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Energy harvesting technology can solve the problem of users' energy consumption in disaster areas. When disasters occur, some users are trapped and unable to recharge and need to collect power from neighboring users to transmit information. To solve the battery charging and information transmission problems of trapped user in disaster scenario, this paper proposes a relay-based on simultaneous wireless information and power transfer (SWIPT) energy harvesting and information transmission time allocation optimization algorithm. In this relay system, trapped user serves as the source node, the neighboring user terminals charge it in SWIPT mode and serve as relays to forward the information of trapped user to the base station. Under the constraint of collecting energy, the optimization problem of maximum system transmission rate is established. By studying the dual correlation of two-hop transmission and using Lambert' W function, the optimal ratio of energy harvesting time of trapped user to total time and the optimal ratio of the information transmission time of the trapped user to total information transmission time of relay system are obtained. Simulation results show that the proposed algorithm can provide energy for trapped user and improve data transmission rate. [ABSTRACT FROM AUTHOR]

A simultaneous wireless information and power transfer (SWIPT)-assisted cognitive overlay-based multiple input multiple output (MIMO) downlink (DL) cooperative relaying system has been considered wherein a secondary network comprising of an energy harvesting (EH) base station (BS) and possibly multiple fully wireless powered secondary users (SUs) share the spectrum of a primary network for information transmission and energy harvesting. In exchange, the secondary BS acts as a relay for the primary network and aids in transmitting information from the primary BS to the primary users (PUs) along with its own information using non-orthogonal transmission and the harvested energy. Closed-form expressions for the end-to-end outage probability (OP) at all the PUs and SUs have been obtained considering Rayleigh fading channel links and also sensitivity and saturation impairments at the energy harvesting nodes. Moreover, all the energy harvesting nodes have been assumed to be equipped with a finite battery for storing the harvested energy and rely solely on this stored energy for running the transceiver circuitry. Closed-form expressions have also been obtained to characterize the degradation due to the energy harvesting impairments and finite battery on the end-to-end OP of all the users. Furthermore, closed-form expressions for the asymptotic outage floor and diversity order have been obtained to analyze the performance of the system at high transmit power. Finally, simulation results have been presented to validate the analytical results derived and provide further insights into the performance of the system. [ABSTRACT FROM AUTHOR]

In this brief, we consider a wireless powered mobile edge computing (MEC) system, where the base station (BS) is integrated with a MEC server to support computation offloading. Meanwhile, the BS is equipped with renewable energy resource and can transfer energy to the wireless devices (WDs) and trade energy with the grid. The objective is to minimize the total energy cost of the operator under the offloading delay constraint by jointly optimizing the BS’s spot-market energy demand and transmit power as well as users’ offloading data size and transmit power. Both the perfect and imperfect channel state information (CSI) are considered. For the former, we propose a low computational-complexity algorithm for solving the formulated problem. For the latter, the non-convex problem is transformed into a convex one by using the successive convex approximation technique, and then an iterative algorithm is proposed. Simulation results verify the effectiveness of our proposed algorithms. [ABSTRACT FROM AUTHOR]

Solar harvesting, as the most mature environmental energy harvesting technology, can provide a convenient, low-carbon, and off-grid solution for energy-constrained WSN in remote environmental monitoring. However, the stochastic and intermittent nature of solar energy seriously affects network energy efficiency. In this paper, we jointly consider solar harvest deployment and scheduling for clustered WSN collaborating with SWIPT, where the solar-powered cluster (SC) coordinates SWIPT to periodically broadcast energy to a set of wireless charging nodes in full-duplex mode, each member node exhausts the recharged energy for data sensing and forwarding. To maximize network energy efficiency, we formulate a Solar harvesting collaborative SWIPT Energy Scheduling(SS-CoES) optimization problem, which jointly optimizes the deployment of SCs, the energy broadcast power with time allocation, and data sensing size under the constraint of the self-sustaining demand for network energy. Given the combinational nature of the energy deployment with its strong coupling with energy scheduling, we propose a multi-layer iteration decoupling optimization algorithm based on the Dinkelbach method, which decouples the problem into three subproblems and proposes the Hybrid discrete Firefly algorithm, Lagrangian dual subgradient algorithm, and bisection search method to obtain near-optimal feasible solutions. Simulation results show that the proposed SS-CoES can effectively maximize network energy efficiency and eliminate the dependence on the grid and move chargers, achieving rechargeable wireless sensor networks (RWSN) energy self-sustainability in remote areas. [ABSTRACT FROM AUTHOR]

