arXiv subjects

Robert Schober

Publications and source records attributed to Robert Schober.

At least 19 recordsLinked to original sources

arXiv2026

Antenna Orientation Optimization for Rotatable Antenna-Enabled ISAC Systems

Non-fixed flexible antenna architectures, such as fluid antenna system (FAS), movable antenna (MA), and pinching antenna, have garnered significant interest in recent years. In this paper, we deploy a rotatable antenna (RA) array at the base station (BS) to improve the integrated sensing and communication (ISAC) performance by exploiting the additional spatial degrees of freedom (DoFs) introduced by antenna rotation. To enhance the sensing performance over an extended region containing a potential target while meeting the communication requirements of multiple users, we aim to maximize the minimum echo signal power within the sensing region, subject to required minimum communication rates of the users. For the special case of a single user and a point target, we develop a tractable approximation of the original problem, leading to independent per-RA subproblems. We characterize the geometric structure of these subproblems and derive closed-form solutions. Under the far-field approximation, the per-RA subproblems become approximately identical, allowing a common pointing vector to be adopted for all RAs. For the general multi-user and regional sensing case, we propose an alternating optimization (AO) algorithm that alternately optimizes the transmit beamforming for communication, the covariance matrix of the probing signal, and the pointing vectors of the RAs in an iterative manner. Simulation results demonstrate that the proposed RA-enabled ISAC system significantly outperforms various benchmark schemes with restricted antenna-orientation flexibility, while the evaluation of the Cramér-Rao bound (CRB) further verifies its benefits for target-position estimation accuracy.

cs.IT↗

arXiv2026

Near-Field Multipath MIMO Channels: Modeling Reflectors and Exploiting NLOS Paths

Near-field (NF) communications is receiving renewed interest in the context of multiple-input multiple-output (MIMO) systems involving large physical apertures with respect to the signal wavelength. While line-of-sight (LOS) links are typically expected to dominate in NF scenarios, the impact of non-LOS (NLOS) components at both in centimeter- and millimeter-wave frequencies may be in general non-negligible. Moreover, although weaker than the LOS path, NLOS links may be essential for achieving multiplexing gains in MIMO systems. The commonly used NF channel models for NLOS links in the literature are based on the point scattering assumption, which is not valid for large reflectors such as walls, ceilings, and the ground. In this paper, we develop a generalized statistical NF MIMO channel model that extends the widely adopted point scattering framework to account for imperfect reflections from large surfaces. This model is then leveraged to investigate how the physical characteristics of these reflectors influence the resulting NF MIMO channel. In addition, using the proposed channel model, we analytically demonstrate for a multi-user scenario that, even when users are located within the NF regime, relying solely on LOS NF links may be insufficient to achieve multiplexing gains, thus exploiting NLOS links becomes essential. Our simulation results validate the accuracy of the proposed model and show that, in many practical settings, the contribution of NLOS components is non-negligible and must be carefully accounted for in the system design.

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arXiv2026

Joint Antenna Position and Beamforming Optimization for Movable Antenna Enabled Near-Field ISAC Imaging

Near-field (NF) integrated sensing and communication (ISAC) systems enable simultaneous two-dimensional (2D) radar imaging and multi-user downlink communication. However, fixed-position antenna arrays can exhibit high sidelobes in the point spread function (PSF), which degrade imaging performance and cause ghost-target artifacts. Movable antennas (MAs) offer additional spatial degrees of freedom to suppress these sidelobes while meeting communication requirements, without increasing the number of antenna elements. In this paper, we investigate MA-enabled NF ISAC by jointly optimizing the transmit and receive antenna positions and the transmit beamforming to minimize a weighted sum of the integrated sidelobe level (ISL) and peak sidelobe level (PSL) of the 2D PSF, subject to communication-rate, illumination-power, transmit-power, and antenna-placement constraints. To tackle the resulting non-convex problem, we propose a hybrid alternating optimization (AO) framework that combines particle swarm optimization with a genetic algorithm. Our numerical results demonstrate that the proposed scheme achieves the lowest ISL among the considered array configurations and reduces the PSL by at least 5 dB compared with the benchmarks. The optimized array is further shown to resolve two closely spaced targets whose reflectivities differ by 6dB, outperforming random, Mills Cross, and rectangular arrays while satisfying the imposed minimum user-throughput requirements.

