A simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) assisted simultaneous wireless information and power transfer (SWIPT) system is investigated. Both active and passive STAR-RISs are considered. Passive STAR-RISs can be cost-efficiently fabricated to large aperture sizes with significant near-field regions, but the design flexibility is limited by the coupled phase-shifts. Active STAR-RISs can further amplify signals and have independent phase-shifts, but their aperture sizes are relatively small due to the high cost. To characterize and compare their performance, a power consumption minimization problem is formulated by jointly designing the beamforming at the access point (AP) and the STAR-RIS, subject to both the power and information quality-of-service requirements. To solve the resulting highly-coupled non-convex problem, the original problem is first decomposed into simpler subproblems and then an alternating optimization framework is proposed. For the passive STAR-RIS, the coupled phase-shift constraint is tackled by employing a vector-driven weighted penalty method. While for the active STAR-RIS, the independent phase-shift is optimized with AP beamforming via matrix-driven semidefinite programming, and the amplitude matrix is updated using convex optimization techniques in each iteration. Numerical results show that: 1) given the same aperture sizes, the active STAR-RIS exhibits superior performance over the passive one when the aperture size is small, but the performance gap decreases with the increase in aperture size; and 2) given identical power budgets, the passive STAR-RIS is generally preferred, whereas the active STAR-RIS typically suffers performance loss for balancing between the hardware power and the amplification power.

Event Causality Identification (ECI) aims to determine whether a causal relationship exists between two events within a document. Most existing approaches rely on pre-constructed event graphs to capture event relationships. However, these methods often neglect the semantic context of events in the original document and struggle to model complex relationships using a single event graph. We propose that event relationship identification should progress from simpler to more complex relationships, with a strong reliance on global semantic information. To address these challenges, we propose an Iterative Progressive Reasoning Network for ECI. First, we introduce an Event Semantic-Aware Module, which captures the global semantic context of events in the document. Then, we design an Iterative Attention Graph Fusion Module, inspired by Bayesian reasoning, that dynamically generates event association graphs to progressively refine event relationships. This approach enables the model to perform high-order reasoning while maintaining semantic coherence across the document. Additionally, a Differential Regularizer constrains the receptive fields of both the semantic-aware and reasoning modules, ensuring they focus on distinct aspects of event relationships. Our experimental results demonstrate that the proposed method outperforms existing state-of-the-art approaches on two benchmark datasets, EventStoryLine and Causal-TimeBank.

A simultaneously transmitting and reflecting reconfigurable-intelligent-surface (STAR-RIS)-assisted wireless powered communication network (WPCN) is proposed, where two energy-limited devices first harvest energy from a hybrid access point (HAP) and then use that energy to transmit information back. To fully eliminate thedoubly-near-far-effect in WPCNs, two STAR-RIS operating protocol-driven transmission strategies, namely energy splitting nonorthogonal multiple access (ES-NOMA) and time switching time division multiple access (TS-TDMA) are proposed. For each strategy, the corresponding optimization problem is formulated to maximize the minimum throughput by jointly optimizing time allocation, user transmit power, active HAP beamforming, and passive STAR-RIS beamforming. For ES-NOMA, the resulting intractable problem is solved via a two-layer algorithm, which exploits the 1-D search and block coordinate descent methods in an iterative manner. For TS-TDMA, the optimal active beamforming and passive beamforming are first determined according to the maximum-ratio transmission beamformer. Then, the optimal solution of the time allocation variables is obtained by solving a standard convex problem. Numerical results show that: 1) the STAR-RIS can achieve considerable performance improvements for both strategies compared to the conventional RIS; 2) TS-TDMA is preferred for single-antenna scenarios, whereas ES-NOMA is better suited for multiantenna scenarios; and 3) the superiority of ES-NOMA over TS-TDMA is enhanced as the number of STAR-RIS elements increases.

A novel movable-element simultaneously transmitting and reflecting surface (ME-STARS)-assisted near-field wideband communication framework is proposed. In particular, the position of each STARS element can be adjusted to combat the significant wideband beam squint issue in the near field instead of using costly true-time delay components. Four practical ME-STARS element movement modes are proposed, namely region-based (RB), horizontal-based (HB), vertical-based (VB), and diagonal-based (DB) modes. Based on this, a near-field wideband multi-user downlink communication scenario is considered, where a sum rate maximization problem is formulated by jointly optimizing the base station (BS) precoding, ME-STARS beamforming, and element positions. To solve this intractable problem, a two-layer algorithm is developed. For the inner layer, the block coordinate descent optimization framework is utilized to solve the BS precoding and ME-STARS beamforming in an iterative manner. For the outer layer, the particle swarm optimization-based heuristic search method is employed to determine the desired element positions. Numerical results show that: 1) the ME-STARSs can effectively address the beam squint for near-field wideband communications compared to conventional STARSs with fixed element positions; 2) the RB mode achieves the most efficient beam squint effect mitigation, while the DB mode achieves the best trade-off between performance gain and hardware overhead; and 3) an increase in the number of ME-STARS elements or BS subcarriers substantially improves the system performance.