Physical layer security of wireless communication network with intelligent reflecting surface (IRS) is investigated in this letter. At the access point (AP) transmission power and user nonlinear energy harvest constraints, maximum secrecy rate of full-duplex (FD) user which employs simultaneous wireless information and power transfer (SWIPT) technology is achieved by jointly optimizing transmit beamformer of AP, IRS phase shift, and artificial noise power of FD user. Due to its undesirable properties, such as coupling of multiple optimization variables and non-convex objective function, original optimization problem is hard to be handled. We solved this problem by an alternating optimization algorithm consisting of semi-definite relaxation, Charnes-Cooper transform and continuous phase shifting discretization techniques to obtain a feasible suboptimal solution. Simulation results demonstrate that although may only guarantee to convergence a local optimal, proposed algorithm still achieves the best security rate comparing to the benchmark algorithms with the computational efficiency sacrificing. [ABSTRACT FROM AUTHOR]

Intelligent reflecting surface (IRS) cooperated with the simultaneous wireless information and power transfer (SWIPT) can reinforce the desired signal and deal with the energy supply problem effectively. By leveraging the on-demand mobility of unmanned aerial vehicles (UAVs), the IRS cooperated SWIPT can be deployed in more flexible and reliable scenarios. In this article, we investigate the UAV-mounted IRS-assisted SWIPT for Internet of Things (IoT) networks. In particular, a UAV-mounted IRS is deployed to assist the information transmission and power transfer from the access point to several IoT devices simultaneously. Taking full advantage of the UAV-mounted IRS in attending multiple IoT devices flexibly, a time division multiple access (TDMA)-based scheduling protocol is proposed to serve different IoT devices alternatively during the UAV flying along an optimized trajectory with the information and power transfer executed. Then, an optimization problem of maximizing the minimum average achievable rate of multiple devices is formulated with the specific energy harvesting requirement guaranteed. To solve the nonconvex problem, we leverage the successive convex approximation and block coordinate descent methods to develop an iterative algorithm. Simulation results demonstrate that with the help of the more flexible and reliable UAV-mounted IRS, the minimum achievable rate of the IoT network can be significantly improved. [ABSTRACT FROM AUTHOR]

This work investigates the secrecy outage performance of a dual-hop relaying network with an untrustworthy energy-constrained amplify-and-forward relay. A destination-based jamming technique is adopted in order to prevent the relay from decoding confidential messages from the source. Additionally, three time switching-based wireless energy transfer strategies are investigated for supplying power to the relay. For these three strategies, we derive simple closed-form asymptotic expressions for the secrecy outage probability at high signal-to-noise ratio. Moreover, we provide analytical expressions for the optimum power allocation factor for the information transmission phase. Finally, Monte Carlo simulations are carried out to verify the theoretical results through different illustrative cases. [ABSTRACT FROM AUTHOR]

This paper investigates a wireless powered unmanned aerial vehicle (UAV) communication network with backscatter and caching technologies. Specifically, we assume a self-energized UAV with a cache memory is deployed as a flying backscatter device (BD), term the UAV-enabled BD (UB), to relay the source’s signals to the destination. Whereas the source S can act as a wireless charging station or a base station to supply power or transmit information to the UB using the dynamic time splitting (DTS) method. The UAV utilizes its harvested energy for backscattering (i.e., passive communication) and transmit information (i.e., active communication) to the destination. In this context, we aim to maximize the total throughput by jointly optimizing the DTS ratio and the UB’s trajectory with caching capability at the UB. The formulation is troublesome to solve since it is a non-convex problem. To find solutions, we decompose the original problem into two sub-problems, whereas we first optimize the DTS ratio for a given UB’s trajectory and the UB’s trajectory optimization for a given DTS ratio. By using the KKT conditions, a closed-form expression for the optimal value of the DTS ratio is obtained, greatly reducing the computation time. Moreover, the solution of the second sub-problem can be acquired by adopting the successive convex approximation (SCA) technique. Consequently, an efficient alternating algorithm is proposed by leveraging the block coordinate descent (BCD) method. To show the advantages of the proposed BCD-based algorithm, we also provide the solution of the original problem applying the inner approximation (IA) method. Finally, the intensive numerical results demonstrate that our proposed schemes achieve significant throughput gain in comparison to the benchmark schemes. [ABSTRACT FROM AUTHOR]

Interference is a detrimental factor for information decoding, but it can be a helpful resource for energy harvesting in a wireless powered network. Considering a two-way wireless powered interference channel, in this study, we present a simultaneous wireless information and power transfer (SWIPT)-then-wireless information transfer (WIT) protocol. In this protocol, transmitters perform SWIPT, and receivers receive both information and energy simultaneously in the forward link (FL). Then, the receivers perform WIT using the harvested energy in the backward link (BL). To maximize the weighted sum rate of the FL and BL, we jointly optimize the transmit power and energy harvesting (EH) ratio according to time switching and power splitting policies. To solve this non-convex optimization problem, we propose an iterative power control and energy harvesting algorithm based on dual methods that reduce computational complexity. The results show that the proposed algorithm finds the optimal transmit power and EH ratio suitably and thus maximizes the weighted sum rate. Consequently, the proposed SWIPT-then-WIT protocol expands the achievable rate region significantly compared with conventional schemes that do not adaptively control the transmit power and EH ratio. [ABSTRACT FROM AUTHOR]

