OFDMA for Pinching Antenna Systems

Pinching-antenna (PA) systems route millimeter wave (mmWave) signals through a leaky waveguide and radiate them at "pinch" apertures, offering low-cost line-of-sight (LoS) coverage. However, when multiple PAs serve multiple users simultaneously, the downlink channel becomes strongly frequency-selective, creating inter-symbol interference (ISI) that existing single-carrier designs overlook. This paper models the overall channel as a finite impulse response (FIR) filter, characterizes its frequency selectivity, and explicitly accounts for the resulting ISI. To overcome ISI, we introduce an orthogonal frequency-division multiple access (OFDMA)-based framework and formulate a max-min resource-allocation problem to achieve user fairness. A lightweight two-stage heuristic-greedy subcarrier assignment, followed by per-user water-filling, achieves near-optimal fairness with polynomial complexity. Simulation results for an indoor layout demonstrate that the proposed scheme notably increases the minimum user rate compared to time-division single-carrier baselines and remains robust under moderate LoS blockage.

Wireless Sensing via Pinching-Antenna Systems

A wireless sensing architecture via pinching antenna systems is proposed. Compared to conventional wireless systems, PASS offers flexible antenna deployment and improved probing performance for wireless sensing by leveraging dielectric waveguides and pinching antennas (PAs). To enhance signal reception, leaky coaxial (LCX) cables are used to uniformly collect echo signals over a wide area. The Cram\'er-Rao bound (CRB) for multi-target sensing is derived and then minimized through the joint optimization of the transmit waveform and the positions of PAs. To solve the resulting highly coupled, non-convex problem, a two-stage particle swarm optimization (PSO)-based algorithm is proposed. Numerical results demonstrate significant gains in sensing accuracy and robustness over conventional sensing systems, highlighting the benefits of integrating LCX-based reception with optimized PASS configurations.

Rate Region of ISAC for Pinching-Antenna Systems

The Pinching-Antenna SyStem (PASS) reconstructs wireless channels through \emph{pinching beamforming}, wherein the activated positions of pinching antennas along dielectric waveguides are optimized to shape the radiation pattern. The aim of this article is to analyze the performance limits of employing PASS in integrated sensing and communications (ISAC). Specifically, a PASS-assisted ISAC system is considered, where a pinched waveguide is utilized to simultaneously communicate with a user and sense a target. Closed-form expressions for the achievable communication rate (CR) and sensing rate (SR) are derived to characterize the information-theoretic limits of this dual-functional operation. \romannumeral1) For the single-pinch case, closed-form solutions for the optimal pinching antenna location are derived under \emph{sensing-centric (S-C)}, \emph{communications-centric (C-C)}, and \emph{Pareto-optimal} designs. On this basis, the CR-SR trade-off is characterized by deriving the full CR-SR rate region, which is shown to encompass that of conventional fixed-antenna systems. \romannumeral2) For the multiple-pinch case, an antenna location refinement method is applied to obtain the optimal C-C and S-C pinching beamformers. As a further advance, inner and outer bounds on the achievable CR-SR region are derived using an element-wise alternating optimization technique and by invoking Cauchy-Schwarz and Karamata's inequalities, respectively. Numerical results demonstrate that: \romannumeral1) the derived bounds closely approximate the true CR-SR region; and \romannumeral2) PASS can achieve a significantly larger rate region than conventional-antenna systems.

Channel Fingerprint Construction for Massive MIMO: A Deep Conditional Generative Approach

