Energy level-based efficient wireless power and information transfer in sensor networks

In cognitive Wireless Radio networks, information transfer and power transfer are given special consideration in next-generation wireless networking devices like Simultaneous Wireless Information and Power Transfer. The benefit of integrating cognitive network concepts is that it provides greater efficiency on energy and spectrum to address interference, fading, and path loss, among many other issues, in certain critical applications. Energy harvesting (EH) is a secure and cost-effective method of powering up cluster heads when needed. The proposed method considers two phases. The first phase is energy harvesting of SUs transferred in power signals send by the hybrid access point during wireless power transfer (WPT). While in the second phrase, Wireless Information Transfer (WIT) phase, the captured energy is used while simultaneously acquiring transmission possibilities. In addition, a fuzzy-based cluster using a greedy algorithm is used to reduce PU secrecy outages and to provide the best ideal result. These may be identified using a convolutional neural network (CNN) to detect and classify distinct attack types. This paper presents an efficient resource allocation using fuzzy logic-based clustering and greedy algorithms, which can provide better performance than other technologies. The subsystem for cognitive radio networks is configured, and the primary nodes’ secrecy is maintained and free of three attacks, and the results are simulated using MATLAB tools.

5G-based green broadband communication system design with simultaneous wireless information and power transfer

Radio frequency (RF) signals have been relied upon for both wireless information delivery and wireless charging to the massively deployed low-power Internet of Things (IoT) devices. Extensive efforts have been invested in physical layer and medium-access-control layer design for coordinating simultaneous wireless information and power transfer (SWIPT) in RF bands. Different from the existing works, we study the coding controlled SWIPT from the information theoretical perspective with practical transceiver. Due to its practical decoding implementation and its flexibility on the codeword structure, unary code is chosen for joint information and energy encoding. Wireless power transfer (WPT) performance in terms of energy harvested per binary sign and of battery overflow/underflow probability is maximised by optimising the codeword distribution of coded information source, while satisfying required wireless information transfer (WIT) performance in terms of mutual information. Furthermore, a Genetic Algorithm (GA) aided coding design is proposed to reduce the computational complexity. Numerical results characterise the SWIPT performance and validate the optimality of our proposed GA aided unary coding design.

Chapter 10 - Transmit beamforming for simultaneous wireless information and power transfer

Realising both wireless information transfer (WIT) and wireless power transfer (WPT) in the same RF spectral band has imposed great challenges on the system design but the spectral efficiency can be substantially improved, which triggers the significant research interest in the simultaneous wireless information and power transfer (SWIPT). In order to fully exploit the limited spectral resources, a non-orthogonal-multiple-access (NOMA) technique aided SWIPT system is considered for simultaneously realising both of WIT and WPT, which consists of a single access point (AP), a single WPT user and a pair of WIT users. The AP delivers the requested information to the pair of WIT users by adopting the NOMA technique. In order to maximise the amount of energy received by the WPT user, a novel constellation rotation based modulation scheme is proposed for constructively combining the symbols requested by the pair of the WIT users by optimising the constellation rotation angle. By considering the sensitivity of the energy harvester, the simulation results demonstrate that our modulation scheme is capable of efficiently increasing the energy harvested by the WPT user without incurring additional symbol detection errors.

This paper presents the design of a bidirectional wireless power and information transfer system. The wireless information transfer is based on near-field technology, utilizing communication coils integrated into power transfer coils. Compared with conventional far-field-based communication methods (e.g., Bluetooth and WLAN), the proposed near-field-based communication method provides a peer-to-peer feature, as well as lower latency, which enables the simple paring of a transmitter and a receiver for power transfer and the real-time updating of control parameters. Using the established communication, control parameters are transmitted from one side of the system to another side, and the co-control of the inverter and the active rectifier is realized. In addition, this work innovatively presents the communication-signal-based synchronization of an inverter and a rectifier, which requires no AC current sensing in the power path and no complex algorithm for stabilization, unlike conventional current-based synchronization methods. The proposed information and power transfer system was measured under different operating conditions, including aligned and misaligned positions, operating points with different charging powers, and forward and reverse power transfer. The results show that the presented prototype allows a bidirectional power transfer of up to 1.2 kW, and efficiency above 90% for the power ranges from 0.6 kW to 1.2 kW was obtained. Furthermore, the integrated communication is robust to the crosstalk from the power transfer and misalignment, and a zero BER (bit error rate) and ultra-low latency of 15.36 µs are achieved. The presented work thus provides a novel solution to the synchronization and real-time co-control of an active rectifier and an inverter in a wireless power transfer system, utilizing integrated near-field-based communication.