This paper proposes a multi-agent double deep Q network (DDQN)-based approach to jointly optimize the beamforming vectors and power splitting (PS) ratio in multi-user multiple-input single-output (MU-MISO) simultaneous wireless information and power transfer (SWIPT)-enabled heterogeneous networks (HetNets), where a macro base station (MBS) and several femto base stations (FBSs) serve multiple macro user equipments (MUEs) and femto user equipments (FUEs). The PS receiver architecture is deployed at FUEs. An optimization problem is formulated to maximize the achievable sum information rate of FUEs under the constraints of the achievable information rate requirements of MUEs and FUEs and the energy harvesting (EH) requirements of FUEs. Since the optimization problem is challenging to handle due to the high dimension and time-varying environment, an efficient multi-agent DDQN-based algorithm is presented, which is trained in a centralized manner and runs in a distributed manner, where two sets of deep neural network parameters are jointly updated and trained to tackle the problem and avoid overestimation. To facilitate the presented multi-agent DDQN-based algorithm, the action space, the state space and the reward function are designed, where the codebook matrix is employed to deal with the complex transmit beamforming vectors. Simulation results validate the proposed algorithm. Notable performance gains are achieved by the proposed algorithm due to considering the beam directions in the action space and the adaptability to the Doppler frequency shifts. Besides, the proposed algorithm is shown to be superior to other benchmark ones numerically. [ABSTRACT FROM AUTHOR]

Abstract 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.

In this paper, we investigate the performance of a hybrid receiver-based simultaneous wireless information and power transfer (SWIPT) two-way relay network over Nakagami-m faded channels. A hybrid receiver is adopted at the relay node that utilizes both the time switching (TS) and power splitting (PS) protocols for energy harvesting and information transmission. Amplify-and-forward relaying protocol is utilized at the relay node to process the information in half-duplex mode. In the considered network, impact of a practical non-linear power amplifier (NLPA) at the relay node is considered. Selection combining is performed at the destination node to utilize the direct-link and relay assisted signals. For the considered system, the analytical expressions of outage probability (OP) and asymptotic OP are derived over Nakagami-m faded channels for both the integer and non-integer value of m. The analytical expression of the system throughput and energy efficiency of the considered network are also derived. Further, the analytical expression of ergodic capacity is derived in terms of the Meijer-G function. By utilizing a cumulative distribution function based approach, analytical expressions of average symbol error rate (ASER) for general order hexagonal quadrature amplitude modulation (QAM), general order rectangular QAM, and 32-cross QAM schemes are derived. For different QAM constellations, a comparative ASER analysis is also illustrated. Furthermore, the impact of TS factor, PS ratio, energy conversion efficiency, NLPA, and threshold data-rates on the considered network is also highlighted. Finally, Monte-Carlo simulations are performed for validation of the derived analytical expressions. [ABSTRACT FROM AUTHOR]

Wireless power transfer technologies such as simultaneous wireless information and power transfer (SWIPT) have shown significant potential to revolutionise the design of future wireless communication systems. When the only energy source is from the wireless signals that are mainly intended for information communications, the sustainability and outage performance of SWIPT systems become critical factors in theoretical evaluation and practical applications. This paper firstly models the energy harvesting and energy consumption of the power splitting protocol based SWIPT systems to investigate the general sustainability condition. We further model the power and information transfer outage probabilities using Markov Chains, which are unique for SWIPT systems since they both could cause communication outage. We further demonstrate how to apply the closed-form expression of the outage to optimise the key parameter of splitting ratio for SWIPT systems. Hardware and numerical experiments demonstrate the validity of the proposed model and outage analysis, and confirm the effectiveness of the solution to calculate the optimal splitting ratios under different signal and channel conditions. [ABSTRACT FROM AUTHOR]

This paper introduces a unified deep neural network (DNN)-based precoder for two-user multiple-input multiple-output (MIMO) networks with five objectives: data transmission, energy harvesting, simultaneous wireless information and power transfer, physical layer (PHY) security, and multicasting. First, a rotation-based precoder is developed to solve the above problems independently. Rotation-based precoding is a new precoding and power allocation scheme that beats existing solutions for PHY security and multicasting and is reliable in different antenna settings. Next, a DNN-based precoder is designed to unify the solution for all objectives. The proposed DNN concurrently learns the solutions given by conventional methods, i.e., analytical or rotation-based solutions. A binary vector is designed as an input feature to distinguish the objectives. Numerical results demonstrate that, compared to the conventional solutions, the proposed DNN-based precoder reduces on-the-fly computational complexity more than an order of magnitude while reaching near-optimal performance (99.45% of the averaged optimal solutions). The new precoder is also more robust to the variations of the numbers of antennas at the receivers. [ABSTRACT FROM AUTHOR]