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arXiv2026

Multiscale MIGHT: Modeling Local and Systemic Particle Transport in the Cardiovascular System

Analytical models of signaling molecule (SM) transport in the cardiovascular system (CVS) force a choice between whole-body scope and vessel-level resolution: Pharmacokinetic models for systemic transport lump each organ and lack small-scale structure, whereas synthetic molecular communication (MC) channel models resolve branched vessel networks (VNs) only for a single pass or capture recirculation only in topologically simple loops, and only partially include SM degradation. To close this gap, we propose Multiscale MIGHT, an extension of the Mixture of Inverse Gaussians for Hemodynamic Transport (MIGHT) model that jointly captures branched topologies, closed-loop circulation, organ clearance, and chemical degradation of SMs. First, we connect the ends of a branched VN to form a closed loop with local and global SM degradation, model the closed-loop channel impulse response for arbitrary transmitter (Tx) and receiver (Rx) positions as a Laplace-domain feedback system, and approximate it in closed form by an inverse Gaussian mixture over multi-pass trajectories. The model is validated against finite-element simulations in COMSOL. Second, we set up a whole-body model, where an exemplary local VN, resolved at vessel-level detail, is embedded into the remaining systemic circulation, represented by lumped organ blocks. We simulate whole-body SM transport for various Tx sites and SM species. Our results show that, at an Rx in a local VN, only the initial pass produces a distinct peak in the SM concentration, significantly shaped by the local vasculature in case of small Tx-Rx distances; subsequent passes arrive strongly dispersed and are shaped almost entirely by organ clearance and chemical degradation rather than by the local VN topology.

q-bio.QM↗

arXiv2026

Design of DoF-Robust MIMO via Generalized Pinching Antennas

Spatial degrees of freedom (DoF) are fundamental to the performance of multiple-input multiple-output (MIMO) systems. However, the use of conventional fixed-location antennas introduces disparities in the users' distances to a common base station, which makes the multi-user channel matrix more susceptible to rank deficiency and, consequently, a loss of spatial DoF. This paper shows that generalized pinching antennas can be used to design a new form of MIMO robust to the loss of spatial DoF. In particular, by deploying pinching antennas in close proximity to the users, the resulting multi-user channel Gram matrix can have a well-conditioned, almost diagonal structure, which reduces its sensitivity to the users' spatial deployment as well as the risk of rank deficiency. Two performance metrics, namely the rank-deficiency probability and the outage probability, are used to evaluate the performance of pinching-antenna-assisted MIMO transmission. The presented analytical and simulation results demonstrate the capability of pinching antennas to preserve spatial DoF and provide ubiquitous connectivity by effectively supporting users at spatially separated locations.

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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

Source Distance and Source Strength Estimation in Turbulent Flow: Exploiting Molecule Degradation Diversity

