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Michail Matthaiou

Publications and source records attributed to Michail Matthaiou.

At least 19 recordsLinked to original sources
arXiv2026

Distributed Pinching-Antenna Architecture for Communication and Target Positioning

We propose a pinching-antenna system (PASS)-assisted integrated sensing and communication (ISAC) framework for joint downlink communication and target positioning. The dielectric waveguides enable flexible signal radiation through activated pinching antennas (PAs), while the reflected echo signals are collected by a sensing receiver. A unified waveform is adopted to support both data transmission and sensing-echo processing. In particular, a two-stage procedure is developed for target localization using time-sum-of-arrival (TSoA) measurements, where the signal propagation distances are first estimated through de-chirp processing and beat frequency extraction. Then, the target position is obtained based on TSoA measurements using the weighted linear least squares(WLLS) technique. To characterize the fundamental limits of the PASS-assisted ISAC system, a Cramér-Rao lower bound (CRB) is derived, which captures the impact of PA activation. Furthermore, the PA activation problem is formulated to jointly optimize the communication spectral efficiency (SE) and sensing performance. To address this, a low-complexity heuristic greedy selection algorithm is proposed to determine the activated PA pattern. Numerical results demonstrate that the proposed scheme outperforms random PA selection, achieving gains of up to 81% improvement in communication SE.

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arXiv2026

Analysis and Antenna Position Selection for Pinching-Antenna Systems in Fading Channels

Pinching-antenna systems (PASSs) are an emerging flexible antenna technology that enables the creation of line-of-sight (LoS) links by repositioning a radiating element along a dielectric waveguide (WG). Most existing studies of PASSs assume a purely LoS environment, despite the fact that many practical wireless environments exhibit scattering and spatially correlated shadow fading. In this paper, we present the first statistical analysis of PASS performance under Ricean fading with spatially correlated large-scale fading. Focusing on a fundamental single-user uplink PASS, we characterize the distribution and mean of the maximum achievable signal-to-noise ratio (SNR). For the classical exponentially correlated shadow fading scenario, we express the channel power process in terms of Brownian motion and derive highly accurate approximations for the maximum SNR distribution and mean. For a general class of smoothly correlated shadow fading processes, we derive an accurate expression for the SNR distribution by modeling the process in terms of the fade sojourn duration. To address the challenges of antenna position selection in fading environments, we propose radio environment map (REM)-based positioning strategies, including opportunistic random-look and grid-based constructions. Analytical results are validated by simulation, and the impacts of key system parameters, such as the Ricean $K$-factor, spatial correlation, WG length, and carrier frequency are investigated. The results provide insights into PASS operation beyond idealized LoS conditions and establish a general analytical framework for performance evaluation and antenna positioning in scattered environments.

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arXiv2026

A Multi-Scenario UAV RF Dataset with Real-World Acquisition and Signal Processing Benchmarking

We present a real-world multi-scenario unmanned aerial vehicle (UAV) radio frequency (RF) dataset, namely DRFF-R2, which is collected using a dedicated acquisition platform under diverse operational conditions. All signals are acquired within a unified framework to ensure consistency in hardware configuration and environmental settings. The dataset is systematically organized into seven well-defined subsets corresponding to different operational and signal composition scenarios to facilitate structured experimentation. Each file follows a clearly annotated naming convention to enable convenient data indexing and reproducible analysis. The dataset contains RF recordings from 26 UAV units spanning 8 distinct models, captured across varying flight states, altitudes, speeds, acquisition days, and receiver configurations. By covering diverse acquisition settings and signal compositions, the dataset provides a comprehensive resource for future UAV RF signal research, including RF fingerprinting (RFF) identification, model-level recognition, flight state analysis, time-varying RFF study, and interference-aware signal processing.

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arXiv2026

Tri-Hybrid SWIPT with Reconfigurable Parasitic Antennas

We propose a coupling-aware tri-hybrid precoding architecture for simultaneous wireless information and power transfer (SWIPT) using reconfigurable parasitic antennas. By integrating multiport network theory and information theory, we develop a third precoding layer that explicitly accounts for mutual coupling and reactive energy storage within the antenna domain. To efficiently optimize this architecture, we propose a low-complexity tri-hybrid solution comprising coordinate descent (CD) for parasitic reactive load optimization, a singular value decomposition (SVD)-based analog precoder, and a protective partial zero-forcing (PPZF) digital precoder. Numerical results demonstrate that the transmit array introduces impedance mismatch that reduces the real power accepted by the antenna array. Moreover, the proposed tri-hybrid architecture significantly outperforms hybrid precoding by constructively exploiting the coupling effects, yielding substantial gains in spectral efficiency (SE) and sum non-linear harvested energy (NLHE) at a fraction of the hardware cost.