The performance of simultaneous wireless information and power transfer (SWIPT) is investigated for an intelligent reflective surface (IRS)-aided wireless system. Tight bounds for the achievable rate and harvested energy are derived in closed-form for the time-switching (TS) and power-splitting (PS) protocols by adopting linear/non-linear energy harvesting models. The achievable rate-energy trade-off of IRS-aided SWIPT is quantified, and the effects of phase-shift quantization at the IRS are investigated. The impact of TS/PS factors, the number of reflective elements, reflective coefficients, and linear versus non-linear energy harvesting models is also investigated through analytical results and Monte-Carlo simulations. [ABSTRACT FROM AUTHOR]

Simultaneous wireless information and power transfer can be realized by means of an integrated receiver, where both the energy harvester and the information decoder operate on the rectified received signal. We investigate the effect of the non-linearity of the rectifier on the error performance of the information decoder when transmitting over a Nakagami- $m$ fading channel. Through analysis and simulation, we demonstrate that the low-noise error performance strongly depends on the small-signal behavior of the rectifier, even when the average operating point is outside the small-signal area. Approximating for analysis purposes the rectifier by a quadratic detector yields accurate bit error rate results for the fading channel in the low-noise regime, whereas an over-optimistic error performance is obtained when applying the envelope detector approximation. [ABSTRACT FROM AUTHOR]

As the number of communication devices rapidly grows, limited radio resources hardly accommodate the every-increasing tele-traffic. As a remedy, spatial modulation (SM) is capable of modulating additional information onto the index of transmit or receive antennas, which results in substantial improvement of spectrum efficiency. Moreover, radio frequency (RF) signal based simultaneous wireless information and power transfer (SWIPT) has attracted tremendous research interest, in order to relieve the energy-thirst of massively deployed low-power communication devices. In this paper, a receive spatial modulation (RSM) aided SWIPT system with finite alphabets is studied, in which three different transmission schemes are proposed, namely the general scheme, the superimposed scheme and the distinct scheme. Furthermore, the performance of these transmission schemes in the RSM aided SWIPT system is theoretically analysed. The energy harvested by the receiver is then maximised by jointly optimising the transmit power of the information signal and the covariance matrix of the energy signal as well as the power splitting ratio, while satisfying the quality of service of the wireless information transfer. At last, simulation results validate our theoretical analysis, while they also demonstrate that the distinct scheme has the best SWIPT performance among these three transmission schemes. [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]

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]

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]

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]

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 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]

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]

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]

This letter investigates the error rate performance of relay-assisted non-orthogonal multiple access networks with simultaneous wireless information and power transfer. In particular, we derive a novel closed-form expression for the pairwise error probability (PEP) of all users, which is then used to derive a union bound on the error rate performance. Additionally, we derive an asymptotic closed-form expression of the PEP in the high signal-to-noise ratio regime and demonstrate that the maximum achievable diversity order for the underlying scenario is equal to one. Numerical and simulation results are presented to corroborate the analysis and to investigate the error rate performance of all users under different energy harvesting scenarios. [ABSTRACT FROM AUTHOR]

In this letter, we investigate the secrecy performance of the simultaneous wireless information and power transfer (SWIPT) system over generalized- $K$ fading channels. After analyzing the communications scenario, we derive the closed-form expression for the secrecy outage probability (SOP), and give some simplified expressions for SOP in some special cases. Effective secrecy throughput is also investigated to capture the amount of secure transmitted information. To derive the diversity order, the asymptotic SOP is also analyzed when the average signal-to-noise ratio is sufficiently large. Finally, numerical results are used to validate the correctness of our derived expressions. [ABSTRACT FROM AUTHOR]

The performance of space shift keying (SSK) modulation using energy harvesting amplify and forward (AF) relaying is analyzed over the Rayleigh fading channel. Simultaneous wireless information and power transfer technique eliminates the need of power supply at the relay in cooperative communication. However, energy tapped from an information signal for harvesting would degrade receiver performance. At the same time, the distance between the relay and the receiver can be increased due to the power splitting-based relay with the SSK modulation. New closed-form expressions for average bit error probability (ABEP) is derived with a single AF relay and an upper bound expression for multiple relays with a direct link. Furthermore, the ABEP is analyzed for a partial relay selection operation. The numerical and computer simulation results are presented with the discussion. [ABSTRACT FROM AUTHOR]