A large-scale simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) assisted simultaneous wireless information and power transfer (SWIPT) system is investigated. In contrast to conventional single-field (near or far) models, a mixed near- and far-field SWIPT is considered, where a STAR-RIS with coupled phase-shift is utilized to support near-field energy devices and far-field information users. Under this setup, a transmit power minimization problem is formulated by jointly designing the access point beamforming and the STARRIS beamforming, subject to the quality of service requirements for power and information. To solve this intractable problem, a weight penalty based alternating optimization algorithm is proposed. Finally, numerical results validate the effectiveness of the proposed scheme. Moreover, the coupled phase-shift associated with the STAR-RIS has a more pronounced effect on far-field information users than on near-field energy devices.

A novel downlink hybrid reconfigurable intelligent surface (RIS) transmitter enabled multi-user communication framework is studied. Specifically, elements on the RIS can flexibly switch between active and passive modes to deliver information to multiple users. The system energy efficiency is maximized by jointly optimizing RIS element mode scheduling, transmission beamforming vector, and power allocation coefficients, subject to the user's individual rate requirement and the maximum RIS amplification power constraint. We first exploit the Dinkelbach approach to transform the original mixed-integer nonlinear programming problem into a nonfractional optimization problem. Then, an alternating optimization based algorithm is developed to address this problem. In particular, the optimal RIS element operating mode is determined by the exhaustive search method. Then, the RIS beamforming and power allocation coefficients are alternately designed. Finally, numerical results show that a significant performance improvement can be reaped by the proposed scheme compared to the baseline schemes employing full-active RIS or full-passive RIS.

A novel hybrid active-passive reconfigurable intelligent surface (RIS) transmitter enabled downlink multi-user communication system is investigated. Specifically, RISs are exploited to serve as transmitter antennas, where each element can flexibly switch between active and passive modes to deliver information to multiple users. The system energy efficiency (EE) maximization problem is formulated by jointly optimizing the RIS element scheduling and beamforming coefficients, as well as the power allocation coefficients, subject to the user’s individual rate requirement and the maximum RIS amplification power constraint. Using the Dinkelbach relaxation, the original mixed-integer nonlinear programming problem is transformed into a nonfractional optimization problem with a two-layer structure, which is solved by the alternating optimization approach. In particular, an exhaustive search method is proposed to determine the optimal operating mode for each RIS element. Then, the RIS beamforming and power allocation coefficients are properly designed in an alternating manner. To overcome the potentially high complexity caused by exhaustive searching, we further develop a joint RIS element mode and beamforming optimization scheme by exploiting the Big-M formulation technique. Numerical results validate that: 1) The proposed hybrid RIS scheme yields higher EE than the baseline multi-antenna schemes employing fully active/passive RIS or conventional radio frequency chains; 2) Both proposed algorithms are effective in improving the system performance, especially the latter can achieve precise design of RIS elements with low complexity; and 3) For a fixed-size hybrid RIS, maximum EE can be reaped by setting only a minority of elements to operate in the active mode.

A simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) assisted simultaneous wireless information and power transfer (SWIPT) system is proposed. More particularly, an STAR-RIS is deployed to assist in the information/power transfer from a multi-antenna access point (AP) to multiple single-antenna information users (IUs) and energy users (EUs), where two practical STAR-RIS operating protocols, namely energy splitting (ES) and time switching (TS), are employed. Under the imperfect channel state information (CSI) condition, a multi-objective optimization problem (MOOP) framework, that simultaneously maximizes the minimum data rate and minimum harvested power, is employed to investigate the fundamental rate-energy trade-off between IUs and EUs. To obtain the optimal robust resource allocation strategy, the MOOP is first transformed into a single-objective optimization problem (SOOP) via the ϵ-constraint method, which is then reformulated by approximating semi-infinite inequality constraints with the S-procedure. For ES, an alternating optimization (AO)-based algorithm is proposed to jointly design AP active beamforming and STAR-RIS passive beamforming, where a penalty method is leveraged in STAR-RIS beamforming design. Furthermore, the developed algorithm is extended to optimize the time allocation policy and beamforming vectors in a two-layer iterative manner for TS. Numerical results reveal that: 1) deploying STAR-RISs achieves a significant performance gain over conventional RISs, especially in terms of harvested power for EUs; 2) the ES protocol obtains a better user fairness performance when focusing only on IUs or EUs, while the TS protocol yields a better balance between IUs and EUs; 3) the imperfect CSI affects IUs more significantly than EUs, whereas TS can confer a more robust design to attenuate these effects.