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arXiv2026

LUNA: Luneburg-Lens-Aided Reconfigurable Array for 6G-and-Advanced Wireless Networks

This article introduces the LUneburg-lens-aided recoNfigurable Array (LUNA), an antenna architecture that unifies multiple-input multiple-output (MIMO) and network-controlled repeater (NCR) functionalities in the Luneburg lens-enabled hardware platform. A Luneburg lens, fabricated from graded-index dielectric materials, passively converts the radiation of a low-gain feed into a highly directional beam without active phase shifting, while a dense passive feed bank and a reconfigurable feed-selection network electronically switch the beam directions with minimal hardware complexity and power consumption. We commence by reviewing the basic principles and application history of Luneburg lenses in radar and wireless communications, which motivates their role in 6G-and-advanced networks. Then, we highlight how a Luneburg lens and a reconfigurable feed array construct both LUNA-MIMO and LUNA-NCR, where the lens and feed bank can be reused across functions and frequency bands. Case studies demonstrate that LUNA achieves the satisfactory spectral and energy efficiency with a few radio-frequency chains, and it also improves positioning performance for sensing tasks. Finally, some open problems and research directions are provided to inspire follow-up research on LUNA.

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arXiv2026

Tri-Hybrid Beamforming Design for DMA-Aided Secure ISAC Systems

This paper proposes a tri-hybrid beamforming scheme for secure integrated sensing and communication (ISAC) with a dynamic metasurface antenna (DMA) architecture, where the base station (BS) is capable of communicating with legitimate users and sensing the target. There is also an eavesdropper in the system intending to eavesdrop on the confidential information. The tri-hybrid beamforming design problem is formulated with the objective of maximizing the sensing signal-to-noise ratio (SNR) under the constraints of secrecy spectral efficiency (SSE), transmit power, and physical structure limitations. We first solve the problem and obtain the optimized fully-digital beamforming solution through successive convex approximation (SCA) and semidefinite relaxation (SDR) approaches. A triple alternating optimization scheme is then developed to iteratively optimize the digital, analog, and DMA beamformers, progressively approximating the fully-digital solution. Numerical results demonstrate that the proposed secure tri-hybrid beamforming design for DMA-aided ISAC improves the sensing SNR by approximately 3 dB compared to a tri-hybrid beamforming scheme with a fixed DMA electromagnetic design.

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arXiv2026

Network Availability Enhancement in Low-Altitude HetNets: A Cross-Layer Design Perspective

This paper proposes a computing-communication resource interchange method to enhance network availability (NA) in low-altitude heterogeneous networks (LA-HetNets). In these networks, communication resource conflicts and imbalances, caused by extreme heterogeneity (diverse mobility, mixed delays, and hybrid transmission), and cross-regional traffic, reduce reliability and lead to unavailability. Restoring NA requires additional communication resources, yet dynamic cross-regional scheduling is limited, making locally redundant computing resources an alternative to reduce communication resource overhead. While computing resources address medium access control (MAC)-layer unreliability, physical (PHY)-layer functionalities still rely on communication resources. Thus, it remains unclear whether increasing computing resources alone can achieve target NA, especially under greater heterogeneity. We elaborate on the impact of heterogeneity on NA and show that expanding computing resources alone cannot meet target NA under high heterogeneity, as NA degrades sharply due to increased communication capability demands. To overcome this, we propose a cross-layer optimization method enabling computing-communication resource interchange to address both MAC- and PHY-layer unreliability. By reducing processing delays with computing resources while ensuring MAC-layer reliability, our method extends PHY-layer transmission delay and expands communication resources. Simulations demonstrate our approach's superiority in achieving target NA under greater heterogeneity, revealing that computing-communication resource interchange fulfills expanding communication capability demands more effectively than conventional resource overhead reduction.

