Simultaneous Wireless Information And Power Transmission Research Articles

Simultaneous wireless information and power transmission‐based power transfer and energy prediction for efficient communication with golden Taylor sea lion optimization in wireless sensor network

SummaryWireless Sensor Network (WSN) is an emerging lower cost and resourceful solution, which enables controlled observation of the environment. The high amount of energy is required in wireless networks during the transmission of data. Here, Golden Ant Lion Whale Optimization (GALWO) and Golden Taylor Sea Lion Optimization (GTSLnO) techniques are presented for cluster head (CH) selection and prediction of neighbor nodes' age. The six stages performed in this work are setup, steady‐state, prediction, power transfer, communication or route discovery, and route maintenance stages. In the setup level, CH selection is carried out by GALWO, which is the combination of Ant Lion Whale Optimization (ALWO) with Golden Search Optimization (GSO). Moreover, ALWO is an integration of Ant Lion Optimizer (ALO) with the Whale Optimization Algorithm (WOA). In the steady state, the distance, energy, delay, throughput, and trust update are considered as objective functions. In the prediction stage, the Deep Convolutional Neural Network (Deep CNN) is utilized for age prediction of neighbor nodes, wherein Deep CNN is tuned by employing GTSLnO. The GTSLnO is an incorporation of GSO and Taylor series with Sea Lion Optimization (SLnO). Then, the power transfer stage is done utilizing simultaneous wireless information and power transmission (SWIPT). Thereafter, the communication/route discovery stage is conducted for path selection through neighbor node, and lastly, the route maintenance stage is carried out. The GTSLnO–Deep CNN achieved a minimal delay of 0.089 s, maximal residual energy, throughput, and trust of 0.500 J, 98,843 kbps, and 0.452 for DoS attack.

High-Efficiency Moderate-Power Amplifier Using Packaged GaN Transistor With Improved Average PAE and Gain for Batteryless IoT Applications

One of the fundamental problems in power amplifier (PA) design is the mismatch between the optimum loads for maximum output power and maximum efficiency. This work demonstrates that a GaN transistor of choice can reduce such mismatch when operating at the minimum input RF power required ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$P_{\text {in}}$ </tex-math></inline-formula> ) to obtain its maximum output power. Furthermore, this work investigates the average power-added efficiency (PAE) degradation caused by the baseband terminations for high-efficient switch-mode class-E PAs. Our results show that the average PAE degradation mechanism of class-E PAs is similar to that of class-B ones, but some class-E solutions are more susceptible to the driving signal’s bandwidth. To clarify that, two class-E PAs were implemented using commercial package GaN transistors based on two different modes from the continuum of class-E solutions. Despite being driven by half of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$P_{\text {in}}$ </tex-math></inline-formula> typically employed by designers, the PAs have achieved a gain almost 3 dB higher than the state-of-the-art and excellent efficiency controlling only the second harmonic. Based on the obtained results, the proposed design strategy is believed to have a promising potential for developing high-efficiency simultaneous wireless information and power transmission (SWIPT) base stations for batteryless Internet of Things (IoT).

Array design for mm-wave UAV-assisted cooperative communications with simultaneous wireless information and power transmission

High performance UAV-assisted communications system using simultaneous wireless information and power transmission (SWIPT) in mm-wave band is presented. UAV is a moving relay powered from a ground source through a power-splitting mechanism. In mm-wave band we utilize antenna array to increase the antenna gain while keeping array size small and practical. The radiation pattern of the UAV antenna is continuously adjusted to peak towards the source and destination. Two array geometries, a line and a cross, are designed for UAV antenna. We achieve near optimal pattern, utilizing innovative low power switches instead of phase shifters which are high power consuming components and using them here defies the purpose. We maximize the end-to-end cooperative throughput by optimizing the UAV power profile, power-splitting ratio profile, antenna weights (0, 1), and UAV trajectory for amplify-and-forward (AF) protocol. We consider two cases. Case1: UAV transmits and receives data simultaneously along two predefined trajectories. The antenna weights for line and cross arrays are optimized utilizing genetic algorithm. The power profile and, power-splitting ratio profile are also optimized using the penalty method. Case2: UAV accumulates the data and power along an optimal trajectory until it reaches the vicinity of target, when it transmits data at high bit rate. Here we define the optimization of parameters mentioned in Case1, while at an optimal point along the trajectory, as sub-problem1, and finding the next optimal point as sub-problem2. Sub-problem1 is solved using the genetic algorithm and dual decomposition method. Sub-problem2 is then solved using successive concave optimization. The overall problem, i.e. cooperative throughput, is solved by reciprocal iteration over the two sub problems. The simulation results show the proposed mm-wave band cross array antenna and switches can overcome the high frequency propagation losses, hence, achieving higher power harvest and data rates. The achieved higher data throughput outperforms the conventional single antenna low frequency systems.