An integrated simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RISs) and full-duplex (FD) relay aided downlink system is investigated. We formulate an optimization problem to maximize the downlink system achievable sum rate, by jointly optimizing the receive beamforming at the relay, the transmit beamforming at both the base station and the relay, and the passive beamforming at the STAR-RIS. To tackle the formulated non-convex problem, we decompose this problem into three subproblems by invoking alternating optimization. In particular, a penalty-based algorithm is developed to solve each subproblem via successive convex approximation technique. Finally, numerical results reveal that the proposed scheme can achieve significant performance gains compared to baselines.

A simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) assisted simultaneous wireless information and power transfer (SWIPT) framework is proposed. More particularly, an STAR-RIS is deployed to assist in SWIPT from a multi-antenna access point (AP) to multiple single-antenna information users (IUs) and energy users (EUs). Due to the near-passive operation of the STAR-RIS, a more practical setup under the assumption of imperfect channel state information is investigated. The max-min fairness optimization problem is formulated to maximize the minimum power harvested by EUs, subject to the signal-to-interference-plus-noise ratio (SINR) constraints for IUs. To tackle this non-convex problem, an alternating optimization (AO) based algorithm is proposed for robust beamforming design. We first approximate the semiinfinite inequality constraints with S-procedure, then the AP active beamforming and the STAR-RIS passive beamforming are alternatively designed, where a penalty based approach is leveraged for STAR-RIS reconfiguration. Numerical results demonstrate that: i) the significant performance gains can be achieved by the proposed scheme over the baseline schemes; and ii) more STAR-RIS elements and higher SINR requirements weaken the robustness of the EU performance in terms of energy harvesting.

A novel coexisting passive reconfigurable intelligent surface (RIS) and active decode-and-forward (DF) relay assisted non-orthogonal multiple access (NOMA) transmission framework is proposed. In particular, two communication protocols are conceived, namely Hybrid NOMA (H-NOMA) and Full NOMA (F-NOMA). Based on the proposed two protocols, both the sum rate maximization and max-min rate fairness problems are formulated for jointly optimizing the power allocation at the access point and relay as well as the passive beamforming design at the RIS. To tackle the non-convex problems, an alternating optimization (AO) based algorithm is first developed, where the transmit power and the RIS phase-shift are alternatingly optimized by leveraging the two-dimensional search and rank-relaxed difference-of-convex (DC) programming, respectively. Then, a two-layer penalty based joint optimization (JO) algorithm is developed to jointly optimize the resource allocation coefficients within each iteration. Finally, numerical results demonstrate that: i) the proposed coexisting RIS and relay assisted transmission framework is capable of achieving a significant user performance improvement than conventional schemes without RIS or relay; ii) compared with the AO algorithm, the JO algorithm requires less execution time at the cost of a slight performance loss; and iii) the H-NOMA and F-NOMA protocols are generally preferable for ensuring user rate fairness and enhancing user sum rate, respectively.

This paper investigates an integrated passive reconfigurable intelligent surface (RIS) and active relay assisted non-orthogonal multiple access (NOMA) system. To unleash the potential of distant user based on the downlink NOMA protocol, we identify a two-stage transmission strategy. In both stages, RISs provide coverage for paired users by actively modifying the channel response, and in the second stage, we introduce a dedicated active relay to realize the communication between the base station (BS) and distant user. Our goal is to maximize the system sum rate by jointly optimizing the power allocation at the BS and the passive beamforming at the RIS. To tackle the formulated non-convex problem, we propose an alternating penalty-based based algorithm. In particular, for the RIS phase-shift reconfiguration, a difference-of-convex (DC) approach is utilized to accurately detect the feasibility of the rank-one constraint. Numerical results demonstrate that: i) the integrated transmission scheme outperforms other baseline schemes; ii) the proposed scheme is capable of significantly enhancing the performance of distant NOMA users.

This paper presents a hierarchical sliding mode control approach for the underactuated tethered system suffering from unknown external disturbances. Taking the three dimensional attitude information of the postcapture combination, the in-plane/out-of-plane angles, and length of the tether into consideration, the dynamics of the tethered system is constructed. Then, based on the dynamics, a hierarchical sliding mode controller is designed and stability of the closed system is guaranteed by rigorous verification. Simulation carried out on the tethered system demonstrates that the proposed control strategy achieves good control efficiencies.