Max–min fairness optimal rate-energy trade-off of simultaneous wireless information and power transfer is derived with imperfectly estimated channels at the massive multiple-input multiple-output base-station and statistical channel knowledge at the users. The optimal transmit power control coefficients, common harvested energy, and common achievable user rates are derived for time-switching and power-splitting protocols. [ABSTRACT FROM AUTHOR]

We study the optimal resource allocation in the MIMO-based wireless powered underground sensor network (WPUSN) for throughput maximization. Compared to existing WPUSNs that rely on single-antenna wireless power transfer techniques to transmit geological data in real time, the MIMO-based WPUSN can be adaptively replenished by beamforming. Note that, WPUSN has two remarkable features: the severe wireless path loss and diverse data traffic demands from different underground sensors. Further, by considering the quality of service (QoS) with respect to diverse data traffic demands and communication reliability, the throughput of the network is considered as a crucial measure, which suffers from a significant loss since it has to encounter a seriously unreasonable energy scarcity under the strong-heterogeneity underground environment. To this end, the MIMO is used to eliminate the unreasonable distribution of harvested energy resources and improve effective throughput for WPUSNs. In this paper, we formulate a non-convex optimization problem to maximize the system throughput in MIMO-based WPUSNs with QoS assurance. Specifically, we find there exists no mutual forbearance between the time allocation and the beamforming weight, and transform this non-convex problem to a solvable convex-constrained problem with convex sub-problems. Finally, we give a closed-form solution and show its advantages by simulations. [ABSTRACT FROM AUTHOR]

Integrating radio frequency energy harvesting into wireless communications to support simultaneous wireless information and power transfer (SWIPT) is a promising technique to extend lifetime of energy-limited wireless cooperative networks. In this paper, multiuser resource optimization for incremental amplify-and-forward orthogonal frequency division multiplexing relaying systems with SWIPT is investigated. To maximize the overall achievable rate, multi-dimensional degrees of freedom (e.g., power allocation, subcarrier assignment, incremental policy, and power splitting ratio) are jointly optimized, subject to the transmission power as well as the quality of service constraints. The optimization problem is formulated as a mixed-integer nonlinear programming and the corresponding solution entails prohibitively high computational complexity. This motivates us to find a suboptimal solution with the aim of realizing a better tradeoff between performance and complexity. Specifically, dual decomposition and subgradient algorithm are applied to achieve this goal and the essence of our proposal is that the variables to be optimized are sequentially and iteratively derived. Finally, complexity analysis and simulation results are shown to verify the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

Non-orthogonal multiple access (NOMA) has been recently considered in millimeter-wave (mmWave) massive MIMO systems to further enhance the spectrum efficiency. In addition, simultaneous wireless information and power transfer (SWIPT) is a promising solution to maximize the energy efficiency. In this paper, for the first time, we investigate the integration of SWIPT in mmWave massive MIMO-NOMA systems. As mmWave massive MIMO will likely use hybrid precoding (HP) to significantly reduce the number of required radio-frequency (RF) chains without an obvious performance loss, where the fully digital precoder is decomposed into a high-dimensional analog precoder and a low-dimensional digital precoder, we propose to apply SWIPT in HP-based MIMO-NOMA systems, where each user can extract both information and energy from the received RF signals by using a power splitting receiver. Specifically, the cluster-head selection algorithm is proposed to select one user for each beam at first, and then the analog precoding is designed according to the selected cluster heads for all beams. After that, user grouping is performed based on the correlation of users’ equivalent channels. Then, the digital precoding is designed by selecting users with the strongest equivalent channel gain in each beam. Finally, the achievable sum rate is maximized by jointly optimizing power allocation for mmWave massive MIMO-NOMA and power splitting factors for SWIPT, and an iterative optimization algorithm is developed to solve the non-convex problem. Simulation results show that the proposed HP-based MIMO-NOMA with SWIPT can achieve higher spectrum and energy efficiency compared with HP-based MIMO-OMA with SWIPT. [ABSTRACT FROM AUTHOR]

