Simultaneous Wireless Information And Power Transfer System Research Articles

Power-Efficient Resource Allocation for Active STAR-RIS-Aided SWIPT Communication Systems

Simultaneous wireless information and power transfer (SWIPT) has emerged as a pivotal technology in 6G, offering an efficient means of delivering energy to a large quantity of low-power devices while transmitting data concurrently. To address the challenges of obstructions, high path loss, and significant energy consumption associated with long-distance communication, this work introduces a novel alternating iterative optimization strategy. The proposed approach combines active simultaneous transmission and reflection of reconfigurable intelligent surfaces (STAR-RIS) with SWIPT to maximize spectrum efficiency and reduce overall system energy consumption. This method addresses the considerable energy demands inherent in SWIPT systems by focusing on reducing the power output from the base station (BS) while meeting key constraints: the communication rate for information receivers (IRs) and minimum energy levels for energy receivers (ERs). Given complex interactions between variables, the solution involves an alternating iterative optimization process. In the first stage of this approach, the passive beamforming variables are kept constant, enabling the use of semi-definite relaxation (SDR) and successive convex approximation (SCA) algorithms to optimize active beamforming variables. In the next stage, with active beamforming variables fixed, penalty-based algorithms are applied to fine-tune the passive beamforming variables. This iterative process continues, alternating between active and passive beamforming optimization, until the system converges on a stable solution. The simulation results indicated that the proposed system configuration, which leverages active STAR-RIS, achieves lower energy consumption and demonstrates improved performance compared to configurations utilizing passive RIS, active RIS, and passive STAR-RIS. This evidence suggests that the proposed approach can significantly contribute to advancing energy efficiency in 6G systems.

Optimizing energy harvesting with diversity in cooperative simultaneous wireless information and power transfer systems

SummaryRadio frequency (RF) energy harvesting (EH) for wireless networks provides a green and sustainable solution and offers an energy‐efficient system. It is most crucial for fulfilling the power requirement of the rising number of low‐powered wireless devices and achieving sustainable development goals (SDG). It ensures the longevity of devices in the network even at inaccessible remote locations. Such RF‐EH‐based mechanisms are utilized in simultaneous wireless information and power transfer (SWIPT) systems. Most of the prevailing studies have analyzed the SWIPT system over conventional fading channels. However, due to the higher rate requirements, the current paradigm shift in frequency usage shifts towards the GHz band, which also offers better EH efficiency. Hence, SWIPT system analysis over the channel that is suitable for mm‐wave signal propagation is dealt with in this study. This study evaluates SWIPT performance over fluctuating two‐ray (FTR) fading channel that is crucial since it provides the best fit for characterizing GHz signal and also provides a generalized framework for most of the conventional fading channels. This study presents new analytical results assuming time switch relaying (TSR) protocol with (i) amplify and forward (AF) and (ii) decode and forward (DF) relaying. The results are also analyzed for H branches maximal ratio combining (MRC) diversity technique and evaluated the diversity gain for both AF and DF relays. The effectiveness of the system is measured in terms of system outage probability (SOP) to envisage the reliability of SWIPT based system. This work presents the simulation and modeling of such system and its obtained results are validated by Monte Carlo simulations for their accuracy.

Joint optimal beam forming and resource allocation in intelligent reflecting surface aided wireless power transfer rate splitting multiple access system

SummaryThe intelligent reflecting surface (IRS) has recently become the most promising technology to achieve maximum beam‐forming gain with a simultaneous wireless information and power transfer (SWIPT) system. Many existing studies perform a single IRS deployment or utilize space division multiple access (SDMA) and non‐orthogonal multiple access (NOMA) schemes. However, the existing schemes face high time complexity and block signal transmission for larger indoor communications. Hence, this article introduces a dual IRS‐aided multiuser SWIPT system by implementing rate‐splitting multiple access (RSMA) systems. To enhance the minimum achievable rate and ensure the minimum harvesting energy (HE), this study proposes a joint successive convex approximation with an integrated optimization algorithm (SCA‐IOA). The proposed algorithm jointly optimizes the reflecting beam forming and power splitting (PS) coefficient of all the users effectively. The simulation results demonstrate the effectiveness of the proposed techniques and produce an outstanding performance for deploying dual IRS and implementing RSMA compared to traditional SDMA and NOMA systems.

