXiv2026

Electromagnetic Modeling of Deformation-Based Pinching Antennas

Pinching-antenna systems (PAS) rely on local perturbations of a guiding structure to radiate part of the guided electromagnetic energy, making the physical response of the resulting pinching antenna (PA) fundamental to both guided-wave propagation and free-space radiation. To capture this coupled behavior, we develop an electromagnetic model of a finite deformation-based PA that directly relates the applied waveguide perturbation to its complex reflection and transmission responses and three-dimensional radiation characteristics. Full-wave MEEP simulations validate the model and demonstrate how the pinching ratio and pinched-section length jointly affect the transmitted power and phase, radiation power-fraction, and radiation pattern, thereby establishing PA geometry as a degree of freedom for controlling the radiation response. Importantly, this geometric dependence extends to communication performance, as the received signal-to-noise ratio (SNR) results reveal that neither minimizing the PA--user distance nor maximizing the radiation power-fraction necessarily yields the highest SNR, since the applied perturbation also determines the realized gain toward the user.

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arXiv2026

Optical ISAC with Single-Photon Avalanche Diode (SPAD) Arrays

Single-photon avalanche diode (SPAD) arrays offer photon-level sensitivity for sensing in optical integrated sensing and communication (O-ISAC). However, after each detection, a SPAD is blind for a dead time, which saturates the array at high received power. Existing O-ISAC analyses assume linear receivers and do not capture this effect. In this paper, we study ranging with a SPAD array in a monostatic O-ISAC system based on direct-current-biased optical orthogonal frequency-division multiplexing (DCO-OFDM). Sampling the array once per dead time, we model the number of pixels that detect a photon in each sampling interval as a binomial random variable whose success probability accounts for the intensity variation of the echo within a dead time. Based on this model, we derive the Cramér-Rao bound (CRB) for range estimation. We show that the SPAD count model of optical wireless communication, which assumes a constant photon rate over a dead time, causes a range bias that depends on the received power. Moreover, unlike for a linear photodiode, saturation degrades the ranging accuracy beyond a sensing-optimal transmit power. The rate-constrained operating point is then the larger of this power and the power needed for the target data rate. Numerical results validate the analysis against a continuous-time photon-counting simulation and show that the proposed model is needed for ranging.

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arXiv2026

Joint Probabilistic Shaping and Symbol-Level Precoding for Covert LEO Satellite Downlinks

The wide footprint of low-Earth-orbit (LEO) satellite downlinks exposes the mere occurrence of a transmission to any receiver within it. This paper studies covert multiuser LEO downlinks, where a passive warden at an unknown but fixed ground location accumulates observations as the satellite moves. We jointly optimize the precoding and the occurrence probabilities of the multiuser symbol combinations to provide covertness against such wardens. Each phase-shift keying (PSK) symbol vector is decomposed into a relative pattern and a common rotation, so that shaping the pattern probabilities leaves the symbols of every legitimate user uniformly distributed. We develop probabilistically shaped symbol-level precoding and probabilistically shaped block-level precoding. We derive the exact chi-square divergence of the warden's Gaussian-mixture observation over the complete session and, by bounding the leakage over a continuous location uncertainty region, obtain certificates that guarantee covertness throughout that region. The certified covertness level is minimized under robust constructive-interference, power, and entropy constraints through an alternating optimization whose updates are equivalent to convex conic problems, and the optimized probabilities follow a Maxwell--Boltzmann-type law. Numerical results show that shaping substantially reduces the certified covertness level of both precoding structures, particularly under large location uncertainty, low elevation, and scarce power.

