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In this paper, we present a physical-layer security scheme that exploits artificial noise (AN) to secure the downlink legitimate communications and transfer energy to nodes operating under non-cooperative non-orthogonal multiple-access (NOMA) scenario. The nodes employ a joint time-switching and power-switching scheme to maximize the harvested energy. We provide necessary analysis and derivations for the optimization parameters and find the optimized transmission parameters that maximize the minimum secrecy rate among users while meeting constraints on minimum transferred energy and outage probabilities at the nodes through an exhaustive grid-based search. Our analysis and simulations prove the feasibility of securing the communication among NOMA nodes, while transferring energy and meeting outage probability constraints. [ABSTRACT FROM AUTHOR]

Adaptive link selection for buffer-aided relaying can achieve significant performance gain compared with the conventional relaying with fixed transmission criterion. However, most of the existing link-selection strategies are designed based on perfect channel state information (CSI), which are very complex by requiring channel estimator. To solve this issue, in this paper, we investigate a buffer-aided differential chaos-shift-keying based simultaneous wireless information and power transfer (DCSK-SWIPT) relay system, where a decode-and-forward protocol is considered and the relay is equipped with a data buffer and an energy buffer. In particular, we propose two link-selection protocols for the proposed system based on harvested energy, data-buffer status and energy-shortage status, where the CSI is replaced by the harvested energy to avoid the channel estimation and the practical problem of the decoding cost at the relay is considered. Furthermore, the bit-error-rate (BER) and average-delay closed-form expressions of the proposed protocols are derived over multipath Rayleigh fading channels, which are validated via simulations. Finally, results demonstrate that both the proposed protocols not only provide better BER performance than the conventional DCSK system and DCSK-SWIPT relay system but also achieve better BER performance and lower average delay in comparison to the conventional signal-to-noise-ratio-based buffer-aided DCSK-SWIPT relay systems. [ABSTRACT FROM AUTHOR]

Abstract In multi-antenna simultaneous wireless information and power transfer (SWIPT) system, beamforming strategy has been widely analyzed due to the increasing signal strength. It can not only increase the signal strength in the direction of the antenna array but also reduce the interference strength, which is a good option for SWIPT system to achieve directional transmission of information and energy. However, the traditional beamforming strategy only uses single beamforming vector, and it does not consider the differences between information and energy in SWIPT system. Actually, interference can also be collected as energy. Based on the traditional beamforming strategy, the resources in SWIPT system are not properly utilized. Therefore, this paper proposes a joint beamforming strategy in multi-input and single-output (MISO) SWIPT system. We extend the traditional single beamforming vector into two beamforming vectors to realize independent control of information and energy based on time switching (TS) receiving mode. In information receiving phase, information beamforming vector is used to carry specific user’s information for information alignment. Since there is an orthogonal relationship between information beamforming vector and channel gain vector, we can achieve to eliminate interference and realize error-free information transmission. In energy receiving phase, energy beamforming vector is used to carry user’s energy. Energy beamforming vector and channel gain vector do not require the orthogonality so that the interference can also be collected as energy. In this paper, we model it as a transmission power optimization (TPO) problem, which is a complex non-convex problem. We firstly transform it into a convex problem, and then, it can be solved using CVX toolbox. Simulation results show that the proposed strategy could increase the energy collection at the same transmission power and also decrease the transmission power at the same energy collection.

Abstract This paper investigates the multi-cell coordinated beamforming (MCBF) design for secure simultaneous wireless information and power transfer (SWIPT) in both centralized and distributed manners. In each cell, one transmitter serves multiple information receivers (IRs) and energy receivers (ERs) with the non-linear energy harvesting (EH) model. Meanwhile, several eavesdroppers (Eves) intend to intercept the confidential information transmitted for IRs. To achieve a secure transmission, the artificial noise (AN) is embedded in the transmit signals of each transmitter. The proposed design is formulated into a power-minimization problem to guarantee the IRs’ information and ERs’ energy requirements while avoiding the information being intercepted by Eves. Since the problem is non-convex and not easy to solve, a solution method based on semi-definition relaxation (SDR) is proposed and the global optimum is proved to be guaranteed with full channel state information (CSI). We further present a distributed AN-aided MCBF for the system by using alternating direction method of multipliers (ADMM), with which each transmitter is able to calculate its own beamforming vectors and AN covariance matrix based on its local CSI. Simulation results show that our proposed distributed design converges to the global optimum obtained by the centralized one. It is also shown that by employing AN, the total required power of the system is reduced and the effect of AN on the system performance decreases with increment of transmit antennas. Compared with traditional linear EH model, optimizing the system under the non-linear EH one avoids false output power at the ERs and saves power at the transmitter.

The simultaneous wireless information and power transfer (SWIPT) technology is recently used to sustain the lifetime of energy-constrained relay nodes in wireless cooperative networks. An example to achieve this technology is the hybridized power-time splitting-based relaying (HPTSR) protocol. However, the information security aspect of wireless cooperative networks is important and needs adequate attention. In this paper, we perform the secrecy analysis of a SWIPT-enabled cooperative network with source–relay link-based decode-and-forward HPTSR protocol, which can enhance the operational lifetime of the relay nodes and the secrecy performance of the entire cooperative network. Specifically, we examine the secrecy performance of the considered network by deriving the analytical expressions for the near-optimal power splitting factor, secrecy outage probability, and secure energy efficiency of the system. All analytical results are confirmed by numerical simulations. Our results show that the SWIPT-enabled cooperative network outperforms the conventional relaying scheme-based network presented in literature at relatively high signal-to-noise ratios.