Joint Beam-Forming Optimization for Active-RIS-Assisted Internet-of-Things Networks with SWIPT

Network energy resources are limited in communication systems, which may cause energy shortages in mobile devices at the user end. Active Reconfigurable Intelligent Surfaces (A-RIS) not only have phase modulation properties but also enhance the signal strength; thus, they are expected to solve the energy shortage problem experience at the user end in 6G communications. In this paper, a resource allocation algorithm for maximizing the sum of harvested energy is proposed for an active RIS-assisted Simultaneous Wireless Information and Power Transfer (SWIPT) system to solve the problem of low performance of harvested energy for users due to multiplicative fading. First, in the active RIS-assisted SWIPT system using a power splitting architecture to achieve information and energy co-transmission, the joint resource allocation problem is constructed with the objective function of maximizing the sum of the collected energy of all users, under the constraints of signal-to-noise ratio, active RIS and base station transmit power, and power splitting factors. Second, the considered non-convex problem can be turned into a standard convex problem by using alternating optimization, semi-definite relaxation, successive convex approximation, penalty function, etc., and then an alternating iterative algorithm for harvesting energy is proposed. The proposed algorithm splits the problem into two sub-problems and then performs iterative optimization separately, and then the whole is alternately optimized to obtain the optimal solution. Simulation results show that the proposed algorithm improves the performance by 45.2% and 103.7% compared to the passive RIS algorithm and the traditional without-RIS algorithm, respectively, at the maximum permissible transmitting power of 45 dBm at the base station.

Energy-efficient trajectory design for secure SWIPT systems assisted by UAV-IRS

Due to its controllable maneuverability, wide coverage, and low cost, unmanned aerial vehicle (UAV) has great potential in post-disaster rescue, cargo transport and emergency communication. Considering its limited onboard energy, energy-efficient UAV communication is a challenge. This research examines the security of simultaneous wireless information and power transfer (SWIPT) systems assisted by intelligent reflecting surfaces (IRS) and UAVs while considering the flight energy of rotary-wing UAVs. Specifically, an IRS is mounted on a UAV to enhance the quality of legitimate transmission, and artificial noise (AN) is introduced into the base station (BS) to reduce eavesdropping quality. The power splitting (PS) technology is adopted at ground devices (GDs) to simultaneously decode information and harvest energy. First, we jointly design the BS transmit beamforming, UAV-IRS phase shifts and trajectory/velocity as well as GDs PS ratio with the aim of maximizing the sum secrecy rate of all GDs. Then, an iterative algorithm is developed to address the formulated problem. In particular, additional variables are introduced to handle this complicated objective function, and the original problem is decoupled into multiple sub-problems, which can be solved alternately by invoking the successive convex approximation (SCA) and semidefinite relaxation (SDR) techniques. Finally, numerical results demonstrate that the proposed scheme exhibits a substantial performance in the security rate of SWIPT systems assisted by UAV-IRS, and its performance is improved by at least 12% compared to benchmark schemes at the flight energy budget ethr=5KJ and the number of reflecting elements Nr=25.

Energy-Efficiency Optimization for Mutual-Coupling-Aware Wireless Communication System Based on RIS-Enhanced SWIPT