This paper considers an MISO simultaneous wireless information and power transfer (SWIPT) system, where one transmitter serves multiple authorized receivers in the presence of several potential eavesdroppers (idle receivers). To prevent the information interception by eavesdroppers, artificial noise (AN) is embedded into the transmit signals. The non-linear energy harvesting (EH) model is adopted and a novel power-splitting (PS) EH receiver architecture is proposed. Stochastic uncertainty channel model (SUM) is considered for the idle receivers due to outdated channel feedback. A global energy efficiency (GEE) maximization problem is formulated by jointly optimizing the transmit beamforming vectors, the AN covariance matrix, and the PS ratios, under the minimal rate and secure transmission constraints of authorized receivers, the EH requirement constraints of idle receivers, and the total available power constraint at the transmitter. Since the problem is non-convex with no known solution, it is solved based on the following solution framework. Firstly, the PS ratios are optimized by using the bisection method and successive convex approximation (SCA), and then, the transmit beamforming vectors and the AN covariance matrix are jointly optimized by using a Dinkelbach’s Algorithm based method, where SCA is applied to solve its inner subproblem. It is theoretically proved that by involving AN, the system GEE can be improved. Numerous results show that system GEE first increases and then keeps unchanged with the increment of the total available power, but it first keeps unchanged and then decreases with the increment of the minimal rate requirement. It is also observed that compared with traditional EH receiver architecture and linear EH model, our proposed PS EH receiver architecture is able to achieve higher GEE and avoid false output power at idle receivers. [ABSTRACT FROM AUTHOR]

This paper considers simultaneous wireless information and power transfer (SWIPT) mechanisms in a relaying-assisted ultra-reliable low latency communication network operating with finite blocklength codes. The reliability of the network is maximized by the optimal selection of SWIPT parameters under both a power splitting (PS) protocol and a time switching (TS) protocol. In addition, we propose a protocol to improve the reliability performance by introducing a tradeoff between the PS and TS protocols. To further improve the reliability, a joint design is provided, which aligns the optimal selection of SWIPT parameters together with a blocklength allocation between two relaying hops. Via simulations, we validate our analytical model and show that the proposed algorithm achieves the same performance as that obtained with exhaustive search. In addition, we evaluate the considered network, and characterize the impact of blocklength, transmit power, and packet size on the reliability of the considered SWIPT-enabled relaying network. Finally, the performance advantages of the proposed protocol (in comparison with the PS and TS protocols) and the proposed joint designs are investigated. [ABSTRACT FROM AUTHOR]

The joint design of beamforming and artificial noise vectors is proposed for the full-duplex simultaneous wireless information and power transferring (FD-SWIPT) systems when multiple eavesdroppers can wiretap information from FD base station (FD-BST) and FD user equipment (FD-UE). To guarantee high security and energy harvesting performance of the FD-SWIPT system, the proposed design is formulated as a sum-information-transmission-rate-maximization (SITRM) problem under information-leakage and energy constraints. Besides, we consider the fairness issue between uplink and downlink information-transmission rates by formulating a fairness-aware-SITRM (FA-SITRM) problem. Since the eavesdroppers can receive the information of FD-BST and FD-UE, the information-leakage region becomes non-convex and challenging to handle. Hence, we propose efficient algorithms to solve the SITRM and FA-SITRM problems optimally via semidefinite relaxation (SDR) and a 1-D search. In each search iteration, our proposed algorithms can recover the rank-one constraints when the application of SDR cannot obtain the optimal solutions. Moreover, we analyze the computational complexities and propose two suboptimal solutions to the formulated problems. For the SITRM problem, our numerical results show that the performance achieved by one of two suboptimal algorithms is close to the performance of optimal algorithm with increasing the maximum transmission power of FD-BST. [ABSTRACT FROM AUTHOR]

The distributed spatial modulation (DSM) protocol, which allows relays to forward the source’s data while simultaneously allowing the relays to transmit their own data, has been proposed by Narayanan et al. In this paper, we introduce two new protocols for enabling the DSM, consisting of single-antenna network nodes, with simultaneous wireless information and power transfer capability: power splitting-based DSM (PS-DSM) and energy recycling-based DSM (ER-DSM). More specifically, the PS-DSM relies on power splitters at the relay nodes to harvest energy transmitted from the source. On the other hand, the ER-DSM, by exploiting the inactive cooperating relays in DSM-based protocols, recycles part of the transmitted energy in the network, without relying on power splitters or time switches at the relays to harvest energy. This leads to an increase in the average harvested energy at the relays with reduced hardware complexity. Both the PS-DSM and the ER-DSM also retain all the original features of DSM. Due to its particular operating principle and specific advantages, we select the ER-DSM as the candidate for further mathematical analysis. More specifically, by considering a multi-state battery model, we propose an analytical framework based on a Markov chain formulation for modeling the charging/discharging behavior of the batteries at the relay nodes in the ER-DSM. Furthermore, based on the derived Markov chain model, we introduce a mathematical framework for computing the error probability of the ER-DSM, by explicitly taking into account, the effect of finite-sized batteries. The frameworks are substantiated with the aid of Monte Carlo simulations for various system setups. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the optimal throughput performance for simultaneous wireless information and power transfer relaying network in the presence of direct link between the source and the destination. By considering the direct link, system performance can be improved when the channel condition is good from source to destination. The cooperative network consists of a source, an amplify-and-forward relay, and a destination, where the relay harvests energy from the source and then uses the harvested energy to forward information to the destination. At the destination node, the signals from the direct link and relay are combined by the maximum ratio combining (MRC) method. The time switching (TS) relaying protocol is applied to enable energy harvesting and information processing simultaneously. At the same time, we made progress on analyzing the throughput of information transmission on the basis of the MRC method with power switching (PS) relaying protocol. Additionally, adaptive-MRC protocol is proposed based on the TS and PS relaying protocols, which can choose better mode to achieve the communication. The numerical analyses provide practical insights into the effect of various system parameters, such as energy harvesting time splitting ratio, source transmission rate, distance between nodes, and noise power at the destination and the relay. [ABSTRACT FROM AUTHOR]