Device-to-device (D2D) communications as an underlay to cellular networks can not only increase the system capacity and energy efficiency but also enable national security and public safety services. A key requirement for these services is to provide alternative access to cellular networks when they are partially or fully damaged due to a natural disaster event. In this paper, we employ energy harvesting (EH) at the relay with simultaneous wireless information and power transfer to prolong the lifetime of energy constrained network. In particular, we consider a user equipment relay that harvests energy from radio frequency signal via base station and use harvested energy for D2D communications. We integrate clustering technique with D2D communications into cellular networks such that communication services can be maintained when the cellular infrastructure becomes partially dysfunctional. Simulation results show that our proposed EH-based D2D clustering model performs efficiently in terms of coverage, energy efficiency, and cluster formation to extend the communication area. Moreover, a novel concept of power transfer in D2D clustering with user equipment relay and cluster head is proposed to provide a new framework to handle critical and emergency situations. The proposed approach is shown to provide significant energy saving for both mobile users and clustering heads to survive in emergency and disaster situations.

In this paper, we investigate the secure transmission in two-way untrusted amplify-and-forward relay networks with simultaneous wireless information and power transfer (SWIPT). Two secure SWIPT relaying strategies, namely, secure power splitting (SPS) and secure time switching (STS), are studied with the objective of secrecy rate (SR) and secure energy efficiency (SEE) maximization. First, the high signal-to-noise ratio approximations of SR and SEE are established, based on which non-convex SPS-based and convex STS-based SR maximization problems are formulated to jointly optimize the source transmit power and resource division ratio. Suboptimal solutions are obtained by employing Dinkelbach's method and Newton's method, respectively. Furthermore, to guarantee both the energy efficiency and secure quality of service (QoS) performance, SEE maximization problems are formulated with the consideration of the energy harvesting activation constraint and the target SR requirement. The intractable non-convex SEE maximization problems are reformulated as parameter programming, transformed to Lagrange dual problems, and finally solved by two SEE resource allocation algorithms with low complexity. Numerical results verify the convergence and effectiveness of the proposed algorithms and provide new insights into relaying strategy design and secure relay placement.

This paper investigates the downlink transmission of massive multiple-input multiple-output-enabled simultaneous wireless information and power transfer systems in Rician fading channels. In the system, the base station is equipped with massive antennas to concurrently deliver information and energy to the users. While a portion of the harvested energy is utilized by the users to support the channel estimation, and the remaining is reserved as the supplement to the user battery for signal processing. The asymptotic expressions of the harvested energy and achievable rate are, respectively, derived, in the context of downlink scenario and line-of-sight propagation. With respect to the proposed system, two optimization problems are formulated, with the purposes of maximizing the system sum rate and the minimum rate among individual users, respectively. As both original problems are nonconvex and hard to solve, we propose a general iterative optimization framework to first decompose each of them into three subproblems, where the power allocation profiles, the channel estimation duration, and the power split ratios are optimized independently. The iteration is then carried out to update the solutions to each subproblem and finally approach the optimum of the original ones. The convergence and the effectiveness of the proposed algorithms are proved and evaluated through both theoretical analysis and simulations. Results demonstrate that the proposed algorithms can achieve the optimal transmission performance of the system with moderate complexity. Moreover, it can be further concluded that the maximum rate can be achieved if the harvested energy is fully devoted to pilot transmission.

We consider a three-node two-way relaying network, where an amplify-and-forward (AF) relay helps to forward the information of source nodes by using the energy harvested from the radio frequency signals transmitted from the two source nodes. The source and relay nodes work on half-duplex, which completes the transmission in two phases. Specifically, in the first transmission phase, two source nodes transmit their signals to relay. The received signals at relay will be divided into two subcarrier groups, to perform information decoding and energy harvesting separately. In the second transmission phase, after subcarrier pairing, relay amplifies the received signals then forwards them to the two source nodes with the harvested energy. An joint resource optimization problem, including subcarrier grouping, paring and power allocation, is formulated to maximize the sum transmission rate of source nodes with power constraints. Simulation analyses show that our proposed algorithm outperforms the other two benchmark algorithms and reveal the system performance influence of relay location and total transmission power.

In the present paper, we investigate the performance of the simultaneous wireless information and power transfer (SWIPT) based cooperative cognitive radio networks (CCRNs). In particular, the outage probability is derived in the closed-form expressions under the opportunistic partial relay selection. Different from the conventional CRNs in which the transmit power of the secondary transmitters count merely on the aggregate interference measured on the primary networks, the transmit power of the SWIPT-enabled transmitters is also constrained by the harvested energy. As a result, the mathematical framework involves more correlated random variables and, thus, is of higher complexity. Monte Carlo simulations are given to corroborate the accuracy of the mathematical analysis and to shed light on the behavior of the OP with respect to several important parameters, e.g., the transmit power and the number of relays. Our findings illustrate that increasing the transmit power and/or the number of relays is beneficial for the outage probability.

This paper studies a wireless sensor relay network consist of a source, a jammer, some distribution helping relays, a information decoding (ID) receiver and a Energy harvesting (EH) receiver. In the first time-slot, the source transmits the legitimate signal to the helping relays equipped a single antenna. Meanwhile, the jammer transmits the jamming signal to the relays in order to disturb the communication between the source and the ID receiver. In the second time-slot, the relays forward the sum signal from the source and jammer to the ID receiver employing beamforming. Meanwhile, the EH receiver need to receive the sufficient energy radiated from the relays satisfying the EH constraint to prolong the service life. With the linear beamforming scheme at the relays, this network can be modeled as an equivalent Gaussian arbitrarily varying channel (GAVC). The purpose is to seek the maximal transmission rate under the EH constraint. Since this problem is nonconvex and hard to tackle, we present a second order cone programming (SOCP)-based algorithm to obtain the optimal beamforming vector so as to maximize the transmission rate between the source and ID receiver when perfect channel state information (CSI) is available. In addition, the two important points of the Rate-Energy Region is identified by (SOCP)-based algorithm. Finally, simulations are used to validate the proposed scheme. [ABSTRACT FROM AUTHOR]

