arXiv subjects

Kaiquan Cai

Publications and source records attributed to Kaiquan Cai.

18 recordsLinked to original sources

arXiv2026

Multi-Mode Pinching-Antenna Systems: An Inter-Mode-Interference-Free Perspective

The physical model of multi-mode pinching-antenna systems (PASS) is proposed based on the coupled-mode theory. Within the considered model, multiple guided modes are simultaneously excited in a single waveguide and exploited as independent signal-bearing channels, thus providing additional modal degrees of freedom for signal transmission. Under the local electromagnetic perturbations introduced by PAs, the undesired guided-modes coupling is explicitly investigated, and the resulting inter-mode interference (IMI) issue is revealed. The sufficient hardware-design condition for achieving the IMI-free regime is further established, for which the practical feasibility is validated through full-wave electromagnetic simulations. Then, a tractable signal model is derived for multi-mode PASS operating over the IMI-free regime. To demonstrate the benefits of the proposed multi-mode PASS model, the integrated sensing and communications (ISAC) is studied as a representative application scenario, where the base station simultaneously communicates with a communication user and senses a target by using two guided modes. A joint baseband and pinching beamforming optimization problem is formulated for the minimization of the Cramer-Rao bound for target localization, subject to the minimum communication rate requirement, under both continuous and discrete PAs activation cases. An alternating optimization-based algorithm is developed to address the formulated non-convex problem. For the baseband beamforming, a penalty-based successive convex approximation method is invoked. For the pinching beamforming, a particle swarm optimization algorithm and a two-sided matching algorithm are proposed for the continuous and discrete PAs activation cases, respectively. Numerical results obtained in the ISAC application scenario demonstrate the superiority of the proposed multi-mode PASS model over the single-mode PASS.

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arXiv2026

Pinching-Antenna Systems-enabled Secure ISAC: A Two-Timescale Optimization Framework

A novel two-timescale optimization framework is proposed for pinching-antenna systems (PASS)-enabled secure integrated sensing and communications (ISAC). Specifically, a base station (BS) equipped with pinching antennas (PAs) transmits signals to a legitimate user under the existence of an eavesdropper (Eve), while employing leaky coaxial cables (LCXs) for receiving echo signals to track Eve's mobility states, i.e., locations and velocities. Considering the practical PAs activation overhead, the pinching beamforming and baseband processing are optimized in the large and small timescales, respectively. The multiple-waveguide scenario is first considered, where the BS can transmit the artificial noise together with communication signals for both jamming and sensing purposes. A joint baseband and pinching beamforming design problem is formulated to maximize the average secrecy rate. To address this problem, an alternating optimization algorithm is first invoked for jointly optimizing the pinching and baseband beamforming with predicted Eve's mobility states. With determined PAs positions, the baseband beamforming is updated with refined Eve's states obtained from real-time echo signal processing. The single-waveguide scenario is then considered. Since a single waveguide carries at most one independent data stream, an ISAC framework with separate communication and sensing phases is proposed. The element-wise algorithm proposed for the multiple-waveguide scenario is extended to solve the resultant pinching beamforming problem. Numerical results demonstrate that: 1) Eve's velocities and positions can be accurately tracked with the proposed two-timescale framework in both multiple- and single-waveguide scenarios; and 2) PASS achieves superior secrecy rate compared to conventional multiple-antenna benchmarks.

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arXiv2026

Rotatable Antenna-Enhanced Secure Integrated Sensing and Communications Under Imperfect CSI

A rotatable antenna (RA)-enhanced secure integrated sensing and communications system is investigated, where an RA-based transceiver simultaneously communicates with legitimate users and senses a target that is regarded as a potential eavesdropper. Under imperfect eavesdropping channel state information (CSI), a max-min data rate optimization problem is formulated by jointly optimizing the transmit beamforming, artificial noise (AN) covariance matrix, and transmit/receive boresights of RAs, subject to the maximum information leakage and minimum sensing power constraints. To address the highly non-convex problem, the information leakage and sensing power constraints are transformed into convex ones via S-Procedure method and Cauchy-Schwarz inequality, respectively. Subsequently, an alternating optimization algorithm is developed to decompose the reformulated problem into two subproblems. In particular, the transmit beamforming and AN covariance matrix are optimized by utilizing successive convex approximation and semi-definite relaxation methods, while the RA boresights are obtained by invoking the particle swarm optimization. Simulation results show that the RA-based scheme significantly outperforms the benchmarks, and offers enhanced robustness against imperfect CSI with the increase of the maximum rotation range.

