Pinching-Antenna Systems-Enabled Multi-User Communications: Transmission Structures and Beamforming Optimization

Pinching-antenna systems (PASS) represent an innovative advancement in flexible-antenna technologies, aimed at significantly improving wireless communications by ensuring reliable line-of-sight connections and dynamic antenna array reconfigurations. To employ multi-waveguide PASS in multi-user communications, three practical transmission structures are proposed, namely waveguide multiplexing (WM), waveguide division (WD), and waveguide switching (WS). Based on the proposed structures, the joint baseband signal processing and pinching beamforming design is studied for a general multi-group multicast communication system, with the unicast communication encompassed as a special case. A max-min fairness problem is formulated for each proposed transmission structure, subject to the maximum transmit power constraint. For WM, to solve the highly-coupled and non-convex MMF problem with complex exponential and fractional expressions, a penalty dual decomposition (PDD)-based algorithm is invoked for obtaining locally optimal solutions. Specifically, the augmented Lagrangian relaxation is first applied to alleviate the stringent coupling constraints, which is followed by the block decomposition over the resulting augmented Lagrangian function. Then, the proposed PDD-based algorithm is extended to solve the MMF problem for both WD and WS. Furthermore, a low-complexity algorithm is proposed for the unicast case employing the WS structure, by simultaneously aligning the signal phases and minimizing the large-scale path loss at each user. Finally, numerical results reveal that: 1) the MMF performance is significantly improved by employing the PASS compared to conventional fixed-position antenna systems; 2) WS and WM are suitable for unicast and multicast communications, respectively; 3) the performance gap between WD and WM can be significantly alleviated when the users are geographically isolated.

Pinching-Antenna Systems (PASS): A Tutorial

Pinching antenna systems (PASS) present a breakthrough among the flexible-antenna technologies, and distinguish themselves by facilitating large-scale antenna reconfiguration, line-of-sight creation, scalable implementation, and near-field benefits, thus bringing wireless communications from the last mile to the last meter. A comprehensive tutorial is presented in this paper. First, the fundamentals of PASS are discussed, including PASS signal models, hardware models, power radiation models, and pinching antenna activation methods. Building upon this, the information-theoretic capacity limits achieved by PASS are characterized, and several typical performance metrics of PASS-based communications are analyzed to demonstrate its superiority over conventional antenna technologies. Next, the pinching beamforming design is investigated. The corresponding power scaling law is first characterized. For the joint transmit and pinching design in the general multiple-waveguide case, 1) a pair of transmission strategies is proposed for PASS-based single-user communications to validate the superiority of PASS, namely sub-connected and fully connected structures; and 2) three practical protocols are proposed for facilitating PASS-based multi-user communications, namely waveguide switching, waveguide division, and waveguide multiplexing. A possible implementation of PASS in wideband communications is further highlighted. Moreover, the channel state information acquisition in PASS is elaborated with a pair of promising solutions. To overcome the high complexity and suboptimality inherent in conventional convex-optimization-based approaches, machine-learning-based methods for operating PASS are also explored, focusing on selected deep neural network architectures and training algorithms. Finally, several promising applications of PASS in next-generation wireless networks are highlighted.

Subspace Fitting Approach for Wideband Near-Field Localization

Two subspace fitting approaches are proposed for wideband near-field localization. Unlike in conventional far-field systems, where distance and angle can be estimated separately, spherical wave propagation in near-field systems couples these parameters. We therefore derive a frequency-domain near-field signal model for multi-target wideband systems and develop a subspace fitting-based MUSIC method that jointly estimates distance and angle. To reduce complexity, a Fresnel approximation MUSIC algorithm is further introduced to decouple the distance and angle parameters. Numerical results verify the effectiveness of both proposed approaches.