This paper presents a patch antenna array topology for Simultaneous Wireless Information and Power Transfer (SWIPT) applications. The resulting Double Patch Antenna Array (DPA) is composed of two patch antennas operating at different frequencies and fabricated on a unique substrate. One of the patches operates at the 1.8 GHz mobile communication band and is used for wireless communication, while the other one operates at the 2.4 GHz Industrial, Scientific, and Medical (ISM) band, and is used for Radio Frequency Energy Harvesting (RFEH). The analyzes and measurements carried out have shown that the adopted topology has satisfactory performance for communication, with a gain of 1.5 dBi, and for out-of-band energy harvesting, with a Vout of 160 mV at 2.45 GHz. These results indicate this approach as a promising strategy for low-power wireless applications. [ABSTRACT FROM AUTHOR]

It is expected that many small battery-operated devices will connect to next generation of cellular networks. In this work, a two-way wireless link is considered, where due to slow variations of the channel, forward link (FL) and reverse link channels are reciprocal, and the remote device's battery is charged via wireless energy harvesting. We analyze the performance of a two-way link setup, with very low complexity signal processing at the node that relies on battery, and consists of antenna selection and maximum ratio combining-based multiple-input single-output (MISO) and multiple-input multiple-output (MIMO) techniques, wherein FL simultaneous wireless information and power transmission is assumed to be utilized. By mathematical tractability, a closed-form analytical expression for probability of outage, ergodic capacity and bit error rate are derived and compared with simulation results. It is shown that the assumed low complexity setup achieves full diversity in both cases of MISO and MIMO. [ABSTRACT FROM AUTHOR]

In this paper, we consider an unmanned aerial vehicle (UAV) assisted communications system, including two cooperative UAVs, a wireless-powered ground destination node leveraging simultaneous wireless information and power transfer (SWIPT) technique, and a terrestrial passive eavesdropper. One UAV delivers confidential information to destination and the other sends jamming signals to against eavesdropping and assist destination with energy harvesting. Assuming UAVs have partial information about eavesdropper's location, we propose two transmission schemes: friendly UAV jamming (FUJ) and Gaussian jamming transmission (GJT) for the cases when jamming signals are known and unknown a priori at destination, respectively. Then, we formulate an average secrecy rate maximization problem to jointly optimize the transmission power and trajectory of UAVs, and the power splitting ratio of destination. Being non-convex and hence difficult to solve the formulated problem, we propose a computationally efficient iterative algorithm based on block coordinate descent and successive convex approximation to obtain a suboptimal solution. Finally, numerical results are provided to substantiate the effectiveness of our proposed multiple-UAV schemes, compared to other existing benchmarks. Specifically, we find that the FUJ demonstrates significant secrecy performance improvement in terms of the optimal instantaneous and average secrecy rate compared to the GJT and the conventional single-UAV counterpart. [ABSTRACT FROM AUTHOR]

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Intelligent reflecting surface (IRS) is a new and revolutionizing technology for achieving spectrum and energy efficient wireless networks. By leveraging massive low-cost passive elements that are able to reflect radio-frequency (RF) signals with adjustable phase shifts, IRS can achieve high passive beamforming gains, which are particularly appealing for improving the efficiency of RF-based wireless power transfer. Motivated by the above, we study in this paper an IRS-assisted simultaneous wireless information and power transfer (SWIPT) system. Specifically, a set of IRSs are 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), respectively. We aim to minimize the transmit power at the AP via jointly optimizing its transmit precoders and the reflect phase shifts at all IRSs, subject to the quality-of-service (QoS) constraints at all users, namely, the individual signal-to-interference-plus-noise ratio (SINR) constraints at IUs and the energy harvesting constraints at EUs. However, this optimization problem is non-convex with intricately coupled variables, for which the existing alternating optimization approach is shown to be inefficient as the number of QoS constraints increases. To tackle this challenge, we first apply proper transformations on the QoS constraints and then propose an efficient iterative algorithm by applying the penalty-based optimization method. Moreover, by exploiting the short-range coverage of IRS, we further propose a more computationally efficient algorithm by optimizing the phase shifts at all IRSs in parallel. Simulation results demonstrate the effectiveness of employing multiple IRSs for enhancing the performance of SWIPT systems as well as the significant performance gains achieved by our proposed algorithms over benchmark schemes. The impact of IRS on the transmitter/receiver design for SWIPT is also unveiled. [ABSTRACT FROM AUTHOR]

An intelligent reflecting surface (IRS) is invoked for enhancing the energy harvesting performance of a simultaneous wireless information and power transfer (SWIPT) aided system. Specifically, an IRS-assisted SWIPT system is considered, where a multi-antenna aided base station (BS) communicates with several multi-antenna assisted information receivers (IRs), while guaranteeing the energy harvesting requirement of the energy receivers (ERs). To maximize the weighted sum rate (WSR) of IRs, the transmit precoding (TPC) matrices of the BS and passive phase shift matrix of the IRS should be jointly optimized. To tackle this challenging optimization problem, we first adopt the classic block coordinate descent (BCD) algorithm for decoupling the original optimization problem into several subproblems and alternately optimize the TPC matrices and the phase shift matrix. For each subproblem, we provide a low-complexity iterative algorithm, which is guaranteed to converge to the Karush-Kuhn-Tucker (KKT) point of each subproblem. The BCD algorithm is rigorously proved to converge to the KKT point of the original problem. We also conceive a feasibility checking method to study its feasibility. Our extensive simulation results confirm that employing IRSs in SWIPT beneficially enhances the system performance and the proposed BCD algorithm converges rapidly, which is appealing for practical applications. [ABSTRACT FROM AUTHOR]