Locating an odor source and estimating its strength are central problems in nature and engineering. For example, an insect may decide whether a food source is worth traveling to based on its distance and how many molecules it emits. Similarly, a drone or sensor network may need to locate a pipe leak and quantify how much chemical is released. Such tasks are highly challenging due to complex turbulent propagation dynamics. While source distance and strength estimation have been extensively investigated for sources releasing a single molecule type, in both turbulent and non-turbulent flow, many odor sources release multiple molecule types. We investigate whether considering multiple molecule types can aid source distance and strength estimation in challenging turbulent flow. We exploit that different molecule types in a mixture degrade at different rates in the atmosphere. Consequently, the relative abundance of the molecule types observed at a receiver provides information about the source distance that a single molecule type does not. Since this relative abundance is independent of the source strength, it resolves the distance-strength ambiguity inherent in the observed signal intensity and thus also improves strength estimation. Building on this, we propose heuristic low-complexity and learning-based schemes that combine the relative abundance of different molecule types with established features such as mean concentration and whiff duration. All schemes are validated via simulations of turbulent molecule propagation. The low-complexity schemes can achieve estimation quality competitive with learning-based schemes that rely only on a single molecule type, while the proposed learning-based schemes outperform their single-type counterparts. Molecule mixtures can therefore support goal-oriented tasks such as source distance and strength estimation even in challenging turbulent flow.

cs.ET↗

arXiv2026

Analytical Modeling of Open- and Closed-Loop Dispersive Molecular Communication Channels with Pulsatile Flow

Molecular communication (MC) is a communication paradigm in which information is conveyed through the release, propagation, and reception of molecules. Many envisioned healthcare applications of MC are expected to operate inside the human body, where the cardiovascular system (CVS) may serve as the physical propagation environment and molecular transport is governed by diffusion and blood flow. Although blood flow is inherently pulsatile, most analytical MC channel models assume steady flow. In this paper, we develop a time-variant analytical model for dispersive MC channels with pulsatile flow. We derive the straight-duct response as a Normal distribution with time-variant mean and variance, capturing the combined effects of diffusion and pulsatile flow, and extend it to closed-loop channels through a wrapped-Normal representation. The model is validated against three-dimensional (3D) particle-based simulations (PBSs) for synthetic and physiologically motivated velocity waveforms. We further derive a closed-form first-order approximation for the first-arrival peak time and introduce the nondimensional indicator $S_{\mathrm{Rx}}$ for assessing the applicability of the reduced one-dimensional (1D) model. Our results show that pulsatility has the strongest influence when molecular transport is predominantly advective and the temporal flow variations are not averaged out, whereas stronger diffusion and faster pulsations reduce its impact on the received signal. Moreover, a PBS-based parameter sweep supports $S_{\mathrm{Rx}} \ge 2$ as a practical criterion for the applicability of the proposed analytical model. Finally, relating the analytical assumptions to representative blood-vessel classes shows that model applicability depends not only on the transport conditions but also on physiological properties such as vessel rigidity, geometric uniformity, and blood rheology.

cs.ET↗

arXiv2026

Rotatable Antenna-Enabled Space-Air-Ground Integrated Networks: Opportunities and Challenges

Space-air-ground integrated networks (SAGINs) are expected to support ubiquitous three-dimensional (3D) communication and sensing services in future sixth-generation (6G) wireless networks. However, heterogeneous mobility and service requirements across the space, air, and ground segments challenge fixed-boresight or fixed-sector antennas in supporting wide-area coverage, maintaining directional alignment over time-varying communication links, and flexibly adjusting observation directions for sensing tasks. To address these limitations, non-fixed flexible antenna architectures, such as fluid antenna system (FAS), movable antenna (MA), and pinching antenna, have garnered significant interest in recent years. Among them, rotatable antenna (RA) technology has emerged as a promising solution by enabling mechanical or electronic boresight adjustment while keeping the antenna positions fixed. This article investigates the roles of RA technology in enabling communication and sensing in SAGINs. Specifically, we first explain how RA boresight control complements platform mobility and supports wide-area coverage, dynamic directional transmission, cross-segment cooperative operation, and cooperative sensing. We then discuss the main design challenges, potential approaches, and future research directions, including channel acquisition and predictive tracking, joint orientation control and access/handover coordination, cross-segment coordination and resource management, as well as deployment tradeoffs and practical implementation. Finally, an RA array prototype and two representative simulation studies are presented to illustrate the feasibility and potential performance gains of RA-enabled SAGINs.