The widespread deployment of the Internet of Things (IoT) is promoting interest in simultaneous wireless information and power transfer (SWIPT), the performance of which can be further improved by employing a reconfigurable intelligent surface (RIS). In this paper, we propose a novel RIS-enhanced SWIPT system built on an electromagnetic-compliant framework. The mutual-coupling effects in the whole system are presented explicitly. Moreover, the reconfigurability of RIS is no longer expressed by the reflection-coefficient matrix but by the impedances of the tunable circuit. For comparison, both the no-coupling and the coupling-awareness cases are discussed. In particular, the energy efficiency (EE) is maximized by cooperatively optimizing the impedance parameters of the RIS elements as well as the active beamforming vectors at the base station (BS). For the coupling-awareness case, the considered problem is split into several sub-problems and solved alternatively due to its nonconvexity. Firstly, it is transformed into a more solvable form by applying the Neuman series approximation, which can be resolved iteratively. Then an alternative optimization (AO) framework and semi-definite relaxation (SDR), successive convex approximation (SCA), and Dinkelbach’s algorithm are applied to solve each sub-problem decomposed from it. Owning to the similarity between the two cases, the no-coupling one can be viewed as a reduced form of the coupling case and thus solved through a similar approach. Numerical results reveal the influence of mutual-coupling effects on the EE, especially in the RIS with closely spaced elements. In addition, physical beam designs are presented to demonstrate how the RIS assists SWIPT through various reflecting states in different conditions.

Secrecy Energy Efficiency Maximization for Secure Unmanned-Aerial-Vehicle-Assisted Simultaneous Wireless Information and Power Transfer Systems

Unmanned aerial vehicle (UAV)-assisted simultaneous wireless information and power transfer (SWIPT) systems have recently gained significant attraction in internet-of-things (IoT) applications that have limited or no infrastructure. Specifically, the free mobility of UAVs in three-dimensional (3D) space allows us good-quality channel links, thereby enhancing the communication environment and improving performance in terms of achievable rates, latency, and energy efficiency. Meanwhile, IoT devices can extend their battery life by harvesting the energy following the SWIPT protocol, which leads to an increase in the overall system lifespan. In this paper, we propose a secure UAV-assisted SWIPT system designed to optimize the secrecy energy efficiency (SEE) of a ground network, wherein a base station (BS) transmits confidential messages to an energy-constrained device in the presence of a passive eavesdropper. Here, we employ a UAV acting as a helper node to improve the SEE of the system and to aid in the energy harvesting (EH) of the battery-limited ground device following the SWIPT protocol. To this end, we formulate the SEE maximization problem by jointly optimizing the transmit powers of the BS and UAV, the power-splitting ratio for EH operations, and the UAV’s flight path. The solution is obtained via a proposed algorithm that leverages successive convex approximation (SCA) and Dinkelbach’s method. Through simulations, we corroborate the feasibility and effectiveness of the proposed algorithm compared to conventional partial optimization approaches.

Second Order Rectified Parallel Factor Model Based Cascaded Channel Estimation in IRS-Assisted SWIPT System

This paper investigates cascaded channel estimation in intelligent reflecting surface (IRS)-assisted simultaneous wireless information and power transfer (SWIPT) system. Multiple-input multiple-output (MIMO) transceiver structures combined with transmitter active beamforming and IRS passive beamforming are studied. Cascaded channel estimation is transformed into sparse signal reconstruction problem, and compressed sensing (CS) is applied to solve this problem. Only a small amount of training overhead provides reliable channel estimation gains as well as better beamforming gains. Second order rectified parallel factor (PARAFA) model is implemented in IRS-assisted SWIPT system, which is described by tensor decomposition method. The received signal can be represented by PARAFA model with algebraic structure and IRS phase shift. Two cascaded channel estimation approaches, namely, bilinear alternating least squares (BALS) and least squares Khatri-Rao factorization (LSKRF), are proposed respectively. Simulation results show that, compared with orthogonal matching pursuit (OMP) approach, the proposed BALS cascaded channel estimation approach obtains better normalized mean square error (NMSE) and convergence performance with the least parameter constraints.