Accurate channel state information (CSI) acquisition for massive multiple-input multiple-output (MIMO) systems is essential for future mobile communication networks. Channel fingerprint (CF), also referred to as channel knowledge map, is a key enabler for intelligent environment-aware communication and can facilitate CSI acquisition. However, due to the cost limitations of practical sensing nodes and test vehicles, the resulting CF is typically coarse-grained, making it insufficient for wireless transceiver design. In this work, we introduce the concept of CF twins and design a conditional generative diffusion model (CGDM) with strong implicit prior learning capabilities as the computational core of the CF twin to establish the connection between coarse- and fine-grained CFs. Specifically, we employ a variational inference technique to derive the evidence lower bound (ELBO) for the log-marginal distribution of the observed fine-grained CF conditioned on the coarse-grained CF, enabling the CGDM to learn the complicated distribution of the target data. During the denoising neural network optimization, the coarse-grained CF is introduced as side information to accurately guide the conditioned generation of the CGDM. To make the proposed CGDM lightweight, we further leverage the additivity of network layers and introduce a one-shot pruning approach along with a multi-objective knowledge distillation technique. Experimental results show that the proposed approach exhibits significant improvement in reconstruction performance compared to the baselines. Additionally, zero-shot testing on reconstruction tasks with different magnification factors further demonstrates the scalability and generalization ability of the proposed approach.

Pinching-Antenna Systems (PASS): Power Radiation Model and Optimal Beamforming Design

Pinching-antenna systems (PASS) improve wireless links by configuring the locations of activated pinching antennas along dielectric waveguides, namely pinching beamforming. In this paper, a novel adjustable power radiation model is proposed for PASS, where power radiation ratios of pinching antennas can be flexibly controlled by tuning the spacing between pinching antennas and waveguides. A closed-form pinching antenna spacing arrangement strategy is derived to achieve the commonly assumed equal-power radiation. Based on this, a practical PASS framework relying on discrete activation is considered, where pinching antennas can only be activated among a set of predefined locations. A transmit power minimization problem is formulated, which jointly optimizes the transmit beamforming, pinching beamforming, and the numbers of activated pinching antennas, subject to each user's minimum rate requirement. (1) To solve the resulting highly coupled mixed-integer nonlinear programming (MINLP) problem, branch-and-bound (BnB)-based algorithms are proposed for both single-user and multi-user scenarios, which is guaranteed to converge to globally optimal solutions. (2) A low-complexity many-to-many matching algorithm is further developed. Combined with the Karush-Kuhn-Tucker (KKT) theory, locally optimal and pairwise-stable solutions are obtained within polynomial-time complexity. Simulation results demonstrate that: (i) PASS significantly outperforms conventional multi-antenna architectures, particularly when the number of users and the spatial range increase; and (ii) The proposed matching-based algorithm achieves near-optimal performance, resulting in only a slight performance loss while significantly reducing computational overheads. Code is available at https://github.com/xiaoxiaxusummer/PASS_Discrete

Pinching-Antenna Systems (PASS)-enabled Secure Wireless Communications

A novel pinching-antenna systems (PASS)-enabled secure wireless communication framework is proposed. By dynamically adjusting the positions of dielectric particles, namely pinching antennas (PAs), along the waveguides, PASS introduces a novel concept of pinching beamforming to enhance the performance of physical layer security. A fundamental PASS-enabled secure communication system is considered with one legitimate user and one eavesdropper. Both single-waveguide and multiple-waveguide scenarios are studied. 1) For the single-waveguide scenario, the secrecy rate (SR) maximization is formulated to optimize the pinching beamforming. A PA-wise successive tuning (PAST) algorithm is proposed, which ensures constructive signal superposition at the legitimate user while inducing a destructive legitimate signal at the eavesdropper. 2) For the multiple-waveguide scenario, artificial noise (AN) is employed to further improve secrecy performance. A pair of practical transmission architectures are developed: waveguide division (WD) and waveguide multiplexing (WM). The key difference lies in whether each waveguide carries a single type of signal or a mixture of signals with baseband beamforming. For the SR maximization problem under the WD case, a two-stage algorithm is developed, where the pinching beamforming is designed with the PAST algorithm and the baseband power allocation among AN and legitimate signals is solved using successive convex approximation (SCA). For the WM case, an alternating optimization algorithm is developed, where the baseband beamforming is optimized with SCA and the pinching beamforming is designed employing particle swarm optimization.