ICOS: A Deep Reinforcement Learning Scheme for Wireless-Charged MEC Networks

Computation offloading is an effective method in mobile edge computing (MEC) to relieve user equipment (UE) from the limited computation resource and battery capacity. Meanwhile, simultaneous wireless information and power transmission (SWIPT) can be applied to MEC to extend the operating time of the equipment. However, in multi-user network environment, diverse computation task requirements and changeable network channel states make it challenging to obtain offloading strategy timely and accurately. To address the issue, we propose an intelligent computation offloading scheme (iCOS) based on enhanced priority deep deterministic policy gradient (EPDDPG) algorithm to minimize the energy consumption of all the UEs by jointly optimizing the offloading decision, the central processing unit (CPU) frequency and the power split ratio in a dynamic SWIPT-MEC network. In particular, we improve the traditional fully-connected network structure to obtain both discrete and continuous action outputs, and accelerate neural network parameter updates by using prioritized experience tuples. Furthermore, we use dynamic voltage and frequency scaling (DVFS) technology to dynamically adjust the CPU frequency of local computing, and employ SWIPT technology to balance the charging and communication according to the obtained strategy. Simulation results show that the algorithm proposed in this paper can effectively reduce the energy cost of UEs, and complete more computation tasks within the delay limit.

Theory and Experiment of Pulse Wave Rectifier with High Efficiency

In this paper, the pulse wave (PW) rectifier of the Schottky diode is theoretically analyzed using the microwave equivalent circuit. It is found that the duty cycle of PW is inversely proportional to the load resistance of the rectifier when the amplitude of the input pulse is the same. Therefore, a stable high-efficiency rectifier can be designed by changing the value of the load resistance when the duty cycles are different. A grounded coplanar waveguide (GCPW) rectifier for the pulse wave is designed to verify this rule. The rectifier is simulated by ADS software and verified by the measurements. When the duty cycle of PW varies from 0.01 to 1 and the input pulse amplitude is stable at the operation frequency of 2.38 GHz, the measured rectifying efficiency can be maintained at the peak efficiency of 76.1% by adjusting the load resistance. However, when the input signal of the rectifier is the continuous wave (CW), the rectifying efficiency is only 3.9% at the same input power amplitude. The proposed rectifier has a simple structure so that it can obtain a high efficiency and has a compact size of 0.22λ0 × 0.11λ0. It can be a good candidate for simultaneous wireless information and power transmission (SWIPT) for low-power electronic devices in the Internet of Things (IoT).

Recent advances in metamaterials for simultaneous wireless information and power transmission

Abstract In the last two decades, metamaterials and metasurfaces have introduced many new electromagnetic (EM) theory concepts and inspired contemporary design methodologies for EM devices and systems. This review focuses on the recent advances in metamaterials (MMs) for simultaneous wireless information and power transmission (SWIPT) technology. In the increasingly complex EM world, digital coding and programmable metamaterials and metasurfaces have enabled commercial opportunities with a broad impact on wireless communications and wireless power transfer. In this review, we first introduce the potential technologies for SWIPT. Then, it is followed by a comprehensive survey of various research efforts on metamaterial-based wireless information transmission (WIT), wireless power transmission (WPT), wireless energy harvesting (WEH) and SWIPT technologies. Finally, it is concluded with perspectives on the rapidly growing SWIPT requirement for 6G. This review is expected to provide researchers with insights into the trend and applications of metamaterial-based SWIPT technologies to stimulate future research in this emerging domain.

