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Reconfigurable Intelligent Surfaces (RIS) provides an emerging affordable solution by leveraging massive low-cost reconfigurable reflective array elements. In this letter, by utilizing low-cost passive reflecting elements, a joint hybrid beamforming with discrete phase shifts design is studied in RIS-assisted multiuser simultaneous wireless information and power transfer (SWIPT) systems. However, the formulated sum rate maximization problem is nonconvex and very challenging to solve. To overcome this difficulty, we decouple the original maximization problem into the digital-, phase shifts and analog subproblem. Specifically, for the nonconvexity of the digital subproblem, we perform the first order Taylor series expansion on the objective function, and then an iterative strategy is developed to tackle the difficulty of the maximum transmit power constraint imposed by discrete optimization variables. Subsequently, an effective convex optimization technique was employed to optimize reflecting elements of RIS. Finally, the greedy selection method based on minimum mean squared error (MMSE) scheme is proposed to solve the analog subproblem. Numerical simulations are conducted to demonstrate the performance advantages of the proposed scheme.

Simultaneous wireless information and power transfer can be achieved using an integrated receiver, where the incoming signal is rectified, and both the energy harvesting (EH) and the information detection (ID) operate on this rectified signal. Because phase information is lost at the input of the ID, commonly-used modulation techniques cannot be straightforwardly applied and biased M-ASK is used instead. We consider downstream communication over a Rician block-fading channel, from a multi-antenna hasestation to a number of single-antenna users. Multi-user interference is eliminated by applying zero-forcing preceding. Using a realistic rectifier model, we compare EH and ID performances of linear precoding (LP) and modified Tomlinson-Harashima preceding (THP). We add low-complexity algorithms to these precoders that optimize the user ordering and the constellation rotations. Moreover, we investigate the effect of the amplitude ratio rho(ASK) of' the constellation on the energy-rate trade-off. Compared to the same precoders without optimization, optimizing the user ordering, rotations and rho(ASK) considerably reduces the transmit power required to achieve a harvested power of -30 dBm or an average mutual information of (log(2) M)/2. Both with and without optimizations, THP outperforms LP in terms of EH and ID, but THP exhibits much larger gains when optimizations are applied.

In this letter, the design of coded modulation for simultaneous wireless information and power transfer (SWIPT) block-fading channels is proposed, for both power-splitting (PS) and time-switching (TS) nonlinear energy harvesting (EH). With PS, although the diversity-rate tradeoff is not affected, nonlinear EH requires asymmetric modulations design which leads to an information transfer (IT) performance penalty. We thus design an asymmetric circular quadrature amplitude modulation (ACQAM) scheme that provides large performance gains compared to conventional modulations. On the other hand, we show that TS negatively impacts the diversity-rate tradeoff of the coded modulation, while an optimal QAM can be employed in the IT phase. We next derive an upper bound on the average word error rate (WER) based on a pairwise error probability analysis for both EH methods. Finally, WER simulation results are shown together with the derived bounds.

In this paper, we study the fundamental limits of a simultaneous wireless information and power transfer communication system, which is facilitated by an intelligent reflecting surface (IRS). Specifically, we propose a low-complexity optimization scheme that optimizes iteratively the input probability distribution at the transmitter side and the phase shift coefficient at the IRS to enhance the information-energy capacity region. By using alternating optimization and Lagrangian decomposition, analytical expressions for the optimal input distribution and the phase shifts are derived which decrease the computational complexity of the proposed scheme. A novel joint optimization scheme is also proposed. systems. Numerical results show that the iterative optimization scheme almost achieves the same performance in comparison with the proposed joint optimization scheme while ensuring a reduced computation for high energy-harvesting thresholds.

As an advanced technology, simultaneous wireless information and power transfer (SWIPT), combined with the internet of things (IoT) devices, can effectively extend the online cycle of the terminal. To cope with the fluctuation of energy harvesting by the hybrid access points (H-AP), the energy cooperation base station is introduced to realize the sharing of renewable energy. In this paper, we study the SWIPT-enabled IoT networks with cooperation. Our goal is to maximize the energy efficiency of the system, and at the same time, we need to meet the energy harvesting constraints, user quality of service (QoS) constraints and transmission power constraints. We jointly solve the power allocation, time switching and energy cooperation problems. Because this problem is a nonlinear programming problem, it is difficult to solve directly, so we use the alternating variable method, the iterative algorithm is used to solve the power allocation and time switching problem, and the matching algorithm is used to solve the energy cooperation problem. Simulation results show that the proposed algorithm has obvious advantages in energy efficiency performance compared with the comparison algorithm. At the same time, it is also proved that the introduction of energy cooperation technology can effectively reduce system energy consumption and improve system energy efficiency.