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arXiv2025

Resource Allocation for Pinching-Antenna Systems (PASS)-enabled NOMA Communications

Pinching-antenna systems (PASS) have emerged as a promising technology due to their ability to dynamically reconfigure wireless propagation environments. A novel PASS-based multi-user non-orthogonal multiple access (NOMA) framework is proposed by exploiting the waveguide-division (WD) transmission characteristic. Specifically, each NOMA user cluster is served by one dedicated waveguide, and the corresponding pinching beamforming is exploited to enhance the intra-cluster performance while mitigating the inter-cluster interference. Based on this framework, a sum-rate maximization problem is formulated for jointly optimizing power allocation, pinching beamforming, and user scheduling. To solve this problem, a two-step algorithm is developed, which decomposes the original problem into two subproblems. For the joint power allocation and pinching beamforming design, a penalty dual decomposition (PDD) algorithm is proposed to obtain the locally optimal solutions. Specifically, the coupling constraints are alleviated through augmented Lagrangian relaxation, and the resulting augmented Lagrangian (AL) problem is decomposed into four subproblems, which are solved by the block coordinate descent (BCD) method. For the user scheduling, a low-complexity matching algorithm is developed to solve the user-to-waveguide assignment problem. Simulation results demonstrate that 1) the proposed PASS-based NOMA framework under the WD transmission structure achieves significant sum-rate gain over conventional fixed-position antenna systems and orthogonal multiple access (OMA) scheme; and 2) the proposed matching-based user scheduling algorithm achieves near-optimal user-waveguide association with low computational complexity.

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arXiv2025

Pinching-Antenna Systems-Assisted SWIPT: A Rate-Energy Trade-off Perspective

This paper investigates the rate-energy trade-off for pinching-antenna systems (PASS)-assisted simultaneous wireless information and power transfer (SWIPT) systems. Both the single information user (IU)/energy user (EU) and multiple IUs/EUs scenarios are considered.1) For the single IU/EU scenario, a pinching beamforming optimization problem is formulated for simultaneously maximizing data rate and harvested energy. To tackle this problem, a two-stage algorithm is proposed. Specifically, the successive convex approximation (SCA) method is first invoked for minimizing the large-scale path loss, which is followed by the fine-tuning method for the phase alignment. 2) For the multiple IUs/EUs scenario, three multiple access schemes are considered, i.e., frequency division multiple access (FDMA), time division multiple access (TDMA), and non-orthogonal multiple access (NOMA). The corresponding multi-objective optimization problem (MOOP) that simultaneously maximizes the minimum data rate and minimum harvested energy is formulated for ensuring users' fairness. To address this problem, we adopt the $ε$-constraint method to first convert the intractable MOOPs to single-objective optimization problems (SOOPs). Then, for the SOOP under each multiple access protocol, the particle swarm optimization (PSO) and convex optimization methods are adopted for solving the pinching beamforming and resource allocation problems, respectively. Simulation results unveil that: i) PASS can achieve a significantly superior rate-energy region compared to conventional fixed-position antenna systems for pinching beamforming; and ii) by exploiting the time-switching feature, TDMA can outperform both NOMA and FDMA for the multiple IUs/EUs scenario.

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arXiv2025

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.

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arXiv2025

Knots: A Large-Scale Multi-Agent Enhanced Expert-Annotated Dataset and LLM Prompt Optimization for NOTAM Semantic Parsing

Notice to Air Missions (NOTAMs) serve as a critical channel for disseminating key flight safety information, yet their complex linguistic structures and implicit reasoning pose significant challenges for automated parsing. Existing research mainly focuses on surface-level tasks such as classification and named entity recognition, lacking deep semantic understanding. To address this gap, we propose NOTAM semantic parsing, a task emphasizing semantic inference and the integration of aviation domain knowledge to produce structured, inference-rich outputs. To support this task, we construct Knots (Knowledge and NOTAM Semantics), a high-quality dataset of 12,347 expert-annotated NOTAMs covering 194 Flight Information Regions, enhanced through a multi-agent collaborative framework for comprehensive field discovery. We systematically evaluate a wide range of prompt-engineering strategies and model-adaptation techniques, achieving substantial improvements in aviation text understanding and processing. Our experimental results demonstrate the effectiveness of the proposed approach and offer valuable insights for automated NOTAM analysis systems. Our code is available at: https://github.com/Estrellajer/Knots.