cs.IT↗

arXiv2026

Simulation and Analysis of Solute Transport in Multi-Lymphangion Lymphatic Vessels

The lymphatic system (LS), a body-wide network of vessels and lymphoid organs governing fluid homeostasis and immune surveillance, has so far not been investigated as a domain for diagnostic and therapeutic molecular communications (MC) applications, despite several properties that make it a promising, complementary alternative to the cardiovascular system. These favorable properties include slower flow, simpler and less dense molecular fluid composition, and direct anatomical access to lymph nodes. Realizing this potential, however, requires a quantitative understanding of how solutes propagate through the LS, a problem that, unlike lymph flow itself, remains largely unaddressed in the literature. As a first step towards narrowing this gap, we develop a particle-based simulation (PBS) framework of solute transport through a three-dimensional chain of valve-separated, concatenated vessel segments, called lymphangions. We simulate the spatiotemporal evolution of solute concentration and qualitatively validate the resulting transport dynamics against existing in vivo measurements of fluorescent tracer propagation in multi-lymphangion lymphatic vessels. Our simulations show that the valve-gated nature of solute transport in lymphatic vessels leads to bursty solute concentrations over time, a characteristic that can also be observed in vivo. Additionally, we find that, within one pumping period, peak timing is dictated by the valves' synchronizing effect rather than the particle release time, while diffusivity and receiver placement determine peak sharpness. Overall, the proposed PBS framework provides a first quantitative basis for solute transport modeling in the LS and several concrete application scenarios for MC in this underexplored domain. Supplementary video material illustrating the PBS is publicly available on Zenodo [DOI: 10.5281/zenodo.21888066].

q-bio.TO↗

arXiv2026

Joint Communication and Control Beamforming: A Closed-Loop Control Perspective

A joint communication and control (JCC) framework is proposed, where a base station (BS) simultaneously serves multiple communication users (CUs) and controls a physical plant in a closed loop. In the downlink, BS-generated control inputs are transmitted to and recovered at the plant, with wireless actuation distortion incorporated into the plant-state evolution. In the uplink, the plant state is reported to the BS and tracked by a Kalman filter (KF) for subsequent control-input generation. To characterize long-term control performance under communication-control interference, finite- and infinite-horizon linear quadratic Gaussian (LQG) costs are derived, directly linking beamforming design to plant-state evolution. JCC beamforming problems are then formulated for vector- and scalar-valued control inputs to minimize the infinite-horizon LQG cost subject to per-user communication signal-to-interference-plus-noise ratio (SINR) requirements. For the vector case, a second-order cone programming (SOCP)-based successive convex approximation method is developed for the resulting nonconvex problem. For the scalar case, a closed-form infinite-horizon LQG cost is derived, and the communication-control Pareto boundary is optimally characterized by an SOCP-based bisection method. Its optimality follows from the strict monotonicity of the scalar control cost with respect to the control SINR. Numerical results show that the derived costs closely match Monte Carlo simulations, the KF accurately tracks the ground-truth plant-state trajectory, and the proposed methods consistently outperform the zero-forcing benchmark. This confirms the benefit of balancing communication-control interference, especially with limited spatial degrees of freedom (DoFs).

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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