High-performance cost efficient simultaneous wireless information and power transfers deploying jointly modulated amplifying programmable metasurface

Programmable metasurfaces present significant capabilities in manipulating electromagnetic waves, making them a promising candidate for simultaneous wireless information and power transfer (SWIPT), which has the potential to enable sustainable wireless communication in complex electromagnetic environments. However, challenges remain in terms of maximum power transmission distance and stable phase manipulation with high-power scattered waves. Additionally, waveform limitations restrict average scattered power and rectifier conversion efficiency, affecting data transmission rates and energy transmission distance. Here we show an amplifying programmable metasurface (APM) and a joint modulation method to address these challenges. The APM mitigates the peak-to-average power ratio and improves maximum power, phase response stability, average output power, and rectifier conversion efficiency. Through experimental validation, we demonstrate the feasibility of the SWIPT system, showcasing simultaneous LED array powering and movie video transmission. This innovative SWIPT system holds promise for diverse applications, including 6 G wireless communications, IoT, implanted devices, and cognitive radio networks.

RETRACTED: Enhancing UAV Communication Links with Reconfigurable Intelligent Surfaces

Reconfigurable intelligent surfaces (RIS) have emerged as a prominent and widely debated solution to enhance the energy efficiency of wireless communications. This article explores the potential of combining RIS with unmanned aerial vehicles (UAVs)-RIS, to provide on-demand deployment services in dynamic environments. However, the energy limitations of battery-powered UAVs can curtail the advantages of UAV-RIS systems. To address this challenge and enhance the durability of UAV-RIS deployments, we introduce an energy harvesting technique for simultaneous wireless information and power transfer (SWIPT) coupled with optimized resource allocation and energy harvesting from incoming radio frequency (RF) signals. In contrast to previous research, our approach involves the division of passive reflected arrays across geometric space, facilitating simultaneous information transfer and energy harvesting. Additionally, we are developing deep Q-network (DQN) and deep deterministic policy gradient (DDPG) techniques to dynamically allocate UAV-RIS resources in both temporal and spatial dimensions. This allocation maximizes the overall harvested energy while upholding communication quality for every user. Our simulation results conclusively demonstrate the substantial superiority of the proposed UAV-RIS SWIPT system over the benchmark.

Energy Optimization for IRS-Aided SWIPT Under Imperfect Cascaded Channels

In this paper, intelligent reflecting surface is deployed in simultaneous wireless information and power transfer (SWIPT) system to improve the energy harvesting performance. We investigate the robust beamforming design considering the impact of the imperfect cascaded channels. We maximize the minimum received energy among all energy receivers to ensure fairness, while guaranteeing the worst-case information receivers rate requirement. To address with the coupling effect of multiple variables in the optimization problem, the alternate optimization method is utilized to decouple the optimization problem into two sub-problems, and the successive convex approximation and the semidefinite relaxation methods are used to solve the sub-problems. Simulation results reveal that employing IRS into SWIPT system can enhance the energy harvest performance, Additionally, our proposed two algorithms converges rapidly and can guarantee the robustness of the system.

A Neurodynamic Approach for SWIPT Power Splitting Optimization

Simultaneous wireless information and power transfer (SWIPT) systems using energy from RF signals can effectively solve the energy shortage of wireless devices. However, the existing SWIPT optimization methods using numerical algorithms are difficult to solve the non-convex problem and to adapt to the dynamic communication circumstances. In this paper, a duplex neurodynamic optimization method is used to address the SWIPT system’s power partitioning issue. The information rate maximization problem of the SWIPT system is framed as a biconvex problem. A duplex recurrent neural network is used to concurrently execute local search and update the initial state of the neural network by a particle swarm optimization method to get the global optimum. The experimental results demonstrate that the duplex neurodynamic-based SWIPT system maximizes information rate while satisfying the minimal harvesting energy requirement in a variety of channel states.