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arXiv2025

NOTAM-Evolve: A Knowledge-Guided Self-Evolving Optimization Framework with LLMs for NOTAM Interpretation

Accurate interpretation of Notices to Airmen (NOTAMs) is critical for aviation safety, yet their condensed and cryptic language poses significant challenges to both manual and automated processing. Existing automated systems are typically limited to shallow parsing, failing to extract the actionable intelligence needed for operational decisions. We formalize the complete interpretation task as deep parsing, a dual-reasoning challenge requiring both dynamic knowledge grounding (linking the NOTAM to evolving real-world aeronautical data) and schema-based inference (applying static domain rules to deduce operational status). To tackle this challenge, we propose NOTAM-Evolve, a self-evolving framework that enables a large language model (LLM) to autonomously master complex NOTAM interpretation. Leveraging a knowledge graph-enhanced retrieval module for data grounding, the framework introduces a closed-loop learning process where the LLM progressively improves from its own outputs, minimizing the need for extensive human-annotated reasoning traces. In conjunction with this framework, we introduce a new benchmark dataset of 10,000 expert-annotated NOTAMs. Our experiments demonstrate that NOTAM-Evolve achieves a 30.4% absolute accuracy improvement over the base LLM, establishing a new state of the art on the task of structured NOTAM interpretation.

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arXiv2025

Near-Field Integrated Sensing and Communications for Secure UAV Networks

A novel near-field integrated sensing and communications framework for secure unmanned aerial vehicle (UAV) networks with high time efficiency is proposed. A ground base station (GBS) with large aperture size communicates with one communication UAV (C-UAV) under the existence of one eavesdropping UAV (E-UAV), where the artificial noise (AN) is employed for both jamming and sensing purpose. Given that the E-UAV's motion model is unknown at the GBS, we first propose a near-field localization and trajectory tracking scheme. Specifically, exploiting the variant Doppler shift observations over the spatial domain in the near field, the E-UAV's three-dimensional (3D) velocities are estimated from echo signals. To provide the timely correction of location prediction errors, the extended Kalman filter (EKF) is adopted to fuse the predicted states and the measured ones. Subsequently, based on the real-time predicated location of the E-UAV, we further propose a joint GBS beamforming and C-UAV trajectory design scheme for maximizing the instantaneous secrecy rate, while guaranteeing the sensing accuracy constraint. To solve the resultant non-convex problem, an alternating optimization approach is developed, where the near-field GBS beamforming and the C-UAV trajectory design subproblems are iteratively solved by exploiting the successive convex approximation method. Finally, our numerical results unveil that: 1) the E-UAV's 3D velocities and location can be accurately estimated in real time with our proposed framework by exploiting the near-field spherical wave propagation; and 2) the proposed framework achieves superior secrecy rate compared to benchmark schemes and closely approaches the performance when the E-UAV trajectory is perfectly known.

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arXiv2025

Movable-Element STARS-Aided Secure Communications

A novel movable-element (ME) enabled simultaneously transmitting and reflecting surface (ME-STARS)-aided secure communication system is investigated. Against the full-space eavesdropping, MEs are deployed at the STARS for enhancing the physical layer security by exploiting higher spatial degrees of freedom. Specifically, a sum secrecy rate maximization problem is formulated, which jointly optimizes the passive beamforming and the MEs positions at the ME-STARS, as well as the active beamforming at the base station. To solve the resultant non-convex optimization problem involving highly-coupled variables, an alternating optimization-based iterative algorithm is developed, decomposing the original problem into three subproblems. In particular, for the MEs position optimization subproblem, a gradient ascent algorithm is employed to iteratively refine the MEs' locations within the confined region. Moreover, the the active and passive beamforming subproblems are solved by employing successive convex approximation. Numerical results unveil that: 1) ME-STARS significantly improves the secrecy performance compared to the conventional STARS with fixed-position elements; and 2) The secrecy rate achieved by the ME-STARS gets saturated within limited movable region size.