Far-field wireless power transfer (WPT) and simultaneous wireless information and power transfer (SWIPT) have become increasingly important in radio frequency (RF) and communication communities recently. The problem of modulation design for SWIPT has however been scarcely addressed. In this paper, a modulation scheme based on asymmetric phase-shift keying (PSK) is considered, which improves the SWIPT rate-energy tradeoff region significantly. The nonlinear rectifier model, which accurately models the energy harvester, is adopted for evaluating the output direct current (DC) power at the receiver. The harvested DC power is maximized under an average power constraint at the transmitter and a constraint on the rate of information transmitted via a multi-carrier signal over a flat fading channel. As a consequence of the rectifier nonlinearity, this work highlights that asymmetric PSK modulation provides benefits over conventional symmetric PSK modulation in SWIPT and opens the door to systematic modulation design tailored for SWIPT.

Considering the problems of network lifetime and energy replenishment in wireless sensor network (WSN), a Power Beacon (PB) assisted energy harvesting Simultaneous wireless information and power transfer (SWIPT) multi-relay system model is proposed. Under the condition that the relay node has the characteristics of capturing the energy of the source node and PB signal, the system throughput of the target node using the maximum ratio combining technology is derived. Then, the problem model is established under multiple constraints to ensure the communication quality of service, and a relay selection strategy based on the adaptive chaotic particle swarm optimization (ACPSO) algorithm is proposed to optimize the system throughput. Simulation and numerical results show that PB transmission power, time switching (TS) factor, power splitting (PS) factor, and other parameters have a significant impact on throughput performance. Compared with the random relay selection (RS) strategy, the proposed strategy can achieve greater throughput gain, and it is proved that the ACPSO algorithm can quickly and effectively optimize network throughput.

In this paper, we consider a wireless powered multi-relay network in which a multi-antenna hybrid access point underlaying a cellular system transmits information to distant receivers. Multiple relays capable of energy harvesting are deployed in the network to assist the information transmission. The hybrid access point can wirelessly supply energy to the relays, achieving multi-user gains from signal and energy cooperation. We propose a joint optimization for signal beamforming of the hybrid access point as well as wireless energy harvesting and collaborative beamforming strategies of the relays. The objective is to maximize network throughput subject to probabilistic interference constraints at the cellular user equipment. We formulate the throughput maximization with both the time-switching and power-splitting schemes, which impose very different couplings between the operating parameters for wireless power and information transfer. Although the optimization problems are inherently non-convex, they share similar structural properties that can be leveraged for efficient algorithm design. In particular, by exploiting monotonicity in the throughput, we maximize it iteratively via customized polyblock approximation with reduced complexity. The numerical results show that the proposed algorithms can achieve close to optimal performance in terms of the energy efficiency and throughput.

Antenna design and angle-of-arrival (AoA) estimation are critical to the efficiency of wireless information and power transfer. The AoA estimation is challenging for energy-efficient lens antenna arrays (LAAs), due to discrete sets of fixed discrete Fourier transform (DFT) beams. This paper presents a novel fast and accurate approach for the AoA estimation of LAAs. The key idea is that we prove the two differential outputs of three adjacent lens beams, referred to as “DFT beam differences (DBDs),” that are the strongest at the two sides of an AoA. They are easy to identify and robust to noises, and their powers are proved to provide an accurate estimate of the AoA. Another important aspect is a new beam synthesis technique which produces different beam widths based on DFT beams and practical 1-bit phase shifts in real time. As a result, the angular region containing the AoA can exponentially narrow down, and the two strongest DBDs can be quickly identified. The proposed approach can operate in coupling with successive interference cancellation to estimate the AoAs of multiple paths. Simulations show that the proposed approach is able to outperform the state of the art by orders of magnitude in terms of accuracy. The power transfer efficiency can be dramatically improved.

Here, the authors investigate robust secure transmission for wireless information and power transfer in heterogeneous networks (HeNets) under the deterministic and stochastic CSI errors, respectively, where one macrocell base station (MBS) and one femtocell base station (FBS) respectively serve to macrocell users (MUs) and femtocell users (FUs). Meanwhile, FUs acquire energy from the FBS and multiple eavesdroppers attempt to wiretap its downlink information. To secure the wireless information and power transfer, the authors propose an artificial noise (AN)‐aided transmission design. Under the deterministic CSI error, the authors jointly design the beamforming and AN vectors of the MBS and FBS to minimise the total transmit power, while satisfying the constraints on the signal‐to‐interference plus noise (SINR) requirement at each MU, energy harvesting (EH) and secrecy outage probability requirement at each FU. This formulated problem is non‐convex. Utilising S‐procedure and successive convex approximation technique, the authors successfully transfer it into a series of convex problems. Under the stochastic CSI error, the joint design problem is formulated with a range of outage probabilistic constraints. Further, the authors, respectively, resort to large deviation and Bernstein‐type inequalities, S‐procedure to convert it into solvable forms. Simulation results demonstrate the effectiveness of the authors’ proposed design.