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arXiv2026

Age of Trust (AoT): A Continuous Verification Framework for Wireless Networks

Zero Trust is a new security vision for 6G networks that emphasises the philosophy of never trust and always verify. However, there is a fundamental trade-off between the wireless transmission efficiency and the trust level, which is reflected by the verification interval and its adaptation strategy. More importantly, the mathematical framework to characterise the trust level of the adaptive verification strategy is still missing. Inspired by this vision, we propose a concept called age of trust (AoT) to capture the characteristics of the trust level degrading over time, with the definition of the time elapsed since the last verification of the target user's trust plus the initial age, which depends on the trust level evaluated at that verification. The higher the trust level, the lower the initial age. To evaluate the trust level in the long term, the average AoT is used. We then investigate how to find a compromise between average AoT and wireless transmission efficiency with limited resources. In particular, we address the bi-objective optimization (BOO) problem between average AoT and throughput over a single link with arbitrary service process, where the identity of the receiver is constantly verified, and we devise a periodic verification scheme and a Q-learning-based scheme for constant process and random process, respectively. We also tackle the BOO problem in a multiple random access scenario, where a trust-enhanced frame-slotted ALOHA is designed. Finally, the numerical results show that our proposals can achieve a fair compromise between trust level and wireless transmission efficiency, and thus have a wide application prospect in various zero-trust architectures.

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arXiv2026

Secure Near-Field ISAC with Pinching-Antenna Systems: Exploiting Constructive-Destructive Interference

This paper investigates secure near-field integrated sensing and communication (ISAC) with pinching-antenna systems (PASS), where a base station serves legitimate users while localizing a target that may also eavesdrop on the transmitted data. We jointly design symbol-level precoding (SLP) and the transmit and receive pinching-antenna positions to minimize the Cartesian position error bound (PEB) averaged over the data symbols. Constructive interference ensures reliable reception at the legitimate users, whereas destructive interference drives the target's observation toward incorrect symbol regions without sacrificing the illumination required for sensing. We derive the PEB for unknown complex target reflectivity and establish an exact factorization into transmit-illumination and receive-geometry terms. This decomposition reveals the distinct sensing roles of the two apertures, enables separate receive-placement and joint transmit-placement/SLP optimization, and provides analytical insights into local position identifiability, the range-information limitations of compact arrays, sensing-oriented receive placement, and in-waveguide attenuation. Building on these results, we develop an efficient algorithm by combining geometry-informed receive initialization, one-dimensional transmit-position searches, and convex per-symbol precoding. Numerical results demonstrate sub-millimeter localization, erroneous symbol decisions at the target, an expanded feasible operating region, and substantial gains over fixed-placement PASS and fully digital extremely large-scale MIMO (XL-MIMO) benchmarks.

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arXiv2026

Pinching Antenna-Assisted Full-Duplex Communication Systems

Full-duplex (FD) communication theoretically doubles spectral efficiency. Despite this potential, its practical performance is primarily constrained by severe self-interference (SI) and co-channel interference. Moreover, conventional fixed antenna arrays suffer from limited spatial flexibility, resulting in insufficient spatial isolation for SI suppression. To address this issue, this letter proposes an FD architecture assisted by pinching antenna systems (PASS). By dynamically adjusting transmit and receive antenna positions, the system enables large-scale channel reconfiguration, thereby synergizing with the base station (BS) beamforming to suppress SI and enhance the desired signal reception. To demonstrate the potential of PASS for FD communication, we formulate a weighted sum-rate maximization problem that jointly optimizes antenna positions, BS beamforming, and power allocation. To tackle this non-convex problem, we reformulate it using the weighted minimum mean square error (WMMSE) framework and develop an efficient alternating optimization (AO) algorithm to iteratively update the optimization variables. Simulation results reveal that the proposed PASS-assisted FD architecture significantly outperforms conventional fixed antenna arrays, achieving substantial sum-rate gains while effectively mitigating SI to enable FD operation.