cs.NI↗
arXiv2026

Toward Security-Resilient Cell-Free Massive MIMO: A Multi-Stage Framework

This paper develops a robust security-resilient transmission framework for cell-free massive multiple-input multiple-output (CF-mMIMO) systems under active pilot spoofing attacks. As a baseline, system performance is characterized under attack-free conditions to establish the target user's pre-attack service level. Upon attack detection, the system enters an absorption phase, during which, power allocation is adaptively adjusted across a limited subset of access points (APs) using contaminated channel state information (CSI). This phase quickly compensates for performance degradation while maintaining low operational overhead. Once the secrecy spectral efficiency (SSE) recovers to a prescribed loss level, the resulting power allocation initializes the restoration phase. Here, the transmit powers of all APs are jointly optimized, and a protective partial zero-forcing (PPZF) strategy further improves secrecy. In parallel, artificial noise (AN) is incorporated under a worst-case eavesdropping scenario accounting for large-scale fading uncertainty. The resulting stage-dependent non-convex problems are formulated within a unified framework and solved using successive convex approximation (SCA). Numerical results demonstrate that the proposed scheme achieves an effective time-quality tradeoff while maintaining the highest recovered secrecy; in a representative setup, it achieves gains of up to 3.6%, 15.7%, and 56% over the respective baseline schemes, with similar improvements under eavesdropper's channel uncertainty.

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arXiv2026

On the Probability of Network States with Gaussian Connectivity Functions

In this paper, we consider the connectivity of a random network of N mobile devices in three dimensions (3D), where the location of each device or node has a Gaussian distribution in each dimension. For each pair of nodes, the probability of connectivity is related to the nodes' separation by a Gaussian connectivity function. The fundamental analytical tool for studying such systems is the probability of a given network state, derived and expressed in terms of its graph Laplacian. Leveraging this result, we obtain results for the connectivity of small networks, the probability of a complete network (where all nodes are connected to all other nodes), and the probability of an isolated node, which gives an approximation to the connectivity probability of larger networks. The general results are then simplified for special cases and limiting scenarios.

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arXiv2026

Hybrid STAR-RIS Architecture for Joint Localization, Communication, and Power Transfer

We propose a hybrid simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) architecture with dynamically switched active and passive elements to support joint localization, communication, and wireless power transfer (WPT). We first pursue a parallel factor analysis with the alternating least squares (PARAFAC-ALS)-based tensor decomposition approach that decouples the base station (BS)-reconfigurable intelligent surface (RIS) and RIS-user channels, thereby enabling low-overhead channel acquisition. Based on this, we formulate a system energy efficiency (EE) maximization problem, subject to the spectral efficiency (SE) requirements of communication users, sensing signal-to-interference-plus-noise ratio constraints, and the nonlinear energy harvesting requirements of energy-harvesting users. The optimization problem is nonconvex since the transmit power allocation, STAR-RIS coefficients, and active/passive mode assignments are tightly coupled in both the objective and constraints. We address this issue by alternating between two subproblems, and solving them via fractional programming, successive convex approximation and a multi-seed greedy strategy employed as an initialization step. Numerical results demonstrate that selectively activating a small, well-chosen subset of STAR-RIS elements achieves 1.5 to 3 times EE improvements compared with fully passive/active architectures, while satisfying communication, sensing, and power-transfer requirements.

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arXiv2026

Power-Efficient XL-MIMO Design for Mixed Near- and Far-Field SWIPT Systems

This paper examines the power consumption (PC) efficiency of a mixed near- and far-field (MF) simultaneous wireless information and power transfer (SWIPT) system underpinned by a hybrid beamforming (HB)-based modular extra-large multiple-input-multiple output (XL-MIMO) array. Multiple information decoding (ID) and energy harvesting (EH) users are served by multiple constituent subarrays in both the near-field (NF) and far-field (FF) region of the transmit array. A novel decision method is proposed for accurate classification of different field users using Frobenius norm-based frequency correlation of the least square (LS) channel estimates. The NF spatial non-stationarities (SnS) effects entail distinct electromagnetic (EM) visibility regions (VRs), which can be customized to employ strategic activation of the constituent XL-MIMO subarrays. We formulate a two-tier joint optimization problem to minimize the overall PC, considering the power allocation (PA) for both ID and EH users in addition to the subarray activation (SA). This challenging mixed-integer problem is transformed into computationally tractable formulations, accompanied by the development of well-optimized algorithms. Our simulation results demonstrate an overall PC reduction for our proposed PA-SA-HB scheme by up to 93% against the equal PA with full array (FA) and up to 18% with respect to the PA-FA-HB case.