For 5G wireless networks, low latency and high energy efficiency are two of the most critical key performance indicators. In this work, we propose a framework to consider these requirements simultaneously by applying the notions of effective capacity, effective energy efficiency, and simultaneous wireless information and power transfer (SWIPT). At first, we define the effective capacity and the effective energy efficiency of SWIPT in multiuser orthogonal frequency division multiple access systems by considering two practical schemes of SWIPT: time switching (TS) and power splitting (PS). Afterwards, we formulate two resource allocation problems to maximize the effective capacity and effective energy efficiency, respectively, subject to three constraints: minimum harvested power, average sum transmit power, and delay quality of service. Numerical results illustrate that there is a fundamental tradeoff between harvested power and the performance in terms of effective capacity and effective energy efficiency. Moreover, the efficiency of PS scheme over TS greatly depends on the minimum required harvested power and the number of users. [ABSTRACT FROM AUTHOR]

This paper investigates the secure transmit design for simultaneous wireless information and power transfer system under the non-linear energy harvesting (EH) model, where a transmitter sends confidential information and transfers energy to multiple information receivers (IRs) and EH receivers (ERs) with the existence of multiple eavesdroppers (Eves). To prevent confidential information leakage, multiple artificial redundant signals (MARSs) are embedded in the transmit signals. The goal is to minimize the total transmit power by jointly optimizing transmit beamforming vectors and the covariance matrixes of MARSs, such that the minimal information rate and EH requirements at IRs and ERs are guaranteed while making the received signal-to-Interference ratio at ERs and Eves lower than their information decoding thresholds. Both the non-robust and the robust designs are studied. For the non-robust design, the optimal solution is derived. For the robust design, an approximate optimal solution is obtained by using Gaussian randomization procedure. Simulation results show that compared with traditional non-MARS-aided beamforming design, our proposed design is superior in terms of the total required transmit power. It also shows that employing the non-linear EH model can avoid false output power at the ERs and/or save power at the transmitter. [ABSTRACT FROM PUBLISHER]

This paper investigates a secure wireless-powered multiantenna multicasting system, where multiple power beacons (PBs) supply power to a transmitter in order to establish a reliable communication link with multiple legitimate users in the presence of multiple eavesdroppers. The transmitter has to harvest radio frequency energy from multiple PBs due to the shortage of embedded power supply before establishing its secure communication. We exploit a novel and practical scenario that the PBs and the transmitter may belong to different operators and a hierarchical energy interaction between the PBs and the transmitter is considered. Specifically, the monetary incentives are required for the PBs to assist the transmitter for secure communications. This leads to the formulation of a Stackelberg game for the secure wireless-powered multiantenna multicasting system, where the transmitter and the PB are modeled as leader and follower, respectively, each maximizing their own utility function. The closed-form Stackelberg equilibrium of the formulated game is then derived, where we study various scenarios of eavesdroppers and legitimate users that can have impact on the optimality of the derived solutions. Finally, numerical results are provided to validate our proposed schemes. [ABSTRACT FROM PUBLISHER]

This paper investigates simultaneous wireless information and power transfer (SWIPT) in the ad hoc network, where access points (APs) with multiple antennas can transfer energy as well as information using a common spectrum resource. The receiving nodes decode the incoming information data (information decoding, ID) and/or harvest the RF energy (energy harvesting, EH), where two different receiving node architectures—time switching (TS) and power splitting (PS)—are considered. By using a stochastic geometry approach, we aim to analyze the transmission capacity and the harvested energy per unit area as performance measures of the SWIPT in the ad hoc network. From the analytical results, we can derive the optimal node densities of ID nodes and EH nodes for TS architectures and, furthermore, optimize the power splitting ratio jointly with the node density for the PS architectures such that the harvested energy per unit area is maximized when the target transmission capacity is given. The proposed node density optimization gives us a useful insight into the design of SWIPT-based ad hoc network, where we can show how densely the APs/nodes can be deployed in a given area and furthermore, find that the ad hoc network with PS receiving nodes outperforms that with TS receiving nodes for a large target transmission capacity, and vice versa. [ABSTRACT FROM AUTHOR]