cs.IT↗

arXiv2026

Secure ISAC with Sensing Privacy under Eavesdropper Uncertainty

This paper investigates the joint protection of confidential data and legitimate-user directional information in integrated sensing and communication (ISAC) networks. We consider a multiuser downlink in which passive multi-antenna eavesdroppers (Eves) attempt to decode confidential signals while exploiting legitimate-user reflections for unauthorized angular sensing. To address both threats, we develop a robust covariance-design framework that jointly limits Eve decoding, maintains the transmitter's accuracy in estimating the Eves' directions and shifts the dominant passive-sensing response toward prescribed deceptive directions. A Bayesian angular prior and the corresponding Bayesian Cramer-Rao bound (BCRB) characterize the transmitter's eavesdropper-angle estimation accuracy. Angular uncertainty is represented through geometry-consistent samples, such that each candidate Eve direction jointly determines the corresponding transmitter-Eve channel, user-Eve bearing, and deceptive direction. The resulting design balances worst-user secrecy, sensing accuracy, sensing privacy, and deception power. Robust Eve-decoding constraints are handled through finite sufficient conditions with intersample margins, while continuous ghost dominance is enforced using interval sum-of-squares (SOS) constraints. The resulting nonconvex problem is addressed through successive convex approximation (SCA) and semidefinite relaxation. Numerical results show that the proposed design effectively preserves secrecy and sensing privacy under Eve-angle uncertainty, provides controlled angular deception in single- and multiple-Eve scenarios, and outperforms benchmarks.

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arXiv2026

A Survey of Pinching-Antenna Systems (PASS)

The pinching-antenna system (PASS), recently proposed as a flexible-antenna technology, has been regarded as a promising solution for several challenges in next-generation wireless networks. It provides large-scale antenna reconfiguration, establishes stable line-of-sight links, mitigates signal blockage, and exploits near-field advantages through its distinctive architecture. This article aims to present a comprehensive overview of the state of the art in PASS. The fundamental principles of PASS are first discussed, including its hardware architecture, circuit and physical models, and signal models. Several emerging PASS designs, such as segmented waveguide-enabled PASS (SWAN), center-fed PASS (C-PASS), and multi-mode PASS (M-PASS), are subsequently introduced, and their design features are discussed. In addition, the properties and promising applications of PASS for wireless sensing are reviewed. On this basis, recent progress in the performance analysis of PASS for both communications and sensing is surveyed, and the performance gains achieved by PASS are highlighted. Existing research contributions in optimization and machine learning are also summarized, with the practical challenges of beamforming and resource allocation being identified in relation to the unique transmission structure and propagation characteristics of PASS. Finally, several variants of PASS are presented, and key implementation challenges that remain open for future study are discussed.

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arXiv2026

Curved Waveguide-Enabled Pinching-Antenna System (C-PAS): Communication Performance Analysis

Existing studies on the pinching-antenna system (PAS) assume that waveguides are deployed straight, which fails to serve communication regions with curved boundaries. To address this limitation, this paper proposes a curved waveguide-enabled pinching-antenna system (C-PAS), where the waveguide is placed along the building ceiling in an arc to maximize the line-of-sight (LoS) coverage. On this basis, the optimal pinching-antenna (PA) placement strategy and the nearest PA placement strategy are presented. The optimal strategy distinguishes between scenarios, i.e., with or without inner-wall blockage, and derives a closed-form solution for the optimal PA position to maximize the signal-to-noise ratio (SNR) received at the user. Meanwhile, the nearest strategy aligns the PA with the angular position of a user in polar coordinates, thereby accommodating the curved geometry of the region. Furthermore, the outage probability (OP) and the average rate (AR) are analyzed for each strategy, and the corresponding analytical expressions are derived, respectively. The results show that the optimal PA placement strategy achieves better OP and AR performance than the nearest strategy, particularly under large waveguide loss coefficient or waveguide height. Moreover, for a service region of fixed area, there exists an optimal sector angle or inner-wall radius that either minimizes the outage probability or maximizes the average rate. Furthermore, the choice of a waveguide bending radius is influenced by the transmit power of the base station, where a smaller bending radius is preferable at high power and the middle arc performs best at low power.

