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.

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.

B2X Networks: Joint Design of Communication and Control for Embodied Intelligence

This article proposes the concept of \emph{brain-body-to-everything (B2X)} networks to facilitate the integration of wireless networks and embodied intelligence. In this framework, the \emph{brain} refers to the intelligence functions for reasoning, planning, and decision-making, the \emph{body} denotes the physical embodied agent that senses and acts in the real world, and \emph{X} represents the surrounding ecosystem involved in the brain-body interaction loop. Two B2X architectures with \emph{distributed} and \emph{centralized} brains are introduced to characterize different placements of intelligence across the body, base station, and core network. The uplink and downlink designs of B2X networks are then discussed under a representative base-station-side brain setting. For the uplink, communication is redesigned for B2X state acquisition under event urgency, sensing volume, and simultaneous multi-body access. For the downlink, communication is redesigned to coordinate command delivery and conventional service under shared radio resources. Based on these uplink and downlink considerations, a communication-control Pareto boundary is further used to characterize the loop-level trade-off between wireless transmission performance and control quality in B2X networks. Finally, several open research problems are discussed to guide future B2X network design.

Pinching Antennas-Assisted Sensing: A Ziv-Zakai Bound (ZZB) Perspective

The sensing capability of the pinching-antenna system (PASS) is analyzed from a Ziv-Zakai bound (ZZB) perspective, motivated by the sensing ambiguity arising from the multimodal observation model inherent to PASS. In comparison to other Bayesian sensing bounds, the ZZB provides a lower bound on the mean-squared error (MSE) across a broad range of signal-to-noise ratios (SNRs) and accounts for ambiguity in the likelihood functions. First, an observation model is developed for an uplink sensing scenario where a single sensing target transmits uplink pilots to a single-waveguide PASS receiver equipped with multiple pinching antennas (PAs). Building on this model, general ZZB expressions are derived for arbitrary prior distributions of the target's position, and are then specialized to the Gaussian and uniform cases. Second, the asymptotic ZZBs in low- and high-SNR regimes are characterized, and the relationship between the ZZBs and the conventional Bayesian Cramér-Rao bound (BCRB) is further studied by introducing the concept of an ambiguity function. Furthermore, to reduce the high computational complexity of direct evaluation of the ZZB, SNR-free and SNR-aware surrogate objective functions are proposed to facilitate ZZB-based optimization for enhancing sensing performance. Numerical results demonstrate that: i) Compared with the BCRB, the ZZB provides a tight sensing performance lower bound over a wide range of SNRs, ii) the ambiguity-awareness of the ZZB can address the multimodality-induced ambiguity in sensing, thereby yielding a reliable lower bound on the MSE, and iii) the proposed surrogate objective functions enable effective ZZB minimization with a lower computational complexity.

Reliable ORIS-assisted FSO Communications via HARQ

This paper studies a free-space optical (FSO) link assisted by an optical reconfigurable intelligent surface (ORIS) and enhanced by a hybrid automatic repeat request (HARQ) scheme. The ORIS creates a virtual line-of-sight path around obstacles, while HARQ recovers frames corrupted by turbulence, pointing jitter, and geometric loss through retransmission and combining. We first derive a tractable statistical model for the end-to-end transmitter-ORIS-receiver (Tx-ORIS-Rx) reflected channel by jointly accounting for atmospheric turbulence, ORIS-induced pointing errors, and geometric attenuation. Building on these results, we obtain closed-form outage probability (OP) expressions for HARQ with Chase combining (HARQ-CC) and analytical outage upper bounds for HARQ with incremental redundancy (HARQ-IR), valid for an arbitrary maximum number of transmission rounds. We further conduct a high signal-to-noise ratio (SNR) analysis that provides a thorough characterization of the outage behavior and reveals the diversity order of both schemes. In addition, we characterize the delay behavior of the truncated HARQ process through the mean number of transmission rounds and the conditional mean number of rounds given successful decoding. Finally, numerical and Monte Carlo results validate the proposed analysis and show that HARQ substantially improves ORIS-assisted FSO reliability, with HARQ-IR achieving lower outage and delay than HARQ-CC, even for a small number of retransmission rounds.

Bending the Rules of Propagation: Caustic Beamforming for Next-Generation Wireless Systems

Conventional beamforming techniques primarily steer energy along desired directions or focus it at specific locations. These techniques become fragile when facing frequent blockage and highly dynamic propagation environments. In this article, we present caustic beamforming as a new paradigm for wireless beam control. First, we classify representative caustic beams according to their underlying mathematical origins and present three unique properties, namely self-bending, self-healing, and near-field non-diffracting. Building on these propagation properties, we then propose several application scenarios in sixth-generation (6G) networks. We undertake two case studies focused on physical layer security and service stability that highlight the capability of caustic beams to bypass potential eavesdroppers, deliver more uniform coverage, and sustain blockage-resilient links. We further discuss the enabling hardware architectures that facilitate practical deployments, and finally outline key open challenges regarding caustic beams that require further research.