Device to device (D2D) communication that provides high data rate proximity based direct communication between users, along with simultaneous wireless information and power transfer (SWIPT) that extracts energy from the received RF power, can achieve high energy and spectral efficiencies together with low latency communication. Heterogeneous networks, that employ efficient frequency reuse, provide high gains in the coverage and capacity of the cellular networks. SWIPT helps in converting the harmful interference, incurred by the frequency reuse of D2D tier underlaying the Hetnet, into energy that can be stored for the future. This work presents a resource allocation and power control scheme for SWIPT enabled underlay D2D networks, designed to improve the energy efficiency and the amount of energy harvested while ensuring the minimum required data rates for the users. Resource allocation is performed using a stable many-to-one matching game model inspired from Gale-Shapley algorithm. Two techniques of SWIPT, namely power splitting SWIPT and time splitting SWIPT, are considered and the resource allocation schemes are designed for both. Simulation results demonstrate the superior performance of the proposed algorithm compared to an existing work in single tier network with power splitting SWIPT. The work is extended to a typical 5G HetNet scenario, and extensive simulations are done to compare the performance of the two SWIPT architectures in the HetNet scenario. [ABSTRACT FROM AUTHOR]

This paper studies the information-energy ($\mathrm{I}$ - $\mathrm{E}$) region for simultaneous wireless information and power transfer (SWIPT) networks in mobility scenarios, where a moving transmitter simultaneously transmits information and power to a fixed receiver, and the receiver adopts power splitting (PS) receiving architecture. In order to characterize the tradeoff between the received information and harvested energy, the $\mathrm{I}$ - $\mathrm{E}$ region is defined, and corresponding optimization problems are formulated to explore the system $\mathrm{I}$ - $\mathrm{E}$ regions by jointly optimizing the transmit power at the transmitter and the PS ratio at the receiver with three popular energy harvesting (EH) models, i.e., traditional linear EH model, the logistic nonlinear EH model and the piecewise nonlinear EH model. Particularly, to efficiently solve the nonconvex optimization problem with the logistic nonlinear EH model, a successive convex approximate (SCA)-based algorithm is proposed, which is able to characterize the lower bound of the $\mathrm{I}$ - $\mathrm{E}$ with low complexity. To solve the optimization problems with the linear and piecewise EH models, as they are convex, some closed and semi-closed solutions are derived by using Lagrange dual method and KKT conditions. Numerical results show that compared with the $\mathrm{I}$ - $\mathrm{E}$ regions under the linear and piecewise EH models, that under the logistic nonlinear EH model is smaller due to the limitations of practical EH circuit features. Moreover, with a fixed moving speed, when the transmit power is relatively large, the logistic nonlinear EH model can be replaced with the piecewise one due to the relatively small gap between their achieved $\mathrm{I}$ - $\mathrm{E}$ regions. Additionally, for a fixed moving track length, the higher moving speed yields the smaller $\mathrm{I}$ - $\mathrm{E}$ region with all three EH models. [ABSTRACT FROM AUTHOR]

In this paper, resource allocation is studied for a fully sustainable cooperative IoT network, in which a relay powered by renewable energy forwards data to a destination while charging multiple IoT nodes by radio-frequency (RF) signals. An optimal joint time and power allocation problem is formulated to maximize the long-term sum-throughput of IoT nodes, taking into consideration the bounded transmit power of IoT nodes, the stochastic characteristic of energy harvesting (EH) process, and dynamic wireless channel conditions. To solve the formulated problem, we analyze the time allocation for cooperative communications with EH, considering both data and energy dependency of the two hop transmissions in three cases with different network settings. Based on the analysis, we derive the closed-form solutions of optimal time and power allocation in a network with symmetric links. Then, we extend our solution to a general network with asymmetric links. By employing Lyapunov optimization, an online stochastic resource allocation algorithm is proposed to obtain the maximum network throughput. It has been shown that the proposed algorithm can achieve close-to-optimal network throughput while maintaining the stability of the system. Finally, extensive simulations validate the analysis and demonstrate the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

This paper considers secure simultaneous wireless information and power transfer (SWIPT) in cell-free massive multiple-input multiple-output (MIMO) systems. The system consists of a large number of randomly (Poisson-distributed) located access points (APs) serving multiple information users (IUs) and an information-untrusted dual-antenna active energy harvester (EH). The active EH uses one antenna to legitimately harvest energy and the other antenna to eavesdrop information. The APs are networked by a centralized infinite backhaul which allows the APs to synchronize and cooperate via a central processing unit (CPU). Closed-form expressions for the average harvested energy (AHE) and a tight lower bound on the ergodic secrecy rate (ESR) are derived. The obtained lower bound on the ESR takes into account the IUs’ knowledge attained by downlink effective precoded-channel training. Since the transmit power constraint is per AP, the ESR is nonlinear in terms of the transmit power elements of the APs and that imposes new challenges in formulating a convex power control problem for the downlink transmission. To deal with these nonlinearities, a new method of balancing the transmit power among the APs via relaxed semidefinite programming (SDP) which is proven to be rank-one globally optimal is derived. A fair comparison between the proposed cell-free and the colocated massive MIMO systems shows that the cell-free MIMO outperforms the colocated MIMO over the interval in which the AHE constraint is low and vice versa. Also, the cell-free MIMO is found to be more immune to the increase in the active eavesdropping power than the colocated MIMO. [ABSTRACT FROM AUTHOR]

The growing demand to make wireless data services 5G compatible has necessitated the development of an energy-efficient approach for an effective new wireless environment. In this paper, we first propose a cognitive sensor node (CSN) based game theory for deriving energy via a primary user-transmitted radio frequency signal. Cognitive users’ time was segmented into three phases based on a time switching protocol: energy harvest, spectrum sensing and data transmission. The proposed model chooses the optimal energy-harvesting phase as the effected factor. We further propose a distributed energy-harvesting model as a utility function via pricing techniques. The model is a non-cooperative game where players can increase their net benefit in a selfish manner. Here, the price is described as a function pertaining to transmit power, which proves that the proposed energy harvest game includes Nash Equilibrium and is also unique. The best response algorithm is used to achieve the green connection between players. As a result, the results obtained from the proposed model and algorithm show the advantages as well as the effectiveness of the proposed study. Moreover, energy consumption was reduced significantly (12%) compared to the benchmark algorithm because the proposed algorithm succeeded in delivering energy in micro which is much better compared to previous studies. Considering the reduction and improvement in power consumption, we could say the proposed model is suitable for the next wireless environment represented in 5G. [ABSTRACT FROM AUTHOR]