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arXiv2026

Electromagnetic Twin: Completing the Wireless World from Sparse Channel Evidence

Acquiring dense channel information over many locations and beams incurs considerable pilot and processing overhead. Radio maps and channel knowledge maps (CKMs) reduce this overhead by reusing site-specific channel information, but their contents must be refreshed when new measurements or environmental observations become available. This paper introduces an \emph{electromagnetic twin} as an updatable digital representation that uses sparse channel evidence to reconstruct the wireless state requested by communication queries. Rather than replacing radio maps or CKMs, the twin uses a CKM as channel memory, combines it with registered scene information, and regenerates its outputs after each evidence update. We instantiate this idea by completing a two-dimensional channel-gain field from sparse samples and an incomplete floor plan. A learned RF completion backbone recovers the main propagation structure, and a lightweight residual adapter tests whether frozen CLIP features provide useful side information. With $4\%$ measured locations and $55\%$ missing semantic objects, the RF backbone attains $4.44$ dB RMSE, compared with $8.29$ dB for CKM interpolation and $8.38$ dB for an incomplete physics prior. Residual adaptation reduces RMSE by a paired mean of $0.135$ dB (95\% confidence interval: $0.100$--$0.169$ dB), but a same-capacity random-feature control is statistically indistinguishable from the CLIP-conditioned adapter. The results therefore support the measurement--update--query loop and lightweight residual correction, while avoiding an unsupported attribution of the correction to visual semantics.

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arXiv2026

Toward Intelligent Skies: Signal Processing and AI Foundations of Low-Altitude Wireless Networks

The rapid growth of low-altitude aerial services and applications, driven by uncrewed aerial vehicles (UAVs), calls for a new class of digital infrastructure beyond conventional terrestrial networks. The low-altitude wireless network (LAWN) has been proposed as dynamically reconfigurable three-dimensional architectures that integrate aerial and ground nodes to provide connectivity, sensing, and control in open, safety-critical airspace. This tutorial presents a comprehensive treatment of LAWNs from the joint perspectives of artificial intelligence (AI) and signal processing. We first review the historical evolution and architectural foundations of LAWNs, introducing altitude-based layers and functional planes, and summarizing the regulatory and standardization landscape. Building on this system view, we then discuss signal processing fundamentals for LAWNs, including 3D channel and system models, performance metrics, waveform and receiver design, localization and tracking, and multi-functionality co-design. Next, we survey AI techniques for LAWNs, covering discriminative and generative models for perception, control, resource management, and security, as well as emerging paradigms such as foundation models, large language models, and digital twins for mission planning and closed-loop optimization. To illustrate AI-signal processing integration in practice, we provide a case study of an AI-driven multi-tier LAWN with hybrid satellite, high-altitude, and ground nodes. The tutorial concludes by outlining key research challenges in architecture design, signal processing-AI co-design, safety and security, experimentation, and standardization, and by highlighting opportunities for LAWNs to evolve into dependable, AI-native infrastructure for the intelligent skies.

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arXiv2026

Integrated Localization, Mapping, and Communication through VCSEL-Based Light-emitting RIS (LeRIS)

Light-emitting reconfigurable intelligent surfaces (LeRISs) have recently emerged as a promising solution for providing the spatial awareness required for reliable millimeter-wave (mmWave) communication in programmable wireless environments (PWEs). However, existing LeRIS designs rely on the diffuse emission of light-emitting diodes, while LiDAR-assisted solutions require dedicated sensing modules that hinder their direct integration into RIS panels. In this paper, a vertical-cavity surface-emitting laser (VCSEL)-based LeRIS framework is developed to jointly support user localization, obstacle-aware mapping, and mmWave communication. Specifically, the narrow Gaussian beams and multimode operation of VCSELs are exploited to derive closed-form schemes for the joint recovery of the user position and orientation from received signal strength measurements. According to the provided simulation results, is shown that five VCSELs are sufficient for unique recovery, while this requirement is reduced to three dual-mode VCSELs under specific geometric conditions. Furthermore, the position error bound (PEB) is derived to characterize the achievable localization accuracy, while reflected-signal time-of-arrival measurements are employed to identify obstructed links and enable blockage-resilient LeRIS routing. As a result, the proposed framework achieves cm-level localization accuracy, reliable obstacle detection, and substantial spectral-efficiency and minimum-user-rate gains, thereby establishing VCSEL-based LeRISs as a solution for spatially aware and resilient PWEs.