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arXiv2026

Modular-CAPA-Based Communication Systems: Joint Activation and Beamforming Design

A modular continuous aperture array (CAPA)-based multi-user communication system is investigated, where only a portion of the aperture, namely sub-CAPAs, is activated to serve users. The signal model for the proposed modular CAPA is first introduced. Based on this model, a spectral efficiency (SE) maximization problem is formulated to jointly optimize the sub-CAPA activation and beamforming, subject to constraints on the limited number of active sub-CAPAs and the total transmit power. To address the resulting mixed-integer optimization problem, a branch-and-bound (B&B)-based algorithm is first proposed for optimal sub-CAPA activation and beamforming design. After that, the spatial bandwidth of the modular CAPA under partial activation is analyzed. The analysis reveals that a modular CAPA with partial sub-CAPAs activated could achieve a maximum spatial bandwidth comparable to that of a conventional CAPA. Motivated by this insight, a low-complexity spatial bandwidth-aware sub-CAPA activation scheme is further proposed. Finally, numerical results demonstrate that i) modular CAPA architectures with partial activation can consistently achieve greater performance gains than adjacent CAPA activations; ii) the proposed B&B scheme outperforms all benchmark schemes in terms of SE; and iii) the proposed spatial bandwidth-aware scheme provides an attractive performance-complexity tradeoff compared with the proposed B&B-based algorithm.

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arXiv2026

Spatial Limits of Fluid Antenna Systems

Continuous fluid antenna systems (CFASs) represent an upper bound on the spatial diversity performance of fluid antenna systems (FASs), achieved when antennas may be positioned anywhere within a defined spatial region. This article examines the fundamental relationships governing CFAS performance. The focus is on the probability that the signal-to-noise ratio (SNR) exceeds a prescribed high threshold, termed the high SNR probability (HSP). This is among the few FAS performance metrics that admit the derivation of closed-form expressions. Following a survey of recent analytical advances in FAS performance limits, a dimensional scaling law derived for the HSP of a single-user, single-antenna CFAS is examined. This law is then applied to the per-user high signal-to-interference-plus-noise ratio (SINR) probability of a two-antenna, two-user CFAS employing minimum mean-squared error (MMSE) combining. For both scenarios, performance gains are shown to increase consistently with both dimensionality and region size. Remarkably, the scaling law remains accurate in the two-user case, showing that, in both scenarios, the influence of additional dimensions is dominated by the CFAS size and considered threshold. Moreover, the per-user high SINR probability of the two-user system exceeds the single-user HSP, despite the addition of inter-user interference.

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arXiv2026

Max-Min Rate Fairness Optimization for Multi-User Pinching-Antenna NOMA Systems

Pinching-antenna systems (PASs) can overcome signal blockage by repositioning dielectric radiating elements, called pinching antennas (PAs), along meter-scale waveguides to create line-of-sight links. Since each waveguide is driven by a single radio-frequency (RF) chain, non-orthogonal multiple access (NOMA) is well suited for PAS-based multi-user communications. This paper studies a PAS-enabled multi-user downlink NOMA system with multiple waveguides, each equipped with multiple PAs. The PA positions and base-station transmit precoding are jointly optimized to maximize the minimum user rate. The resulting problem is highly non-smooth and non-convex because of the rapidly oscillating coherent sums caused by inter-PA interference. To tackle this challenge, we propose a two-stage structured optimization framework. In the first stage, coarse PA-position and power-allocation optimization is performed using an interior-point algorithm while neglecting the PA channel phases, which gives solutions near the true optima. In the second stage, PA positions and transmit precoding are fine-tuned while accounting for the PA channel phase shifts. This stage first applies phase zeroing, where each PA is locally repositioned to align the corresponding channel phase toward zero and promote constructive coherent combining. It then uses an alternating procedure that iteratively performs forward-backward PA position refinement and successive-convex-approximation-based complex transmit precoding optimization until convergence, thereby reducing residual phase mismatch. Simulation results show that the proposed framework significantly outperforms heuristic optimization benchmarks with much lower computational time. They also demonstrate large gains over a comparable multiple-input multiple-output downlink NOMA system and reveal the impact of the number of PAs, users, and transmit power on system performance.

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arXiv2026

Sparse Channel Estimation for SIM-based mmWave Near-Field Communications

In this paper, we address the channel estimation (CE) problem in SIM-based multi-user (MU) millimeter-wave (mmWave) near-field communication systems. To address the severe path loss and blockage in mmWave communication systems, many meta-atoms are typically integrated into each layer of the SIM. Then, the number of radio frequency (RF) chains at the base station (BS) is fewer than that of meta-atoms per layer, resulting in an underdetermined problem. Additionally, the increase in the number of meta-atoms in each layer expands the SIM's near-field region, leading to the user equipment (UEs) being mostly situated in this region, necessitating precise modeling of the channel under the spherical wavefront assumption. To address these issues, we introduce a compressed sensing (CS)-based CE protocol to tackle the underdetermined problem. In contrast to the traditional CS-based estimation framework, we investigate a polar-domain channel representation to tackle the severe energy spread effect of the classical angular-domain channel representation in near-field communication systems. Specifically, we design a novel polar-domain transform matrix for uniform planar arrays (UPAs), thereby transforming the CE problem into a sparse recovery task of the paths' support set and complex gains. To overcome the limitations of the sparse Bayesian learning (SBL) framework in tackling high-dimensional dictionaries, we propose a low-complexity polar-domain SBL (LCPD-SBL) algorithm, which significantly reduces computational complexity without compromising estimation accuracy.