This book is the first systematic exposition on the emerging domain of wireless power transfer in ad hoc communication networks. It selectively spans a coherent, large spectrum of fundamental aspects of wireless power transfer, such as mobility management in the network, combined wireless power and information transfer, energy flow among network devices, joint activities with wireless power transfer (routing, data gathering and solar energy harvesting), and safety provisioning through electromagnetic radiation control, as well as fundamental and novel circuits and technologies enabling the wide application of wireless powering. Comprising a total of 27 chapters, contributed by leading experts, the content is organized into six thematic sections: technologies, communication, mobility, energy flow, joint operations, and electromagnetic radiation awareness. It will be valuable for researchers, engineers, educators, and students, and it may also be used as a supplement to academic courses on algorithmic applications, wireless protocols, distributed computing, and networking.

Antenna beamforming for Simultaneous Wireless Information and Power Transfer (SWIPT) and Wireless Power Transfer (WPT) in an indoor 6G communication system is presented in this paper. The objective function is to maximize the total harvesting power for the SWIPT and WPT nodes with the constraints of the bit error rate and minimum harvesting power. In the study, the power-splitting ratio between harvesting power and decoding information can be adjusted for the SWIPT node. Due to the non-convex problem, we use Self-Adaptive Dynamic Differential Evolution (SADDE) to optimize the designed multi-objective function. We use a symmetric antenna array to study three situations of distance—closer, farther, and similar—between the transmitting antenna and the individual SWIPT and WPT nodes in this paper. Experimental results show that the overall harvesting efficiency is improved, especially in the case of SWIPT nodes closer to the transmitter. The total harvesting power can be improved by 86.7% in the total short-distance case, and by 7.87% in the total long-distance case.

This paper investigates the optimal power minimization design of simultaneous wireless information and power transfer systems under non-linear energy harvesting (EH) model, where a multi-antenna hybrid access point (H-AP) simultaneously transmits information and power to multiple heterogeneous users, such as information-energy receivers (IERs), information receivers (IRs), and ERs. Power splitting (PS) receiver architecture is adopted at all IERs. In order to achieve green system design, an optimization problem is formulated to minimize the transmit power of H-AP subject to the required signal-to-interference-plus-noise ratios (SINRs) constraints at IERs and IRs, and the harvested energy constrains at IERs and ERs, by jointly optimizing the beamforming vector at H-AP and the PS ratios at IERs. Since the problem is nonconvex and the employ of the non-linear EH model makes it more difficult to solve, the semidefinite relaxation and variable substitutions are used to handle it. For some cases, we theoretically prove that the globe optimal solution can be guaranteed by using our method, and for rest cases, we discuss its optimality via simulations. Numerical results show that although the traditional linear EH model is feasible for the practical EH circuits in some cases, the corresponding system consumes more transmit power than that under the non-linear model EH. Moreover, the effects of the numbers of users, the required SINRs, and the harvested energy on the system transmit power are also discussed.

This paper investigates the problem of power allocation for distributed estimation via diffusion in wireless sensor networks (WSNs) with simultaneous wireless information and power transfer (SWIPT). We consider a WSN consisting of smart sensor nodes (SNs) and common sensor nodes (CNs), and each SN is capable of performing SWIPT via multi-antenna beamforming to its neighboring (i.e., near-tier) CNs. In each diffusion iteration, all nodes collect measurements and exchange intermediate estimates with their neighbors. We first analyze the effect of each SN's beamforming design and each near-tier CN's harvested power allocation on the steady-state network-wide mean square deviation (MSD) of the diffusion least-mean-squares (LMSs) strategy. Then, we formulate a problem to minimize an upper bound MSD by jointly optimizing the global power allocation weights for each SN to perform beamforming, and the local power allocation proportion for each CN to perform measurement collection. We further show that the formulated non-convex problem is decomposable and propose a gradient-based iterative algorithm to find the optimal solution. In addition, for practical implementation, we propose adaptive online approaches to estimate some parameters required for system optimization. Finally, extensive simulation results demonstrate that with optimal power allocation, our proposed scheme improves the MSD performance significantly, compared to the conventional diffusion LMS strategy without wireless power transfer (WPT).