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arXiv2025

RIS-Assisted Beamfocusing in Near-Field IoT Communication Systems: A Transformer-Based Approach

The massive number of antennas in extremely large aperture array (ELAA) systems shifts the propagation regime of signals in internet of things (IoT) communication systems towards near-field spherical wave propagation. We propose a reconfigurable intelligent surfaces (RIS)-assisted beamfocusing mechanism, where the design of the two-dimensional beam codebook that contains both the angular and distance domains is challenging. To address this issue, we introduce a novel Transformer-based two-stage beam training algorithm, which includes the coarse and fine search phases. The proposed mechanism provides a fine-grained codebook with enhanced spatial resolution, enabling precise beamfocusing. Specifically, in the first stage, the beam training is performed to estimate the approximate location of the device by using a simple codebook, determining whether it is within the beamfocusing range (BFR) or the none-beamfocusing range (NBFR). In the second stage, by using a more precise codebook, a fine-grained beam search strategy is conducted. Experimental results unveil that the precision of the RIS-assisted beamfocusing is greatly improved. The proposed method achieves beam selection accuracy up to 97% at signal-to-noise ratio (SNR) of 20 dB, and improves 10% to 50% over the baseline method at different SNRs.

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arXiv2025

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.

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arXiv2025

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.

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arXiv2025

Interference-Robust Broadband Rapidly-Varying MIMO Communications: A Knowledge-Data Dual Driven Framework

A novel time-efficient framework is proposed for improving the robustness of a broadband multiple-input multiple-output (MIMO) system against unknown interference under rapidly-varying channels. A mean-squared error (MSE) minimization problem is formulated by optimizing the beamformers employed. Since the unknown interference statistics are the premise for solving the formulated problem, an interference statistics tracking (IST) module is first designed. The IST module exploits both the time- and spatial-domain correlations of the interference-plus-noise (IPN) covariance for the future predictions with data training. Compared to the conventional signal-free space sampling approach, the IST module can realize zero-pilot and low-latency estimation. Subsequently, an interference-resistant hybrid beamforming (IR-HBF) module is presented, which incorporates both the prior knowledge of the theoretical optimization method as well as the data-fed training. Taking advantage of the interpretable network structure, the IR-HBF module enables the simplified mapping from the interference statistics to the beamforming weights. The simulations are executed in high-mobility scenarios, where the numerical results unveil that: 1) the proposed IST module attains promising prediction accuracy compared to the conventional counterparts under different snapshot sampling errors; and 2) the proposed IR-HBF module achieves lower MSE with significantly reduced computational complexity.

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arXiv2025

Waveguide Division Multiple Access for Pinching-Antenna Systems (PASS)

A novel concept of waveguide division multiple access (WDMA) is proposed for multi-user pinching-antenna systems (PASS). The key principle of WDMA is to allocate each user with a dedicated waveguide, which is regarded as a new type of radio resources, so as to facilitate multi-user communications. By adjusting the activation positions of pinching antennas (PAs) over each waveguide, the pinching beamforming can be exploited for intended user signal enhancement and inter-user interference mitigation. Considering both ideal continuous and practical discrete PA position activation schemes, a joint power allocation and pinching beamforming optimization problem is formulated for the maximization of the sum rate. An alternating optimization-based algorithm is developed to address the formulated nonconvex problem. For solving the power allocation subproblem, the successive convex approximation method is invoked. For the pinching beamforming design subproblem, a penalty-based gradient ascent algorithm is first developed for the continuous PA activation case. Then, for the discrete PA activation case, a matching theory-based algorithm is proposed to achieve the near-optimal performance but with a low complexity. Numerical results unveil that: 1) For both continuous and discrete activation cases, PASS can achieve a significant performance gain over conventional fixed-position antenna systems; 2) the proposed WDMA can effectively underpin multi-user communications with the near orthogonality in free space achieved by the pinching beamforming; and 3) the performance gap between the discrete and continuous activation cases can be significantly alleviated with practically feasible numbers of PA candidate positions.