A new concept of simultaneous wireless information and power transfer (SWIPT) is proposed, based on multiplexing a continuous-phase modulated (CPM) information transfer signal and a multitone power transfer (PT) signal. The tones of the PT signal have frequencies falling into low-power sub-bands and/or spectral null frequencies of the CPM signal. Therefore, the interference of the PT signal to the CPM signal is minimized and, simultaneously, the CPM and PT signals can be separated by the corresponding complementary filters in the receiver. Numerical evaluations show that the proposed PT signal design practically entails a negligible loss of CPM detection performance. [ABSTRACT FROM AUTHOR]

Future wireless networks demand high spectral efficiency, energy efficiency and reliability. Cooperative non-orthogonal multiple access (NOMA) with simultaneous wireless information and power transfer (SWIPT) is considered as one of the novel techniques to meet this demand. In this work, an adaptive power allocation scheme called SWIPT based adaptive power allocation (SWIPT-APA-NOMA) is proposed for a power domain NOMA network. The proposed scheme considers the receiver sensitivity of the end users while calculating the power allocation coefficients in order to prevent wastage of power allocated to user in outage and by offering priority to any one of the users to use maximum harvested power. A detailed analysis on the bit error rate (BER) performance of the proposed scheme is done and closed form expression is obtained. Simulations have been carried out with various parameters that influence the receiver sensitivity and the results show that the network achieves better outage and BER performance using the proposed scheme. It is found that the proposed scheme leads to a ten-fold decrease in transmit power for the same error performance of a fixed power allocation scheme. Further, it offers 96.06% improvement in the capacity for a cumulative noise figure and fading margin of 10 dB. [ABSTRACT FROM AUTHOR]

The traditional simultaneous wireless information and power transfer (SWIPT) system uses a part of signals to decode information, and the other part is used for harvesting energy, so that the device can be charged while working. However, the problems, such as the independent antenna and the feeble signal power and energy, greatly restrict the area of rate-energy region, thus leading to a big deviation between the theoretical value and the actual value. To solve these problems, a transmission scheme of SWIPT based on time reversal (TR) is proposed. Considering the general multi-input and single-output wireless communication system, on the one hand, the temporal and spatial focus of TR is used to increase the signal strength at the receiving end, on the other hand, the Kronecker model is used to theoretically build the transmission process on the condition of relevant antennas. After that the closed expression of the rate-energy region will be derived. The correctness of the formulary in different conditions is verified through the results of Monte Carlo simulation. The area of the rate-energy region is increased remarkably by comparing with the performance of SWIPT-MISO. [ABSTRACT FROM AUTHOR]

Energy harvesting (EH) is an eminent solution to perpetuate the lifetime of energy-constrained relay nodes in wireless sensor networks (WSNs). This paper considers a multi-hop amplify-and-forward (AF) network in which relay nodes with EH capability harvest energy inherent in the source transmitted radio frequency (RF) signal and use the harvested energy for signal transmission. Based on the time switching and power splitting EH receiver designs, we have examined the performance of, (i) time switching based relaying (TSR) and (ii) power splitting based relaying (PSR) protocols in multi-hop AF network, with throughput as the figure of merit. The numerical analysis reveals that, PSR outperforms TSR at high signal-to-noise ratio (SNR) whereas TSR outperforms PSR at low SNR, in multi-hop AF-WSNs with energy harvesting. [ABSTRACT FROM AUTHOR]

Simultaneous wireless information and power transfer (SWIPT) has been widely used in multi-input single-output (MISO) systems to transmit information and energy simultaneously from the base station (BS) towards the users. The traditional approach used in the literature is based on space-division multiple access (SDMA) method by using the multi-user linear precoding technique, where the information decoding is done by considering the multi-user interference as noise. Recently, the novel rate-splitting multiple access (RSMA) method, based on partially decode the multi-user interference and partially treat that interference as noise, has been shown to outperform the SDMA method in multi-user MISO systems. Motivated by the superior performance of RSMA, we consider a multi-user MISO SWIPT system applying the RSMA method, where multiple energy-constrained users are equipped with a power-splitting structure to harvest energy and decode information simultaneously. In particular, we investigate the optimal precoders and power-splitting ratios design to minimize the total transmit power at the BS, subject to constraints of the minimum data rate for users, minimum energy harvesting by users, and maximum power at the BS. The proposed solution for the formulated non-convex problem is based on two phases. First, we convert the non-convex problem into bilevel programming where the upper optimization problem is solved by using particle swarm optimization. Second, we propose two algorithms to solve the inner optimization problem based on a semidefinite relaxation method or a successive interference cancellation method. Numerical results show that RSMA achieves significant improvement over SDMA in reducing the total transmit power. [ABSTRACT FROM AUTHOR]

We consider a multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) network in which a source node, Alice, communicates with an energy-harvesting destination node, Bob, in the presence of a passive eavesdropper. To secure the wireless transmission, Alice generates a hybrid artificial noise (AN) in both frequency and time domains. Moreover, in order to collect more energy, Bob splits the received signal power of the cyclic prefix of each OFDM block. We then propose two non-convex optimization problems to balance both the need for security and the need for harvesting energy at Bob. While one considers maximizing the secrecy rate, the other approach aims at maximizing the harvested energy. Path-following algorithms of low computational complexity are developed and evaluated. Our numerical results show the gain of our proposed scheme and the effectiveness of our proposed algorithms. [ABSTRACT FROM AUTHOR]