cs.IT↗

arXiv2026

Breaking Network Densification Limits with Distributed Cooperative Massive Access (DCMA)

In this work, we investigate the performance of the distributed cooperative massive access (DCMA) framework in large-scale network setups by incorporating stochastic geometry modeling. A partially centralized cell-free cloud-radio access (C-RAN) architecture is considered where remote radio heads (RRHs) decode transmitted messages and cooperate with each other to enhance system performance. Specifically, they can share decoded messages via feedback links, allowing receivers to cancel inter-user interference through successive interference cancellation (SIC), thus improving the decoding capabilities of the system. For such a network, we propose a novel synergetic decoding algorithm that efficiently resolves the assignment and message sharing routing for each user while accounting for practical network constraints. Furthermore, using game theory, we develop a merge-and-split algorithm with lexicographic preference to solve the problem of minimizing the RRHs utilized without compromising the performance. Simulation results show that the proposed framework significantly outperforms systems that do not implement SIC or take advantage of the cooperation between RRHs in terms of outage probability. Finally, we evaluate the performance of the proposed algorithms and validate their efficiency.

cs.GT↗

arXiv2026

Fronthaul-Efficient Distributed Cooperative 3D Positioning with Quantized Latent CSI Embeddings

High-precision three-dimensional (3D) positioning in dense urban non-line-of-sight (NLOS) environments benefits significantly from cooperation among multiple distributed base stations (BSs). However, forwarding raw CSI from multiple BSs to a central unit (CU) incurs prohibitive fronthaul overhead, which limits scalable cooperative positioning in practice. This paper proposes a learning-based edge-cloud cooperative positioning framework under limited-capacity fronthaul constraints. In the proposed architecture, a neural network is deployed at each BS to compress the locally estimated CSI into a quantized representation subject to a fixed fronthaul payload. The quantized CSI is transmitted to the CU, which performs cooperative 3D positioning by jointly processing the compressed CSI received from multiple BSs. The proposed framework adopts a two-stage training strategy consisting of self-supervised local training at the BSs and end-to-end joint training for positioning at the CU. Simulation results based on a 3.5~GHz 5G NR compliant urban ray-tracing scenario with six BSs and 20~MHz bandwidth show that the proposed method achieves a mean 3D positioning error of 0.48~m and a 90th-percentile error of 0.83~m, while reducing the fronthaul payload to 6.25% of lossless CSI forwarding. The achieved performance is close to that of cooperative positioning with full CSI exchange.

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arXiv2026

Elliptic Range-Doppler Mapping for OFDM-ISAC under IQ Imbalance

Receiver in-phase/quadrature imbalance (IQI) couples each OFDM subcarrier with its mirror counterpart, creating ghost targets and degrading range-Doppler recovery in orthogonal frequency division multiplexing (OFDM) integrated sensing and communication (ISAC). Instead of first compensating for IQI and then applying conventional processing, this letter exploits the structure of the IQI-impaired observation directly. We show that each physical target induces coupled direct and mirror components linked through the target coefficient and its conjugate, which motivates an elliptic atom group representation for each candidate delay-Doppler cell. Based on this model, we propose an elliptic group orthogonal matching pursuit detector that performs sparse recovery directly on the received OFDM grid. The required correlations are computed efficiently through two weighted two-dimensional fast Fourier transforms (FFTs) followed by local group projections. Numerical results show that the proposed method improves exact support recovery and weak-target detection compared to corresponding benchmarks, especially under moderate and strong receiver IQI.