Optimizing Energy Efficiency for Supporting Near-Cloud Access Region of UAV-Based NOMA Networks in IoT Systems

Nonorthogonal multiple access (NOMA) and unmanned aerial vehicle (UAV) are two promising technologies for the wireless fifth generation (5G) networks and beyond. On the one hand, UAVs can be deployed as flying base stations to build line-of-sight (LoS) communication links to two ground users (GUs) and to improve the performance of conventional terrestrial cellular networks. On the other hand, NOMA enables the share of an orthogonal resource to multiple users simultaneously, thus improving the spectral efficiency and supporting massive connectivities. This paper presents two protocols, namely, cloud-based central station- (CCS-) based power-splitting protocol (PSR) and time-switching protocol (TSR), for simultaneous wireless information and power transmission (SWIPT) at UAV employed in power domain NOMA-based multitier heterogeneous cloud radio access network (H-CRAN) of Internet of Things (IoT) system. The system model with k types of UAVs and two users in which the CCS manages the entire H-CRAN and operates as a central unit in the cloud is proposed in our work. Closed-form expressions of throughput and energy efficiency (EE) for UAVs are derived. In particular, the EE is determined for the impacts of power allocation at CCS, various UAV types, and channel environment. The simulation results show that the performance for CCS-based PSR outperforms that for CCS-based TSR for the impacts of power allocation at the CCS. On the contrary, the TSR protocol has a higher EE than the PSR in the cases of the impact of various UAV types and channel environment. The analytic results match Monte Carlo simulations.

Energy-Efficient Power Allocation in Non-Linear Energy Harvesting Multiple Relay Systems

In this paper, to maximize the energy efficiency (EE) in the two-hop multi-relay cooperative decoding and forwarding (DF) system for simultaneous wireless information and power transmission (SWIPT), an optimal power allocation algorithm is proposed, in which the relay energy harvesting (EH) adopts a nonlinear model. Under the constraints, including energy causality, the minimum transmission quality of information and the total transmission power at the relays, an optimization problem is constructed to jointly optimize the transmit power and power-splitting (PS) ratios of multiple relays. Although this problem is a nonlinear fractional programming problem, an iterative algorithm is developed to obtain the optimal power allocation. In particular, the joint power allocation at multiple relays is first decoupled into a single relay power allocation, and then single-relay power allocation is performed by the Dinkelbach iteration algorithm, which can be proven that it is a convex programming problem. Its closed form solutions for different polylines of EH models are obtained by using mathematical methods, such as monotonicity, Lagrange multipliers, the KKT condition and the Cardan formula. The simulation results show the superiority of the power allocation algorithm proposed in this paper in terms of EE.

Robust Beamforming and Power Minimization Design in MISO Health Monitoring System

In this paper, we study the power splitting (PS) scheme for each user in a multiple-input single-output (MISO) health monitoring system, while considering simultaneous wireless information and power transmission (SWIPT). We construct an optimization problem with robust power minimization constrained by the signal-to-inference-plus-noise ratio (SINR) and energy harvesting (EH). For channel uncertainty, this problem is a non-convexity and is not easy to solve and it can be translated into semidefinite program (SDP) by utilizing S-Procedure. Then the above optimization problem is combined with different channel uncertainty models, and the Bernstein-type inequality and Gaussian error function are introduced to further simplify the optimization problem. Simulation results prove the performance of the proposed robust scheme and point out its effective help for the development of modern telemedicine systems.

Dual-Frequency Programmed Harmonics Modulation-based Simultaneous Wireless Information and Power Transfer System via a Common Resonance Link

Most simultaneous wireless information and power transmission (SWIPT) systems currently operate at a single frequency, where the power and information transmission affect the resonance state of each other. This paper proposes a structure using dual-frequency programmed harmonics modulation (DFPHM). The primary-side inverter outputs a dual-frequency (DF) wave containing the power transmission and information transmission frequencies, while the DF wave is coupled to the secondary side through a common inductive link. After the power and information are transmitted to the secondary side, they are demodulated in different branches. Wave trappers are designed on each branch to reduce the interference of information transmission on power transmission. There is no tight coupling transformer in the system to inject information, so the system order is not high. Experiments verified that the proposed structure based on DFPHM is effective.