To achieve a high reliable and energy-saving green communication, we investigate a multisource simultaneous wireless information and power transfer (SWIPT)-based coded cooperation where the relay can realize information decoding and energy harvesting. Firstly, a class of naturally rate compatible low-density parity-check (LDPC) codes–quasi-cyclic repeat-accumulate (QC-RA) codes is introduced, and the joint parity-check matrix corresponding to the QC-RA codes employed by the multiple sources and relay is deduced. Based on the joint parity-check matrix, we jointly design the QC-RA codes to cancel all the short girth cycles. Then, by exploiting the rate compatible characteristic of QC-RA codes, we propose a new SWIPT protocol—codeword splitting protocol for the proposed system, which has the characteristics of lower complexity, higher efficiency, no strictly bit synchronization limitation, and less hardware requirement. The results show that the bit error rate (BER) performance of the proposed system employing jointly designed QC-RA codes clearly outperforms that of general RA codes. Theoretical analysis and numerical simulations also demonstrate the superiority of the proposed codeword splitting protocol. [ABSTRACT FROM AUTHOR]

In this paper, we consider simultaneous wireless information and power transfer (SWIPT) in a multiple-input single-output interference channel (IC) system where the power-splitting (PS) receivers utilize linear/nonlinear energy-harvesting (EH) models. The functions that express the relationship between the input radio frequency power and the output direct current harvested energy of the EH circuits are usually assumed to be linear in recent SWIPT works, while the nonlinear function is suitable for practical data. In a SWIPT IC system, two important targets are sum harvested energy maximization and harvested energy efficiency maximization at the PS receiver, and they are investigated under linear/nonlinear EH models. Thus, some nonconvex resource allocation problems with the two targets and linear/nonlinear EH models are formulated to jointly optimize beamforming vectors at the transmitters and the PS ratios at the receivers. By exploiting a successive convex approximation method and a semidefinite relaxation (SDR) technique, iterative algorithms are proposed to obtain local optimal solutions. Interestingly, the optimal solution to the subproblem is proven to satisfy the rank-1 constraint of the SDR technique. Finally, numerical experiments illustrate effective performance from the proposed solutions, in comparison with some special schemes. [ABSTRACT FROM AUTHOR]

A full-duplex, amplify-and-forward multiple relay system employing simultaneous wireless information and power transfer receivers operating in interference channels is studied. Since all links want to maximize their own achievable rate, a power allocation problem under transmit power and energy harvesting constraints is developed. Through alternative optimization, a distributed iterative water-filling algorithm based on game theory with provable convergence is devised. The existence and uniqueness of a Nash equilibrium point are both guaranteed and the convergence of the proposed algorithm is examined using a diagonally strict concavity condition. Numerical results show that the proposed algorithm is convergent and can achieve a higher sum rate than previous schemes. [ABSTRACT FROM AUTHOR]

This paper investigates the optimal transmit beamforming design of simultaneous wireless information and power transfer (SWIPT) in the multiuser multiple-input-single-output (MISO) downlink with specific absorption rate (SAR) constraints. We consider the power splitting technique for SWIPT, where each receiver divides the received signal into two parts: one for information decoding and the other for energy harvesting with a practical non-linear rectification model. The problem of interest is to maximize as much as possible the received signal-to-interference-plus-noise ratio (SINR) and the energy harvested for all receivers, while satisfying the transmit power and the SAR constraints by optimizing the transmit beamforming at the transmitter and the power splitting ratios at different receivers. The optimal beamforming and power splitting solutions are obtained with the aid of semidefinite programming and bisection search. Low-complexity fixed beamforming and hybrid beamforming techniques are also studied. Furthermore, we study the effect of imperfect channel information and radiation matrices, and design robust beamforming to guarantee the worst-case performance. Simulation results demonstrate that our proposed algorithms can effectively deal with the radio exposure constraints and significantly outperform the conventional transmission scheme with power backoff. [ABSTRACT FROM AUTHOR]

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In this paper, we study the unmanned aerial vehicles (UAV) assisted relaying communication system, where a UAV acts the mobile relay and provides the information transfer from the source to the destination. The simultaneous wireless information and power transfer techniques are considered at the UAV relays, where the UAV harvests energy from the source node, and exclusively uses the harvested energy for the data relaying. To maximize the system throughput, we jointly consider the UAV trajectory optimization and resource allocation problem, where the UAV trajectory is optimized the UAV positions to harvest the benefits of the line-of-sight links, and resource allocation, including power allocation and the subcarrier allocation, is used to achieve optimal network performance with the power constraints. An alternating maximization algorithm is proposed to solve the optimization problem, in which the UAV trajectory optimization and resource allocation are solved iteratively to maximize the total throughput. Compared with other benchmarks, the proposed algorithm can achieve higher throughput by the benefits from UAV trajectory optimization and resource allocation. [ABSTRACT FROM AUTHOR]

In this paper, we study the resource allocation design for non-orthogonal multiple access (NOMA)-based cellular massive Internet-of-Things (IoT) enabled with simultaneous wireless information and power transfer (SWIPT). The design is formulated as a non-convex optimization problem, which takes into account practical and adverse factors, e.g., the channel uncertainty during channel state information (CSI) acquisition, the non-linear receiver during energy harvesting (EH) and the imperfect successive information cancellation (SIC) during the information decoding (ID). The originally harmful co-channel interference in massive access is coordinated to strike a balance between efficient information transmission and efficient energy harvesting via spatial beamforming. Subsequently, two robust beamforming algorithms are designed from the aspects of the weighted sum rate maximization and the total power consumption minimization, respectively. It is found that overall performance can be improved by adding BS antennas due to more array gains. Moreover, it is proved that the proposed algorithms can effectively alleviate the influence of adverse practical conditions and achieve the best performance compared to the baseline ones, which demonstrates the effectiveness and robustness of proposed algorithms for cellular massive IoT. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Integration of backscatter communication and wireless powered communication is a promising way to improve the performance of future Internet of Things (IoT) networks. However, this integration needs to be studied in practical scenarios with realistic models for the network elements. In this paper, we investigate optimal resource allocation in a backscatter assisted wireless powered communication network (BS-WPCN), where a piece-wise linear energy harvesting (EH) model is assumed at the users, which accounts for the saturation effect of practical energy harvesters. We study the problem of throughput maximization and apply a block coordinate descent (BCD) method to find the optimal allocation of resources for maximizing the total throughput. Numerical results demonstrate that the proposed scheme considerably improves the performance compared to the baseline scheme, which assumes linear EH model at the users. [ABSTRACT FROM AUTHOR]