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arXiv2026

Jacobi Elliptic Chirps for Sub-Nyquist Multi-Target Ranging

Sub-Nyquist sampling is an attractive way to reduce the hardware cost of wideband pulse-compression radar, but it introduces coherent alias-induced replicas in the matched-filter range profile, producing spurious peaks known as ghost targets. Existing frequency-modulated waveforms face a practical trade-off in this regime: linear frequency-modulated (LFM) pulses provide compact range responses but are highly susceptible to ghost-target detections, whereas hyperbolic frequency-modulated (HFM) pulses suppress ghosts at the cost of degraded target separability. To overcome this trade-off, we propose a sine-over-cosine Jacobi elliptic frequency-modulated waveform, referred to as SC-EFM, in which the elliptic modulus tunes the instantaneous-frequency (IF) curvature while preserving the pulse duration and bandwidth of conventional benchmarks. We characterize the sub-Nyquist folding structure of SC-EFM and derive closed-form expressions for the multi-target and ghost-target detection probabilities. Numerical results show that SC-EFM significantly suppresses ghost detections relative to LFM while matching its target separability, and substantially outperforms HFM in resolving close targets, providing a unified waveform solution for ghost-resilient sub-Nyquist multi-target ranging.

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arXiv2026

Non-Uniform Codebook Design for Optical IRS-Assisted VLC Systems

Optical intelligent reflecting surfaces (OIRS) can improve the coverage of indoor visible light communication (VLC) systems, however, practical deployment requires a finite offline codebook to avoid repeated real-time optimisation of mirror orientations. A uniform codebook with fixed angular steps does not provide uniform coverage on the user plane, because the mapping from steering angles to reflection locations on the user plane is nonlinear. To address this problem, this paper proposes a geometric-optics-based non-uniform codebook design for OIRS-assisted VLC systems. The proposed method constructs an individual codebook for each IRS element according to its geometric position, so that the reflected beams are distributed more uniformly over the user plane. The codebook accuracy is evaluated using the Frobenius norm of the channel error matrix. Simulation results show that the proposed design provides more uniform spatial mapping with fewer codewords than the uniform codebook, and that the sweep-angle resolution has a stronger effect on the codebook accuracy than the tilt-angle resolution.

cs.IT↗

arXiv2026

Weighted Sum-Rate Enhancement for Flexible Intelligent Metasurface-Assisted Multicell Systems

Flexible intelligent metasurface (FIM) technology has emerged as a promising technology for enhancing wireless communication performance by dynamically reshaping the propagation environment. Compared with conventional rigid reconfigurable intelligent surfaces (RIS), an FIM is composed of multiple electromagnetic (EM) scattering units, each of which can flexibly modify its displacement in the direction normal to the surface, thereby cooperatively morphing the overall surface shape. This additional degree of freedom (DoF) enables improved beamforming and interference mitigation, particularly in complex multicell scenarios. In this paper, an optimization problem for maximizing the weighted sum-rate (WSR) in a multicell multi-user multiple-input single-output (MU-MISO) system assisted by an FIM deployed at the cell boundary is investigated. We jointly optimize the transmit beamforming at the base station (BS), the phase shift matrix, and the FIM surface shape, subject to constraints on the transmit power budget, unit-modulus reflection coefficients, and surface shape morphing range. Due to the non-convex objective function with highly coupled variables, solving the formulated optimization problem is challenging. To tackle this challenge, we propose an efficient alternating optimization framework that leverages the weighted minimum mean square error (WMMSE) method to reformulate the problem and the block coordinate descent (BCD) algorithm to iteratively update the variables. Specifically, the Riemannian conjugate gradient (RCG) algorithm is leveraged to optimize the phase shift matrix, while the projected gradient descent (PGD) method is adopted to optimize the surface shape of the FIM. Additionally, the optimal beamforming vectors are obtained in closed form.

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