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arXiv2026

Distributed Near-Field Channel Estimation for U6G XL-MIMO Systems under Beam Squint

Since the beam squint and near-field effects both inherently exist in upper-6 GHz (U6G) extremely large-scale multiple-input multiple-output (XL-MIMO) systems, wideband near-field channel estimation faces severe challenges, such as higher computational complexity, and higher pilot overhead particularly at hybrid architectures with fewer radio frequency (RF) chains. To precisely reduce the complexity and number of pilots, the parametric symmetry of wideband near-field channels is explored, such that the channel parameters, including angle, distance, and range, can be decoupled based on the delay variations observed by different antennas. Based on this, a distributed parametric symmetry-based (DPS) algorithm, applicable to U6G XL-MIMO, is proposed. The delays observed by different subarrays are estimated and extrapolated across the local processing units (LPUs) firstly, and then, the channel parameters are decoupled and estimated at the central processing unit (CPU), by only linearly combining the delays from different LPUs. The path gains are calculated at different LPUs, respectively, to reconstruct the channel with low complexity. Since the proposed algorithm does not rely on scanning the polar-domain dictionary, only a single pilot is required even with hybrid architectures. Furthermore, the computational complexity, multiple-path resolution, Cramer-Rao lower bound (CRLB) and lower bound (LB) of the estimates in hybrid architectures and the DPS algorithm, respectively, are analyzed, to evaluate the realizable potential of the proposed algorithm. The simulation results prove that the proposed algorithm has a higher estimation accuracy, while requiring less complexity and pilots.

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arXiv2026

Wideband Precoding for U6G XL-MIMO Systems: Beam Squint Boundaries and Channel Slicing

The unconventionally large aperture of extremely large-scale multiple-input multiple-output (XL-MIMO) arrays, in conjunction with the wider bandwidths in the upper-6 GHz (U6G) frequency bands, will very likely lead to non-negligible beam squint effects. In the context of a limited number of radio frequency (RF) chains, and by adopting hybrid precoding, the beams at different subcarriers may point to different positions and compromise the spectral efficiency (SE). Moreover, the existence of \textit{multiple paths} in U6G XL-MIMO channels also entails practical challenges for wideband precoding. It is therefore essential to ascertain whether the beam squint effect is pronounced for U6G XL-MIMO systems and design efficient wideband precoding schemes. To address these challenges, precise antenna-domain and frequency-domain wideband boundaries are derived from the near-field and far-field perspectives, respectively. These boundaries can inform the design of wideband precoding in future system settings. Subsequently, a channel slicing scheme is proposed for wideband precoding. The process involves the segmentation of U6G XL-MIMO channels into multiple blocks, with the objective of mitigating the beam squint effect for each path. The antenna-domain and frequency-domain slicing methods are developed for multipath and multiuser scenarios, respectively. The simulation results prove that the beam squint effect remains a significant issue for U6G XL-MIMO systems, while the near-field effect invariably precedes the beam squint effect as the array size and the bandwidth increase. In addition, the proposed scheme can greatly improve the SE.

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arXiv2026

Mobile Communications in Intelligent Rail Transit: From LCX to PASS

Wireless communications in intelligent rail transit face harsh propagation conditions, including severe penetration loss, frequent blockages, and amplified large-scale fading. Existing leaky coaxial cables (LCX) provide wired-to-wireless conversion and stable coverage, but can be energy- and spectrum-inefficient, particularly at high carrier frequencies. Motivated by the growing demand for high-capacity and high-reliability rail services, this article introduces pinching-antenna systems (PASS), which are flexible waveguide-based architectures that enable reconfigurable radiation points with low deployment overhead and a natural fit to predominantly straight track geometries. We discuss the key benefits and deployment flexibility of PASS, evaluate their performance relative to LCX via representative simulations, and present a deep learning (DL)-enabled channel-estimation framework to cope with mobility-induced channel dynamics. Finally, we summarize the major open challenges for practical deployment and outline promising research directions.

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