Frequency-Selective Pinching-Antenna Systems

An uplink pinching-antenna system (PASS) is considered, where a segmented dielectric waveguide is employed to serve multiple users and one pinching antenna (PA) is activated on each segment. Extensive waveguide deployment reduces user-to-PA path loss but also creates differential propagation delays among the PA-assisted paths spanning the large waveguide aperture. These delays are retained, and a Toeplitz block model is derived to characterize the resulting frequency-selective (FS) channel. For infinite-blocklength transmission, the achievable single-user rate and the multiuser sum-rates under joint and parallel decoding are characterized. For carrier-phase-aligned single-user PA placement, the frequency-flat (FF) model is shown to overestimate the exact FS rate. The difference between the rates computed under the FF channel model and the exact FS channel model is referred to as the FF rate overestimation, and its dependence on the waveguide-aperture-induced delay spread is characterized. For small delay spreads, the FF rate overestimation is shown to increase approximately quadratically with the delay spread, whereas a derived lower bound reveals that the overestimation grows at least double logarithmically with the waveguide aperture, or equivalently with the delay spread, in the large-aperture regime. For finite-blocklength transmission, achievable rates are derived under a practical cyclic-prefix single-carrier frequency-domain equalization framework. An element-wise algorithm is developed to optimize FS-aware PA placement in both transmission regimes. The analytical findings demonstrate that differential delays across the extensively deployed waveguide can cause significant frequency selectivity and that the proposed FS-aware PA placement method substantially improves the achievable rate over placement based on the FF approximation, especially for large bandwidths and apertures.

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arXiv2026

Statistical Channel Model for FSO Systems Assisted by a UAV-Mounted IRS

Integrating optical intelligent reflecting surfaces (IRSs) into aerial platforms, such as unmanned aerial vehicles (UAVs), has been proposed to relax the line-of-sight (LoS) constraint, extend coverage, and enhance deployment flexibility of free space optical (FSO) systems. However, misalignment errors induced by the UAV hovering, in both position and orientation, may degrade connectivity and impair the end-to-end channel quality. In this paper, we develop novel expressions for the electric fields incident on and reflected by an optical IRS, based on the Huygens-Fresnel principle. The resulting expressions are applicable for any combination of incident and reflected propagation directions. Building on this framework, we derive a closed-form statistical channel model that captures the geometric and misalignment losses of an FSO link assisted by a UAV-mounted IRS in the presence of random UAV fluctuations. In particular, we develop a statistical model for the beam misalignment at the receiver lens, assuming Gaussian fluctuations in both the UAV position and orientation. The proposed analytical model is validated through Monte Carlo (MC) simulations and is further used to provide practical design guidelines regarding the optimal placement of the UAV-mounted IRS for the minimization of the outage probability.

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arXiv2026

Rotatable Antenna-Empowered Wireless Networks: A Tutorial

Non-fixed flexible antenna architectures, such as fluid antenna system (FAS), movable antenna (MA), and pinching antenna, have garnered significant interest in recent years. Among them, rotatable antenna (RA) has emerged as a promising technology for enhancing wireless communication and sensing performance through flexible antenna orientation/boresight rotation. By enabling mechanical or electronic boresight adjustment without altering physical antenna positions, RA introduces additional spatial degrees of freedom (DoFs) beyond conventional beamforming. In this paper, we provide a comprehensive tutorial on the fundamentals, architectures, and applications of RA-empowered wireless networks. Specifically, we begin by reviewing the historical evolution of RA-related technologies and clarifying the distinctive role of RA among flexible antenna architectures. Then, we establish a unified mathematical framework for RA-enabled systems, including general antenna/array rotation models, as well as channel models that cover near- and far-field propagation characteristics, wideband frequency selectivity, and polarization effects. Building upon this foundation, we investigate antenna/array rotation optimization in representative communication and sensing scenarios. Furthermore, we examine RA channel estimation/acquisition strategies encompassing orientation scheduling mechanisms and signal processing methods that exploit multi-view channel observations. Beyond theoretical modeling and algorithmic design, we discuss practical RA configurations and deployment strategies. We also present recent RA prototypes and experimental results that validate the practical performance gains enabled by antenna rotation. Finally, we highlight promising extensions of RA to emerging wireless paradigms and outline open challenges to inspire future research.

cs.IT↗

arXiv2026

ToDMA: Large Model-Driven Massive Token Communications for Semantic Multiple Access