In this paper, we jointly consider the downlink simultaneous wireless information and power transfer (SWIPT) and uplink information transmission in unmanned aerial vehicle (UAV)-assisted millimeter wave (mmWave) cellular networks, in which the user equipment (UE) locations are modeled using Poisson cluster processes (e.g., Thomas cluster processes or Matérn cluster processes). Distinguishing features of mmWave communications, such as different path loss models for line-of-sight (LOS) and non-LOS (NLOS) links and directional transmissions are taken into account. In the downlink phase, the association probability, and energy coverages of different tier UAVs and ground base stations (GBSs) are investigated. Moreover, we define a successful transmission probability to jointly present the energy and signal-to-interference-plus-noise ratio (SINR) coverages and provide general expressions. In the uplink phase, we consider the scenario that each UAV receives information from its own cluster member UEs. We determine the Laplace transform of the interference components and characterize the uplink SINR coverage. In addition, we formulate the average uplink throughput, with the goal to identify the optimal time division multiplexing between the donwlink and uplink phases. Through numerical results we investigate the impact of key system parameters on the performance. We show that the network performance is improved when the cluster size becomes smaller. In addition, we analyze the optimal height of UAVs, optimal power splitting value and optimal time division multiplexing that maximizes the network performance. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the energy-efficient hybrid precoding design for integrated multicast-unicast millimeter wave (mmWave) system, where the simultaneous wireless information and power transform is considered at receivers. We adopt two sparse radio frequency chain antenna structures at the base station (BS), i.e., fully-connected and subarray structures, and design the codebook-based analog precoding according to the different structures. Then, we formulate a joint digital multicast, unicast precoding and power splitting ratio optimization problem to maximize the energy efficiency of the system, while the maximum transmit power at the BS and minimum harvested energy at receivers are considered. Due to its difficulty to directly solve the formulated problem, we equivalently transform the fractional objective function into a subtractive form one and propose a two-loop iterative algorithm to solve it. For the outer loop, the classic Bi-section iterative algorithm is applied. For the inner loop, we transform the formulated problem into a convex one by successive convex approximation techniques and propose an iterative algorithm to solve it. Meanwhile, to reduce the complexity of the inner loop, we develop a zero forcing (ZF) technique-based low complexity iterative algorithm. Specifically, the ZF technique is applied to cancel the inter-unicast interference and the first order Taylor approximation is used for the convexification of the non-convex constraints in the original problem. Finally, simulation results are provided to compare the performance of the proposed algorithms under different schemes. [ABSTRACT FROM AUTHOR]

Radio frequency (RF) signals can be relied upon for conventional wireless information transfer (WIT) and for challenging wireless power transfer (WPT), which triggers the significant research interest in the topic of simultaneous wireless information and power transfer (SWIPT). By further exploiting the advanced non-orthogonal-multiple-access (NOMA) technique, we are capable of improving the spectrum efficiency of the resource-limited SWIPT system. In our SWIPT system, a hybrid access point (H-AP) superimposes the modulated symbols destined to multiple WIT users by exploiting the power-domain NOMA, while WPT users are capable of harvesting the energy carried by the superposition symbols. In order to maximize the amount of energy transferred to the WPT users, we propose a joint design of the energy interleaver and the constellation rotation-based modulator in the symbol-block level by constructively superimposing the symbols destined to the WIT users in the power domain. Furthermore, a transmit power allocation scheme is proposed to guarantee the symbol-error-ratio (SER) of all the WIT users. By considering the sensitivity of practical energy harvesters, simulation results demonstrate that our scheme is capable of substantially increasing the WPT performance without any remarkable degradation of the WIT performance. [ABSTRACT FROM AUTHOR]

Cooperative Non-Orthogonal Multiple Access (NOMA) with Simultaneous Wireless Information and Power Transfer (SWIPT) communication can not only effectively improve the spectrum efficiency and energy efficiency of wireless networks but also extend their coverage. An important design issue is to incentivize a full duplex (FD) relaying center user to participate in the cooperative process and achieve a win–win situation for both the base station (BS) and the center user. Some private information of the center users are hidden from the BS in the network. A contract theory-based incentive mechanism under this asymmetric information scenario is applied to incentivize the center user to join the cooperative communication to maximize the BS’s benefit utility and to guarantee the center user’s expected payoff. In this work, we propose a matching theory-based Gale–Shapley algorithm to obtain the optimal strategy with low computation complexity in the multi-user pairing scenario. Simulation results indicate that the network performance of the proposed FD cooperative NOMA and SWIPT communication is much better than the conventional NOMA communication, and the benefit utility of the BS with the stable match strategy is nearly close to the multi-user pairing scenario with complete channel state information (CSI), while the center users get the satisfied expected payoffs.

In order to support a massive number of resource-constrained Internet-of-Things (IoT) devices and machine-type devices, it is crucial to design a future beyond 5G/6G wireless networks in an energy-efficient manner while incorporating suitable network coverage expansion methodologies. To this end, this paper proposes a novel two-hop hybrid active-and-passive relaying scheme to facilitate simultaneous wireless information and power transfer (SWIPT) considering both time-switching (TS) and power-splitting (PS) receiver architectures, while dynamically modelling the involved dual-hop time-period (TP) metric. An optimization problem is formulated to jointly optimize the throughput, harvested energy, and transmit power of a SWIPT-enabled system with the proposed hybrid scheme. In this regard, we provide two distinct ways to obtain suitable solutions based on the Lagrange dual technique and Dinkelbach method assisted convex programming, respectively, where both the approaches yield an appreciable solution within polynomial computational time. The experimental results are obtained by directly solving the primal problem using a non-linear optimizer. Our numerical results in terms of weighted utility function show the superior performance of the proposed hybrid scheme over passive repeater-only and active relay-only schemes, while also depicting their individual performance benefits over the corresponding benchmark SWIPT systems with the fixed-TP.