Latency-Aware Multi-Antenna SWIPT System With Battery-Constrained Receivers

Power splitting (PS) based simultaneous wireless information and power transfer (SWIPT) is considered in a multi-user multiple-input-single-output broadcast scenario. Specifically, we focus on jointly configuring the transmit beamforming vectors and receive PS ratios to minimize the total transmit energy of the base station under the user-specific latency and energy harvesting (EH) requirements. The battery depletion phenomenon is avoided by preemptively incorporating information regarding the receivers' battery state and EH fluctuations into the resource allocation design. The resulting time-average sum-power minimization problem is temporally correlated, non-convex (including mutually coupled latency-battery queue dynamics), and in general intractable. We use the Lyapunov optimization framework and derive a dynamic control algorithm to transform the original problem into a sequence of deterministic and independent subproblems, which are then solved via two alternative approaches: i) semidefinite relaxation combined with fractional programming, and ii) successive convex approximation. Furthermore, we design a low-complexity closed-form iterative algorithm exploiting the Karush-Kuhn-Tucker optimality conditions for a specific scenario with delay bounded batteryless receivers. Numerical results provide insights on the robustness of the proposed design to realize an energy-efficient SWIPT system while ensuring latency and EH requirements in a time dynamic mobile access network.

RIS-Aided SCMA-Based SWIPT Systems: Design and Optimization

The amalgamation of sparse code multiple access (SCMA) and simultaneous wireless information and power transfer (SWIPT) is envisioned to be a promising solution to massive connectivity while providing both information and power to myriads of wireless machines and sensors in Internet-of-Things (IoT) application. However, the benefit of the SCMA-based SWIPT system has not been fully exploited yet, especially when the communications link is hostile. Fortunately, the propagation-induced impairment can be mitigated by the emerging technique of reconfigurable intelligent surface (RIS). In this paper, we investigate the beneficial role of RIS in SCMA-based SWIPT systems, where <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$K$</tex-math></inline-formula> single-antenna information receivers and one signal-antenna energy receiver are served by a multiple-antenna base station over <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$J$</tex-math></inline-formula> orthogonal subcarriers with the aid of RIS. We propose transmit power minimization algorithms for both <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i)</i> the perfect and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ii)</i> the imperfect channel state information (CSI) scenarios, by jointly optimizing the codebook assignment, the BS active beamforming, as well as RIS reflection coefficients, relying on advanced techniques both of alternating optimization and of successive convex approximations, and on the robust design framework. Furthermore, we compare and evaluate the detection performance of the system considered. The numerical results demonstrate that our proposed RIS-aided SCMA-based SWIPT system significantly outperforms the conventional SCMA-based SWIPT system without RIS and is capable of adapting to the imperfect full channel estimation results.

Transmission Design for Active RIS-Aided Simultaneous Wireless Information and Power Transfer

Reconfigurable intelligent surface (RIS) is a revolutionary technology to enhance both the spectral efficiency and energy efficiency of wireless communication systems. However, most of the existing contributions mainly focused on the study of passive RIS, which suffers from the “double fading” effect. On the other hand, active RIS, which is equipped with amplifiers, can effectively address this issue. In this letter, we propose an active RIS-aided simultaneous wireless information and power transfer (SWIPT) system. Specifically, we maximize the weighted sum rate of the information receivers, subject to the minimum power received at all energy receivers, amplification power constraint at the active RIS, and the maximum transmit power constraint at the base station (BS). By adopting alternating optimization framework, suboptimal solutions are obtained. Simulation results show that the active RIS-aided SWIPT system has higher performance gain with the same power budget.

Energy Efficiency Optimization for MISO-NOMA SWIPT System with Heterogeneous QoS Requirements

This letter solves the energy efficiency optimization problem for the simultaneous wireless information and power transfer (SWIPT) systems with non-orthogonal multiple access (NOMA), multiple input single output (MISO) and power-splitting structures, where each user may have different individual quality of service (QoS) requirements about information and energy. Nonlinear energy harvesting model is used. Alternate optimization approach is adopted to find the solution, which shows a fast convergence behavior. Simulation results show the proposed scheme has higher energy efficiency than existing dual-layer iteration and throughput maximization methods.