Token communications (TokenCom) is an emerging generative semantic communication paradigm, where tokens serve as compact representation units across modalities. Their contextual dependencies can be exploited by pretrained large models for semantic recovery. In this paper, we propose token-domain multiple access (ToDMA), a large-model-driven semantic multiple access scheme for massive token communications. ToDMA integrates unsourced random access with context-aware token processing. It enables massive uncoordinated devices to transmit tokenized source representations over common uplink resources. Specifically, each token index is associated with a shared modulation codeword, exposing token-level structure to the receiver for context-aware recovery. At the receiver, compressed sensing is first employed to jointly detect active tokens and estimate their corresponding channel state information (CSI) from the superposed signals. The source token sequences are then reconstructed by exploiting the consistency of token-associated CSI across multiple token positions. In the presence of token collisions, some active tokens may remain unassigned, leading to missing entries in the reconstructed token sequences. To recover these tokens, candidate-restricted masked-token prediction is performed using pretrained contextual models, thereby leveraging token-level context to mitigate collision effects. Simulation results on both image and text transmission tasks demonstrate that ToDMA reduces access latency while maintaining favorable token recovery and semantic reconstruction quality, showing its scalability for semantic multiple access.

cs.IT↗

arXiv2026

Optimization and Deep Learning based Resource Allocation for UAV-Aided Wireless Communication with Rotatable Antenna Array

Multi-antenna unmanned aerial vehicle (UAV)-aided communication presents a promising solution to increase the system capacity and improve the quality of service (QoS) of the future wireless networks. In this paper, we equip a UAV platform with a rotatable antenna array (RAA), which can be rotated flexibly in three-dimensional (3D) space via an onboard gimbal, enabling additional spatial degrees of freedom (DoFs) for improving multiuser signal transmission and interference management. Compared with a conventional fixed antenna array (FAA), the RAA can proactively align users with the high-gain region of its antenna elements and reduce the spatial channel correlations among users. To demonstrate the advantages of RAA, we jointly design the RAA orientation and beamforming to maximize the sum-rate of multiple users subject to per-user QoS constraints. The formulated problem is highly nonconvex and exhibits strong coupling between the RAA orientation and beamforming variables. To solve this challenging problem, we propose first an optimization framework based on the penalty dual decomposition (PDD) method to iteratively optimize RAA orientation and beamforming. While the optimization framework yields high reliability in QoS satisfaction and favorable sum-rate performance, its iterative nature may hinder real-time deployment. To accelerate the joint design and preserve a high-quality solution, we further propose a deep learning (DL) framework based on graph neural networks (GNNs). Simulation results demonstrate that RAAs significantly outperform FAAs in UAV-aided communication. Additionally, the proposed optimization framework is capable of satisfying stringent QoS requirements with high reliability, while the proposed DL framework attains comparable sum-rate performance with substantially reduced computation time and exhibits robustness to user position information errors.

cs.IT↗

arXiv2026

Multiuser MIMO-AFDM Beamforming for ISAC in Doubly Dispersive Channels

Integrated sensing and communication (ISAC) in high-mobility channels requires waveform and beamforming designs that are robust to delay-Doppler dispersion. With this in mind, in this paper we study a monostatic multiuser multiple-input multiple-output (MIMO) affine frequency division multiplexing (AFDM) downlink system. We develop a discrete affine Fourier transform (DAFT)-domain model that preserves Doppler-induced inter-bin coupling and derive a data-aided delay-Doppler detector. The expected matched-bin detector signal-to-noise ratio (SNR) is shown to be proportional to a transmit-covariance beampattern, which leads to a detector-SNR-based sector-illumination constraint. The resulting sensing-constrained weighted sum-rate maximization problem is solved using a combined weighted minimum mean squared error (WMMSE) and majorization-minimization (MM) formulation. Simulations show that the proposed AFDM design outperforms its orthogonal frequency division multiplexing (OFDM) counterpart in terms of the rate-sensing tradeoff, robustness to Doppler, and delay-Doppler sensing quality.

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