Throughput Analysis for Near-Field Mobile Communications: Beamfocusing or Caustic Beamforming?

The migration to the Terahertz (THz) band and the deployment of extremely large antenna arrays (ELAAs) are transitioning wireless communications into the radiative near-field regime, fundamentally evolving conventional angular beam steering to beamfocusing (BF). However, the combination of the extremely narrow beamwidth and the mobility of the users necessitates frequent beamfocusing reconfigurations, incurring a significant switching overhead that degrades the system achievable throughput. In this regard, caustic beamforming (CB) is a promising alternative based on the synthesis of a continuous curved beam, which eliminates the need for beam tracking at the expense of a distributed beamforming gain. By leveraging the Airy beam as a canonical model, this paper develops an analytical framework to compare the throughputs achieved by CB and BF. Our main results include closed-form throughput expressions for both beamforming strategies and a performance boundary for paradigm selection. First, we derive the BF throughput by modeling a defocusing penalty induced by continuous user movement. The optimal beam dwell time that maximizes the throughput is analytically determined, and the impact of user speed and switching overhead on the throughput is quantified. For the CB scheme, we demonstrate that its throughput is determined by the signal-to-noise ratio (SNR) and the geometry of the trajectory of the user, yet invariant to the user speed. Finally, we analytically establish a threshold for the switching overhead to define the crossover point of the achievable throughput of both beamformers. Crucially, this threshold asymptotically vanishes at extremely high frequencies, positioning the continuous CB scheme as the preferred beam design paradigm for high-mobility THz communications.

Point Spread Function Optimization for Communication-assisted UAV-borne MIMO TomoSAR

This paper tackles the optimization of the point spread function (PSF) of unmanned aerial vehicle (UAV)-borne multiple-input multiple-output (MIMO) synthetic aperture radar (SAR) tomography systems. A swarm of UAV-borne SAR systems is deployed to image an area to obtain its height profile. To achieve a high-quality three-dimensional (3D) image of the scene, the PSF has to exhibit low sidelobes. The heavy computations, required for image generation, are performed on the ground. To this end, the sensor data collected by the UAV-SARs is offloaded in real time via a frequency division multiple access (FDMA) air-to-ground backhaul link. In this work, the UAV formation and the power allocated for offloading are jointly optimized for the minimization of the PSF sidelobe levels. To this end, we propose a novel solution based on the particle swarm optimization (PSO) algorithm, which meets practical sensing and communication constraints. Our simulation results demonstrate that the proposed solution can significantly improve sidelobe suppression compared to several benchmark schemes.

Movable-Antenna-Enhanced ISAC: Optimal Antenna Trajectory and Beamforming Design

Integrated sensing and communication (ISAC) is a key enabling technology for next-generation wireless networks. However, most existing ISAC systems rely on fixed-position antennas, which restrict performance when balancing sensing and communication objectives. Movable antenna (MA) technology introduces additional spatial degrees of freedom through antenna mobility, yet existing studies on MA-enabled ISAC schemes mainly consider static antenna repositioning and fail to fully exploit this capability. By leveraging spatio-temporal sampling enabled by antenna motion, optimized MA trajectories can synthesize large virtual aperture arrays, thereby improving angular resolution and reducing sensing ambiguity. To this end, this paper investigates a dynamic MA-enabled ISAC system and studies the joint design of MA trajectories and transmit beamforming. We formulate a joint trajectory and beamforming optimization problem to minimize sensing beampattern mismatch under communication quality-of-service constraints. A branch-and-bound-based algorithm is developed to obtain the globally optimal solution. Numerical results show that the proposed framework significantly outperforms baseline schemes with only one or two antenna repositioning steps, demonstrating its practical feasibility.

Closed-form Model for Radiation Pattern of Pinching Antennas

In this article, we develop an analytical radiation-pattern model for pinching-antenna systems (PASS) based on a two-dimensional dielectric slab waveguide. The model is derived in two steps. First, we employ coupled-mode theory (CMT) to derive a closed-form expression for the field coupled into the pinching antennas (PAs). Second, we use this analytical field profile as a scattering source model and derive the far-field radiation pattern via a two-dimensional radiation integral. We validate the proposed model against full-wave finite-element simulations performed in COMSOL Multiphysics, showing that it accurately reproduces the directional radiation characteristics of PASS. In contrast, most existing works model PAs as omni-directional point radiators, which simplifies system-level analysis but does not accurately capture the underlying electromagnetic radiation mechanism. Because the proposed model is given in closed form, it can be easily integrated into existing system-level PASS models to replace the assumed omni-directional pattern with a physically motivated directional radiation pattern. Finally, numerical simulations quantify the performance degradation that arises when the directional behavior of PAs is neglected in a representative wireless communications scenario.