Capacity Characterization of Pinching-Antenna Systems

Unlike conventional systems using a fixed-location antenna, the channel capacity of the pinching-antenna system (PASS) is determined by the activated positions of pinching antennas. This article characterizes the capacity region of multiuser PASS, where a single pinched waveguide is deployed to enable both uplink and downlink communications. The capacity region of the uplink channel is first characterized. \romannumeral1) For the single-pinch case, closed-form expressions are derived for the optimal antenna activation position, along with the corresponding capacity region and the achievable data rate regions under time-division multiple access (TDMA) and frequency-division multiple access (FDMA). It is proven that the capacity region of PASS encompasses that of conventional fixed-antenna systems, and that the FDMA rate region contains the TDMA rate region. \romannumeral2) For the multiple-pinch case, inner and outer bounds on the capacity region are derived using an element-wise alternating antenna position optimization technique and the Cauchy-Schwarz inequality, respectively. The achievable FDMA rate region is also derived using the same optimization framework, while the TDMA rate region is obtained through an antenna position refinement approach. The analysis is then extended to the downlink PASS using the uplink-downlink duality framework. It is proven that the relationships among the downlink capacity and rate regions are consistent with those in the uplink case. Numerical results demonstrate that: \romannumeral1) the derived bounds closely approximate the exact capacity region, \romannumeral2) PASS yields a significantly enlarged capacity region compared to conventional fixed-antenna systems, and \romannumeral3) in the multiple-pinch case, TDMA and FDMA are capable of approaching the channel capacity limit.

Pinching-Antenna Systems (PASS) Meet Multiple Access: NOMA or OMA?

A fundamental two-user PASS-based communication system is considered under three MA schemes, namely non-orthogonal multiple access (NOMA), frequency division multiple access (FDMA), and time division multiple access (TDMA). For each MA scheme, a pinching beamforming optimization problem is formulated to minimize the required transmit power for satisfying users' rate requirements. For NOMA and FDMA, a two-stage algorithm is proposed, where the locations of PAs are derived sequentially by using the successive convex approximation (SCA) method and fine-turning phase adjustment. For TDMA, by leveraging the time-switching feature of PASS, the optimal pinching beamforming of each time slot is derived to maximize the served user channel gain. Numerical results are provided to show that: 1) PASS can achieve a significant performance gain over conventional antenna systems, and 2) NOMA consistently outperforms FDMA, while TDMA provides superior performance than NOMA for symmetric user rate requirements.

Multiuser Beamforming for Pinching-Antenna Systems: An Element-wise Optimization Framework

The pinching-antenna system (PASS) reconstructs wireless channels through pinching beamforming, i.e., optimizing the activated locations of pinching antennas (PAs) along the waveguide. The aim of this article is to investigate the joint design of baseband beamforming and pinching beamforming. A low-complexity element-wise sequential optimization framework is proposed to address the sum-rate maximization problem in PASS-enabled downlink and uplink channels. i) For the downlink scenario, maximum ratio transmission (MRT), zero-forcing (ZF), and minimum mean square error (MMSE) beamforming schemes are employed as baseband beamformers. For each beamformer, a closed-form expression for the downlink sum-rate is derived as a single-variable function with respect to the pinching beamformer. Based on this, a sequential optimization method is proposed, where the positions of the PAs are updated element-wise using a low-complexity one-dimensional search. ii) For the uplink scenario, signal detection is performed using maximum ratio combining (MRC), ZF, and MMSE combiners. A closed-form sum-rate expression is derived for each linear combiner, and a similar element-wise design is applied to optimize the pinching beamforming. Numerical results are provided to validate the effectiveness of the proposed method and demonstrate that: (i) For all considered linear beamformers, the proposed PASS architecture outperforms conventional fixed-antenna systems in terms of sum-rate performance; (ii) in both downlink and uplink channels, ZF achieves performance close to that of MMSE and significantly outperforms MRT or MRC; and (iii) the proposed element-wise design eliminates the need for alternating updates between the baseband and pinching beamformers, thereby ensuring low computational complexity.

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.