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arXiv2024

Exploiting Movable-Element STARS for Wireless Communications

A novel movable-element enabled simultaneously transmitting and reflecting surface (ME-STARS) communication system is proposed, where ME-STARS elements positions can be adjusted to enhance the degress-of-freedom for transmission and reflection. For each ME-STARS operating protocols, namely energy-splitting (ES), mode switching (MS), and time switching (TS), a weighted sum rate (WSR) maximization problem is formulated to jointly optimize the active beamforming at the base station (BS) as well as the elements positions and passive beamforming at the ME-STARS. An alternative optimization (AO)-based iterative algorithm is developed to decompose the original non-convex problem into three subproblems. Specifically, the gradient descent algorithm is employed for solving the ME-STARS element position optimization subproblem, and the weighted minimum mean square error and the successive convex approximation methods are invoked for solving the active and passive beamforming subproblems, respectively. It is further demonstrated that the proposed AO algorithm for ES can be extended to solve the problems for MS and TS. Numerical results unveil that: 1) the ME-STARS can significantly improve the WSR compared to the STARS with fixed position elements and the conventional reconfigurable intelligent surface with movable elements, thanks to the extra spatial-domain diversity and the higher flexibility in beamforming; and 2) the performance gain of ME-STARS is significant in the scenarios with larger number of users or more scatterers.

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arXiv2023

Multiple-Antenna Aided Aeronautical Communications in Air-Ground Integrated Networks: Channel Estimation, Reliable Transmission, and Multiple Access

To provide seamless coverage during all flight phases, aeronautical communications systems (ACS) have to integrate space-based, air-based, as well as ground-based platforms to formulate aviation-oriented space-air-ground integrated networks (SAGINs). In continental areas, L-band aeronautical broadband communications (ABC) are gaining popularity for supporting air traffic management (ATM) modernization. However, L-band ABC faces the challenges of spectrum congestion and severe interference due to the legacy systems. To circumvent these, we propose a novel multiple-antenna aided L-band ABC paradigm to tackle the key issues of reliable and high-rate air-to-ground (A2G) transmissions. Specifically, we first introduce the development roadmap of the ABC. Furthermore, we discuss the peculiarities of the L-band ABC propagation environment and the distinctive challenges of the associated multiple-antenna techniques. To overcome these challenges, we propose an advanced multiple-antenna assisted L-band ABC paradigm from the perspective of channel estimation, reliable transmission, and multiple access. Finally, we shed light on the compelling research directions of the aviation component of SAGINs.

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arXiv2021

UAV Deployment, Device Scheduling and Resource Allocation for Energy-Efficient UAV-Aided IoT Networks with NOMA

This article investigates the energy efficiency issue in non-orthogonal multiple access (NOMA)-enhanced Internet-of-Things (IoT) networks, where a mobile unmanned aerial vehicle (UAV) is exploited as a flying base station to collect data from ground devices via the NOMA protocol. With the aim of maximizing network energy efficiency, we formulate a joint problem of UAV deployment, device scheduling and resource allocation. First, we formulate the joint device scheduling and spectrum allocation problem as a three-sided matching problem, and propose a novel low-complexity near-optimal algorithm. We also introduce the novel concept of `exploration' into the matching game for further performance improvement. By algorithm analysis, we prove the convergence and stability of the final matching state. Second, in an effort to allocate proper transmit power to IoT devices, we adopt the Dinkelbach's algorithm to obtain the optimal power allocation solution. Furthermore, we provide a simple but effective approach based on disk covering problem to determine the optimal number and locations of UAV's stop points to ensure that all IoT devices can be fully covered by the UAV via line-of-sight (LoS) links for the sake of better channel condition. Numerical results unveil that: i) the proposed joint UAV deployment, device scheduling and resource allocation scheme achieves much higher EE compared to predefined stationary UAV deployment case and fixed power allocation scheme, with acceptable complexity; and ii) the UAV-aided IoT networks with NOMA greatly outperforms the OMA case in terms of number of accessed devices.

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