Proportional fairness secrecy beamforming for massive MIMO-SWIPT systems with low-resolution ADCs

Simultaneous wireless information and power transfer (SWIPT) technology is one of the solutions to the energy shortage problem in Massive multiple-input and multiple-output (MIMO) systems, while the low-resolution analog-to-digital convertor (ADC) is a potential way to significantly reduce the power consumption of radio frequency circuits in Massive MIMO enabled SWIPT systems. In this paper, we focus on the secrecy transmission maximization problem for Massive MIMO-SWIPT systems over Nakagami-m fading channels, where a low-resolution ADC quantization model and a non-linear energy harvester are exploited. By considering proportional fairness, a joint beamforming design and power allocation problem are proposed to achieve the sum logarithmic secrecy rates. To tackle the non-convex maximization problem, the suboptimal solutions of the beamforming design and power allocation are respectively obtained based on a successive convex approximation and a semidefinite relaxation. Numerical results demonstrate the effectiveness of the proposed joint optimization scheme.

Optimization for IRS-Assisted MIMO-OFDM SWIPT System With Nonlinear EH Model

Simultaneous wireless information and power transfer (SWIPT) has emerged as an appealing solution to prolonging the lifetime of low-power Internet of Things (IoT) networks. Meanwhile, an intelligent reflecting surface (IRS) can reconstruct a favorable wireless propagation environment for IoT terminals to achieve high spectrum and energy efficiencies. To take full advantage of these two technologies, this article studies the optimization of an IRS-assisted multiple-input and multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) SWIPT system with nonlinear energy harvesting (EH) model. In particular, we aim to maximize the achievable data rate by jointly designing the transmit precoding matrices, the IRS matrix, as well as the power splitting (PS) ratio subject to the transmit power and harvested power constraints. Since the formulated problem is highly nonconvex, we develop an alternating optimization (AO)-based algorithm to find a high-quality suboptimal solution. Moreover, we further design a heuristic algorithm based on a two-stage optimization strategy to reduce the computational complexity. Simulation results verify that the proposed AO-based algorithm can significantly improve the achievable data rate compared to conventional benchmarks, and the proposed heuristic low-complexity algorithm can achieve comparable performance to the AO-based algorithm.

Proportional Fair Trajectory Design and Resource Allocation for UAV-Assisted SWIPT System

In this study, we investigate the proportional fair trajectory design and resource allocation for an unmanned-aerial-vehicle (UAV)-assisted simultaneous wireless information and power transfer (SWIPT) system, where multiple ground nodes (GNs) receive information and harvest energy from the signal transmitted by the UAV using a power-splitting (PS) policy. With this system, we aim to maximize the sum of the logarithmic average spectral efficiency (SE) of the GNs while guaranteeing the average harvested energy requirement to improve the average SE and user fairness simultaneously. To deal with the nonconvexity of the optimization problem, we adopt the quadratic transform and first-order Taylor expansion, proposing an iterative algorithm to find the optimal trajectory and transmit the power of the UAV and the PS ratio of the GNs. Through simulations, we confirm that the proposed scheme achieves a higher average SE compared with the conventional baseline schemes and ensures a level of user fairness similar to that of the state-of-the-art baseline scheme.

Rate-Splitting Multiple Access in a MISO SWIPT System Assisted by an Intelligent Reflecting Surface

Rate-splitting multiple access (RSMA) and the intelligent reflecting surface (IRS) are novel technologies to improve spectrum and energy efficiencies in multi-antenna networks. In this paper, we investigate a multi-user multiple-input single-output (MISO) simultaneous wireless information and power transfer (SWIPT) system assisted with an IRS and using RSMA. In particular, the IRS assists with data and energy transmission from the base station (BS) to power-splitting (PS) users under a non-linear energy harvesting (EH) model. Our objective is to minimize the transmission power subject to rate and EH requirements at the users. To solve the non-convex problem, we propose a bilevel programming problem in which a genetic algorithm is used to solve the outer optimization problem, and the inner optimization problem is addressed with the semidefinite relaxation (SDR) method. In addition, to study a practical scenario of imperfect channel state information (CSI), we consider a robust beamforming design based on imperfect cascade channels at the BS. Then, we propose a solution based on the S-procedure with the SDR technique. Simulation results show that our proposed RSMA-based scheme provides a significant reduction in transmission power compared to the space-division multiple access (SDMA) and non-orthogonal multiple access (NOMA) methods under perfect and imperfect CSI.