Resource allocation of simultaneous wireless information and power transmission of multi-beam solar power satellites in space–terrestrial integrated networks for 6G wireless systems

The technique of simultaneous wireless information and power transmission (SWIPT) has been applied to wireless sensor networks, which employ static or mobile base stations (BSs) such as drones and ships to charge passively powered devices. SWIPT can be strongly expanded by solar power satellites (SPSs), which collect solar energy and transmit it to the earth through microwaves to alleviate the power shortage problem. Furthermore, multi-beam SPSs can serve a broader range than terrestrial BSs for information transmission.In 6G networks, satellites are core devices in space-terrestrial integrated networks (STINs) supporting super Internet-of-Things. However, when discussing 6G wireless systems, previous works did not consider SWIPT applied in STINs through multi-beam SPSs. Therefore, this work proposes a novel resource allocation problem for SWIPT performed by multi-beam SPSs in the STIN while optimizing the following two objectives: minimizing deficit or excess of information transmission rate and maximizing power transmission based on two receiving architectures of terrestrial devices for information decoding and energy harvesting. Different from previous works, this problem considers not only assigning power to one of multiple satellite beams but also further allocating power in each beam into two parts for information and power transmission. This problem is NP-hard as it includes an NP-hard problem. Artificial intelligence (AI) algorithms can be used to optimize the network resource management. Hence, this problem with continuous decision variables is further solved by a classical and two recent AI algorithms specially designed for continuous variables, i.e., particle swarm optimization, improved harmony search algorithm, and monkey algorithm. Through simulation, the most appropriate AI algorithms to the concerned problem are analyzed, and the results show that for the two special designed receiving architectures of the terrestrial devices, the power splitting architecture generally outperforms the time switching architecture.

Weighted Sum-SINR and Fairness Optimization for SWIPT-Multigroup Multicasting Systems With Heterogeneous Users

The development of next generation wireless communication systems focuses on the expansion of existing technologies, while ensuring an accord between various devices within a system. In this article, we target the aspect of precoder design for simultaneous wireless information and power transmission (SWIPT) in a multi-group (MG) multicasting (MC) framework capable of handling heterogeneous types of users, viz., information decoding (ID) specific, energy harvesting (EH) explicit, and/or both ID and EH operations concurrently. Precoding is a technique well-known for handling the inter-user interference in multi-user systems, however, the joint design with SWIPT is not yet fully exploited. Herein, we investigate the potential benefits of having a dedicated precoder for the set of users with EH demands, in addition to the MC precoding. We study the system performance of the aforementioned system from the perspectives of weighted sum of signal-to-interference-plus-noise-ratio (SINR) and fairness. In this regard, we formulate the precoder design problems for (i) maximizing the weighted sum of SINRs at the intended users and (ii) maximizing the minimum of SINRs at the intended users; both subject to the constraints on minimum (non-linear) harvested energy, an upper limit on the total transmit power and a minimum SINR required to close the link. We solve the above-mentioned problems using distinct iterative algorithms with the help of semi-definite relaxation (SDR) and slack-variable replacement (SVR) techniques, following suitable transformations pertaining the problem convexification. The main novelty of the proposed approach lies in the ability to jointly design the MC and EH precoders for serving the heterogeneously classified ID and EH users present in distinct groups, respectively. We illustrate the comparison between the proposed weighted sum-SINR and fairness models via simulation results, carried out under various parameter values and operating conditions.

SWIPT Signaling Over Frequency-Selective Channels With a Nonlinear Energy Harvester: Non-Zero Mean and Asymmetric Inputs

Simultaneous wireless information and power transmission (SWIPT) over a point-to-point frequency-selective channel is studied. Leveraging a small-signal model for a nonlinear energy harvester, a general form of the delivered power in terms of system baseband parameters is derived, which demonstrates the dependency of the delivered power on higher moments of the baseband channel input. The optimization problem of maximizing rate-power (RP) region is studied. Assuming that the channel state information (CSI) is available at both the receiver and the transmitter, and constraining to the non-zero mean Gaussian input distributions, an optimization algorithm for power allocation among different subchannels is studied. As a special case, optimality conditions for zero mean Gaussian inputs are derived. Results obtained from the numerical optimization demonstrate the superiority of the non-zero mean Gaussian inputs (with asymmetric power allocation in each complex subchannel) in yielding a larger RP region compared to their zero mean and non-zero mean (with symmetric power allocation in each complex subchannel) counterparts. The results motivate the design of new modulation for SWIPT and contrast with the SWIPT design under linear energy harvesting, for which the circularly symmetric Gaussian inputs with water-filling power allocation are optimal.