In this paper, we study the physical layer security for simultaneous wireless information and power transfer (SWIPT)-based half-duplex (HD) decode-and-forward relaying system. We consider a system model including one transmitter that tries to transmit information to one receiver under the help of multiple relay users and in the presence of one eavesdropper that attempts to overhear the confidential information. More specifically, to investigate the secrecy performance, we derive closed-form expressions of outage probability (OP) and secrecy outage probability for dynamic power splitting-based relaying (DPSBR) and static power splitting-based relaying (SPSBR) schemes. Moreover, the lower bound of secrecy outage probability is obtained when the source’s transmit power goes to infinity. The Monte Carlo simulations are given to corroborate the correctness of our mathematical analysis. It is observed from simulation results that the proposed DPSBR scheme outperforms the SPSBR-based schemes in terms of OP and SOP under the impact of different parameters on system performance.

Communication between the primary and secondary sides is pivotal to the wireless power transfer (WPT) system. The system control commands and feedback information need simultaneous wireless information and power transfer (SWIPT). In this paper, a FSK-based SWIPT system with full-duplex communication via a shared channel is provided. Considering the complexity of the coupling relationship in this kind of full-duplex SWIPT system, this paper proposes an analysis method based on the transmission channel, studies the crosstalk between the power channel and the information channel, and between the forward and reverse transfer of information. A design method of full-duplex communication SWIPT system based on shared coupling channels is provided. A 60 W SWIPT prototype with a full-duplex communication rate of 20 kbps is built to verify the proposed method.

Full-duplex (FD) with simultaneous wireless information and power transfer (SWIPT) in wireless ad hoc networks has received increased attention as a technology for improving spectrum and energy efficiency. This paper studies the outage performance for a SWIPT-based decode-and-forward (DF) FD relaying network consisting of a single-antenna source S, a two-antenna relay R, and a multi-antenna destination D. Specifically, we propose four protocols, namely static time-switching factor with selection combining (STSF-SC), static time-switching factor with maximal ratio combining (STSF-MRC), optimal dynamic time-switching factor with selection combining (ODTSF-SC), and optimal dynamic time-switching factor with maximal ratio combining (ODTSF-MRC) to fully investigate the outage performance of the proposed system. In particular, the optimal time-switching factor from the ODTSF-SC and ODTSF-MRC methods is designed to maximize the total received data at the destination. In this context, we derive exact closed-formed expressions for all schemes in terms of the outage probability (OP). Finally, the Monte Carlo simulations are conducted to corroborate the theoretical analysis’s correctness and the proposed schemes’ effectiveness.

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.

This paper jointly investigates the downlink/uplink of wireless powered networks (WPNs), which are exposed to the effect of the cascaded near-far problem, i.e., the asymmetric overall degradation of the users' performance, due to different path-loss values. More specifically, assuming that the users are able to harvest energy both from interference and desired signals, higher path loss reduces the downlink rate of the far user, while it also negatively affects its uplink rate, since less energy can be harvested during downlink. Furthermore, if the far user is located at the cell edge, its performance is more severely impaired by interference, despite the potential gain due to energy harvesting from interference signals. To this end, we fairly maximize the downlink/uplink users' rates, by utilizing corresponding priority weights. Two communication protocols are taken into account for the downlink, namely, time division multiple access and non-orthogonal multiple access (NOMA), while NOMA with time sharing is considered for the uplink. The formulated multidimensional non-convex optimization problems are transformed into the equivalent convex ones and can be solved with low complexity. Simulations results illustrate that: 1) a relatively high downlink rate can be achieved, while the required energy is simultaneously harvested by the users for the uplink and 2) dowlink NOMA is a more appropriate option with respect to the network topology, especially when a high downlink rate is desired.

In this paper, we consider simultaneous wireless information and power transfer in a full-duplex (FD) communication system consisting of one FD access point A (FD-A) and one FD device B (FD-B), each being equipped with a pair of transmitter-receiver antennas for signal transmission and reception respectively. The power splitting (PS) scheme is adopted at FD-B to receive information and energy concurrently. In order to maximize the energy harvested by FD-B while considering the constraints of signal-to-interference-and-noise ratio (SINR) and maximum transmit power at both nodes, we jointly design the optimal transmit power of FD-A and FD-B, as well as the PS ratio of FD-B. Unfortunately, the primal problem is non-convex and is not always feasible with different parameters. Thus, we first present a set of conditions, under which the feasibility of the primal problem is guaranteed. Then, we derive the closed form of the optimal solution with the aid of analyzing the feasible region of the problem. Furthermore, the influences of the parameters on the maximum harvested energy are theoretically analyzed. Finally, simulation results are provided to verify the optimality of the proposed closed-form solution, to validate the analysis of the impact of parameters on the maximum harvested energy and to show the effectiveness of the proposed design, respectively.

Beamforming has the potential to improve the efficiency of simultaneous wireless information and power transfer (SWIPT) systems. Existing beamforming techniques have been focused on the downlink of SWIPT systems. In this paper, we optimize the beamformers and transmit duration to maximize the weighted sum rate of both the downlink and uplink in a multiuser multiple-input multiple-output (MIMO) SWIPT system. Specifically, we formulate and transform the problem into a weighted sum mean square error minimization, conduct difference of convex programming to decouple the downlink and uplink, and convert the problem to quadratic programming (QP), which can be solved iteratively in a centralized fashion. We also decentralize the QP problem using dual decompositions, and reduce the time-complexity without compromising the data rate. Moreover, our algorithms are extended to the case under imperfect channel state information. Confirmed by simulations, the proposed decentralization can dramatically reduce the time-complexity by orders of magnitude. The scalability of the proposed approach can be substantially enhanced to support medium to large networks.