This letter investigates the downlink achievable rates of massive multiple-input-multiple-output (MIMO) enabled simultaneous wireless information and power transfer (SWIPT) systems. Since the transmission range of massive MIMO SWIPT systems is quite short, the transmission channels are generally of line-of-sight. Therefore, by assuming Rician fading channels, this letter theoretically derives the approximate expressions of harvested energy and achievable rate. In addition, the corresponding asymptotic expressions are presented for large number of transmit antennas case. Simulation results are provided to demonstrate the accuracy of the derived expressions. [ABSTRACT FROM PUBLISHER]

In this paper, we consider the sum secrecy rate maximization problem in multiuser multiple-input single-output (MU-MISO) systems in the presence of multiple energy harvesters (EHs) which also have potential to wire-tap the information users (IUs). To facilitate delivering secure information to the IUs and increase the total harvested energy by the EHs simultaneously, we optimize the transmit beamforming vectors to direct the information signals toward the IUs and artificial noise (AN) toward the EHs. We assume that each EH relies on itself to decode the information signal intended for an individual IU. Therefore, the corresponding problem is to maximize the worst-case sum secrecy rate under transmit power and energy harvesting constraints. The problem is optimally solved by transforming it into a convex iterative program using a change of variables, semi-definite relaxation (SDR), and linearization of quadratic terms. We prove that rank-one optimal solutions for the IUs beamforming covariance matrices can be obtained from the optimal relaxed unconstrained solution. Also, we provide three suboptimal solutions based on null space projection and power control of the beamforming vectors for the low and high harvested energy constrained regions. A special case of cooperative EHs in which the EHs can collaboratively cancel the signal of all IUs except the one they intend to eavesdrop is also investigated, and the optimal solution is derived in a comparable way as in noncooperative EHs case. Our simulation results reveal an understanding of how the tradeoff between the AN and information signal can jointly improve both the sum secrecy rate and the total harvested energy. We also show that, within the low total harvested energy region, the suboptimal solution in which the AN is projected in the null space of the IUs channels outperforms the suboptimal solution which ignores AN alignment at the IUs, and vice versa over the high total harvested energy region; and the suboptimal solution that combines both of them achieves close to optimal performance. [ABSTRACT FROM PUBLISHER]

In this paper, the fundamental performance of the simultaneous wireless information and power transfer (SWIPT) system is studied. Unlike any existing works where the codelength was assumed to be infinity, we explicitly consider the case of the finite codelength, which is much more realistic especially for the practical SWIPT system due to its limited power and complexity. For the four well-known SWIPT schemes, we analyze the tradeoff between the rate and energy; then we study the optimality of those SWIPT schemes. Furthermore, to fully characterize the fundamental performance of the SWIPT system in the regime of finite codelength, we propose to additionally use the new tradeoff between the decoding error probability and the harvested energy. In the sense of this new tradeoff, we study the optimality of the four SWIPT schemes. For the analysis of the two types of tradeoffs, we consider two different cases: when the transmit power of symbols is adapted or not. For various scenarios, we provide useful insights into the performance of the SWIPT system in the finite codelength. [ABSTRACT FROM PUBLISHER]

In this letter, we investigate the energy efficiency optimization for simultaneous wireless information and power transfer in multiple-input-multiple-output wiretapping systems, which consist of one transmitter, multiple desired receivers (DRs), and multiple eavesdroppers. Specifically, considering non-linear energy harvesting model, we aim to maximize the ratio of the total harvested power at the DRs to the total power consumption at the transmitter, e.g., the harvested power efficiency, by jointly designing the transmit precoding matrix, the artificial noise covariance and the power splitting ratios, subject to the secrecy rate constraint. To solve the formulated highly non-convex non-linear single-ratio problem, we propose a successive convex approximation and constrained concave convex procedure-based iterative algorithm. Finally, our proposed algorithm is validated by some representative numerical results. [ABSTRACT FROM PUBLISHER]

This letter investigates the artificial noise aided beamforming design for secure simultaneous wireless information and power transfer in a two-tier downlink heterogeneous network (HetNet), where one femtocell underlays one macrocell in co-channel deployment. Each energy receiver in femtocell can be considered as a potential eavesdropper for messages intended for information receiver (IR). Our objective is to maximize the secrecy rate at IR subject to the signal-to-interference-plus noise ratio requirements of macro users, transmit power constraint and energy harvesting constraint. Due to the non-convexity of the formulated problem, it cannot be solved directly. Thus, we propose a novel reformulation by using first-order Taylor expansion and successive convex approximation (SCA) techniques. Furthermore, an SCA-based algorithm with low complexity is proposed to arrive at provably convergent solution. Finally, numerical results evaluate the performance of the proposed algorithm. [ABSTRACT FROM PUBLISHER]