Fundamentals of Simultaneous Wireless Information and Power Transmission in Heterogeneous Networks: A Cell-Load Perspective

In a heterogeneous cellular network (HetNet) consisting of multiple different types (tiers) of base stations (BSs), the void cell event in which a BS does not have any users has been shown to exist due to user-centric BS association and its probability is dominated by the cell load of each tier. Such a void cell phenomenon has not been well characterized in the modeling and analytical framework of simultaneous wireless information and power transmission (SWIPT) in a HetNet. This paper aims to accurately exploit the fundamental performance limits of the SWIPT between a BS and its user by modeling the cell-load impact on the downlink and uplink transmissions of each BS. We first characterize the power-splitting receiver architecture at a user and analyze the statistical properties and limits of its harvested power and energy, which reveals how much of the average energy can be harvested by users and how likely the self-powered sustainability of users can be achieved. We then derive the downlink and uplink rates that characterize the cell-load and user association effects and use them to define the energy efficiency of a user. The optimality of the energy efficiency is investigated, which maximizes the SWIPT performance of the receiver architecture for different user association and network deployment scenarios.

Receiver Design to Employ Simultaneous Wireless Information and Power Transmission with Joint CFO and Channel Estimation

Radio-frequency energy harvesting (EH) is one of the enabling technologies for the next-generation wireless communication systems. EH techniques are specifically used to improve the energy efficiency of the system. Recently, the simultaneous wireless information and power transmission (SWIPT) protocol is adapted for EH. In this paper, we design a new receiver for joint carrier frequency offset (CFO) and channel estimation on single-carrier modulations with frequency-domain equalization along with SWIPT implementation for EH by using the pilot signal. The pilot signal is a highly energized signal, which is superimposed with the information signal. The superimposed signal is used not only to transmit power for EH purposes but also to estimate the CFO and channel conditions. The receiver is designed to accommodate the strong interference levels in the channel estimation and data detection. The proposed scheme offers a flexible design method and efficient resource utilization. We validate our analytical results using simulations.

Dual-Polarized Communication Rectenna Array for Simultaneous Wireless Information and Power Transmission

A dual-polarized communication rectenna array with high isolation and low cross polarization for simultaneous wireless information and power transmission (SWIPT) is presented. It consists of a 2 × 2 element receiving antenna array and a high efficiency rectifier based on voltage doubler topology. The receiving element is corner-fed to achieve high isolation of more than 20 dB between the dual-polarized ports, which guarantees low mutual interference between the communication and the rectifying ports. To receive enough electromagnetic (EM) wave for rectifying and meanwhile meet the communication sensitivity, this 2 × 2 array uses its 2 × 2 vertical polarization ports and 1 × 2 horizontal polarization ports for power rectifying, and the rest 1 × 2 horizontal polarization ports for communication. For the communication port, the measured gain is 10.9 dBi and the cross polarization is less than -20 dB. The performance of the whole communication rectenna array has been measured, where a 2 × 4 circularly-polarized array with a gain of 17.5 dBi, settled 1 meter away is used as the transmitter. Measured results show that the system achieves a peak microwave - direct circuit (mw-dc) conversion efficiency of 74.9 % for the CW signal, and 67 % for the QPSK signal with 10 MHz channel bandwidth on the load of 345 Ω at 2.58 GHz operating frequency.

Fundamentals of Wireless Information and Power Transfer: From RF Energy Harvester Models to Signal and System Designs

Radio waves carry both energy and information simultaneously. Nevertheless, radio-frequency (RF) transmissions of these quantities have traditionally been treated separately. Currently, the community is experiencing a paradigm shift in wireless network design, namely, unifying wireless transmission of information and power so as to make the best use of the RF spectrum and radiation as well as the network infrastructure for the dual purpose of communicating and energizing. In this paper, we review and discuss recent progress in laying the foundations of the envisioned dual purpose networks by establishing a signal theory and design for wireless information and power transmission (WIPT) and identifying the fundamental tradeoff between conveying information and power wirelessly. We start with an overview of WIPT challenges and technologies, namely, simultaneous WIPT (SWIPT), wirelessly powered communication networks (WPCNs), and wirelessly powered backscatter communication (WPBC). We then characterize energy harvesters and show how WIPT signal and system designs crucially revolve around the underlying energy harvester model. To that end, we highlight three different energy harvester models, namely, one linear model and two nonlinear models, and show how WIPT designs differ for each of them in single-user and multi-user deployments. Topics discussed include rate-energy region characterization, transmitter and receiver architectures, waveform design, modulation, beamforming and input distribution optimizations, resource allocation, and RF spectrum use. We discuss and check the validity of the different energy harvester models and the resulting signal theory and design based on circuit simulations, prototyping, and experimentation. We also point out numerous directions that are promising for future research.