Continuous Aperture Array (CAPA)-Based Secure Wireless Communications

A continuous aperture array (CAPA)-based secure communication system is investigated, where a base station equipped with a CAPA transmits signals to a legitimate user under the existence of an eavesdropper. For improving the secrecy performance, the artificial noise (AN) is employed at the BS for the jamming purpose. We aim at maximizing the secrecy rate by jointly optimizing the information-bearing and AN source current patterns, subject to the maximum transmit power constraint. To solve the resultant non-convex integral-based functional programming problem, a channel subspace-based approach is first proposed via exploiting the result that the optimal current patterns always lie within the subspace spanned by all users' channel responses. Then, the intractable CAPA continuous source current pattern design problem with an infinite number of optimization variables is equivalently transformed into the channel-subspace weighting factor optimization problem with a finite number of optimization variables. A penalty-based successive convex approximation method is developed for iteratively optimizing the finite-size weighting vectors. To further reduce the computational complexity, we propose a two-stage source current patterns design scheme. Specifically, the information-bearing and AN patterns are first designed using the maximal ration transmission and zero-forcing transmission, respectively. Then, the remaining power allocation is addressed via the one-dimensional search method. Numerical results unveil that 1) the CAPA brings in significant secrecy rate gain compared to the conventional discrete multiple-input multiple-output; 2) the proposed channel subspace-based algorithm outperforms the conventional Fourier-based approach, while sustaining much lower computational complexity; and 3) the two-stage ZF-MRT approach has negligible performance loss for the large transmit power regime.

Pinching-Antenna System (PASS) Enhanced Covert Communications

A Pinching-Antenna SyStem (PASS)-assisted convert communication framework is proposed. PASS utilizes dielectric waveguides with freely positioned pinching antennas (PAs) to establish strong line-of-sight links. Capitalizing on this high reconfigurable flexibility of antennas, the potential of PASS for covert communications is investigated. 1)~For the single-waveguide single-PA (SWSP) scenario, a closed-form optimal PA position that maximizes the covert rate is first derived. Subsequently, a one-dimensional power search is employed to enable low-complexity optimization for covert communications. With antenna mobility on a scale of meters, PASS can deal with the challenging situation of the eavesdropper enjoying better channel conditions than the legal user. 2)~For the multi-waveguide multi-PA (MWMP) scenario, the positions of multiple PAs are optimized to enable effective pinching beamforming, thereby enhancing the covert rate. To address the resultant multimodal joint transmit and pinching beamforming problem, a twin particle swarm optimization (TwinPSO) approach is proposed. Numerical results demonstrate that: i)~the proposed approaches can effectively resolve the optimization problems; ii)~PASS achieves a higher covert rate than conventional fixed-position antenna architectures; and iii)~with enhanced flexibility, the MWMP setup outperforms the SWSP counterpart.

Two-Timescale Joint Transmit and Pinching Beamforming for Pinching-Antenna Systems

Pinching antenna systems (PASS) have been proposed as a revolutionary flexible antenna technology which facilitates line-of-sight links via numerous low-cost pinching antennas with adjustable activation positions over waveguides. This letter proposes a two-timescale joint transmit and pinching beamforming design for the maximization of sum rate of a PASS-based downlink multi-user multiple input single output system. A primal dual decomposition method is developed to decouple the two-timescale problem into two sub-problems: 1) A Karush-Kuhn-Tucker-guided dual learning-based approach is proposed to solve the short-term transmit beamforming design sub-problem; 2) The long-term pinching beamforming design sub-problem is tackled by adopting a stochastic successive convex approximation method. Simulation results demonstrate that the proposed two-timescale algorithm achieves a significant performance gain compared to other baselines.

Movable-Element RIS-Aided Wireless Communications: An Element-Wise Position Optimization Approach

A point-to-point movable element (ME) enabled reconfigurable intelligent surface (ME-RIS) communication system is investigated, where each element position can be flexibly adjusted to create favorable channel conditions. For maximizing the communication rate, an efficient ME position optimization approach is proposed. Specifically, by characterizing the cascaded channel power gain in an element-wise manner, the position of each ME is iteratively updated by invoking the successive convex approximation method. Numerical results unveil that 1) the proposed element-wise ME position optimization algorithm outperforms the gradient descent algorithm; and 2) the ME-RIS significantly improves the communication rate compared to the conventional RIS with fixed-position elements.