This paper presents a general methodology based on the description of the inductive channel as virtual magnetic transmission-lines (VMGTLs). In comparison with other existing methods, VMGTL approach presents a better physical insight of the channel behavior since the model correctly preserves the energy flow between the transmitting and receiving coils. Besides that, it facilitates the integration into the analysis of highly nonlinear and dispersive structures such as metamaterial (MTM) lenses. Particularly, the virtual-TL analogy clarifies that the enhancement of the transmission gain between any two coils assisted by MTM is not due to an enhanced coupling between the drivers, as usually claimed, but to the emergence of propagating near-field modes supported by the MTM. This approach, by means of a parametric study, also indicates, for the first time, that MTMs could be employed not only for the increasing of power but also of data transfer due to the emergence of a sub-resonant region of minimum distortion. Nonetheless, since both effects are mutually exclusive, no passive MTM structure could simultaneously improve power and data transmission.

The advent of simultaneous wireless information and power (SWIPT) has been regarded as a promising technique to provide power supplies for an energy sustainable Internet of Things (IoT), which is of paramount importance due to the proliferation of high data communication demands of low-power network devices. In such networks, a multi-antenna base station (BS) in each cell can be utilized to concurrently transmit messages and energies to its intended IoT user equipment (IoT-UE) with a single antenna under a common broadcast frequency band, resulting in a multi-cell multi-input single-output (MISO) interference channel (IC). In this work, we aim to find the trade-off between the spectrum efficiency (SE) and energy harvesting (EH) in SWIPT-enabled networks with MISO ICs. For this, we derive a multi-objective optimization (MOO) formulation to obtain the optimal beamforming pattern (BP) and power splitting ratio (PR), and we propose a fractional programming (FP) model to find the solution. To tackle the nonconvexity of FP, an evolutionary algorithm (EA)-aided quadratic transform technique is proposed, which recasts the nonconvex problem as a sequence of convex problems to be solved iteratively. To further reduce the communication overhead and computational complexity, a distributed multi-agent learning-based approach is proposed that requires only partial observations of the channel state information (CSI). In this approach, each BS is equipped with a double deep Q network (DDQN) to determine the BP and PR for its UE with lower computational complexity based on the observations through a limited information exchange process. Finally, with the simulation experiments, we verify the trade-off between SE and EH, and we demonstrate that, apart from the FP algorithm introduced to provide superior solutions, the proposed DDQN algorithm also shows its performance gain in terms of utility to be up to 1.23-, 1.87-, and 3.45-times larger than the Advantage Actor Critic (A2C), greedy, and random algorithms, respectively, in comparison in the simulated environment.

Device-to-Device (D2D) communication is an emerging paradigm which enhances the coverage, capacity, and spectral efficiency of the network using cooperative communication in an underlay of cellular networks. In spite of these advantages, it suffers from large bandwidth and energy loss due to usage of half-duplex relaying and limited energy storage devices. To solve these issues, we integrate the full-duplex (FD) relaying and time splitting simultaneous wireless information and power transfer (SWIPT) technique at the D2D transmitters (DDTs). Moreover, to support the ubiquitous connectivity and reduce the latency, non-orthogonal multiple access is used at the base station. The SWIPT-FD-based DDTs and SWIPT-based cell user equipment (CUE) harvest the energy from the base station, after that the DDTs and CUEs decode the desired signal from the multiplexed signal using successive interference cancellation technique, and forward the desired signal to the D2D user equipment (DUE) to improve their QoS. In this paper, ergodic capacity at the DDTs and DUEs & closed-form expressions of the outage probabilities are derived with imperfect CSI. The results demonstrate that the proposed scheme achieves better performance as compared to that of the existing SWIPT-FD-OMA based scheme.

In this letter, we study the impact of nonlinear high power amplifier (HPA) on simultaneous wireless information and power transfer (SWIPT), for a point-to-point multiple-input multiple-output communication system. We derive the rate-energy (RE) region by taking into account the HPA nonlinearities and its associated memory effects. We show that HPA significantly degrades the achievable RE region, and a predistortion technique is investigated for compensation. The performance of the proposed predistortion scheme is evaluated in terms of RE region enhancement. Numerical results demonstrate that approximately 24% improvement is obtained for both power-splitting and time-splitting SWIPT architectures., Comment: 5 pages, 6 figures. To appear in IEEE Wireless Communications Letters

In this paper, we evaluate the performance of a linear minimum mean square error (MMSE) receiver in the context of simultaneous wireless information and power transfer (SWIPT)-enabled cellular networks. In contract to the existing works, where a single-antenna SWIPT architecture is mainly considered, we focus on the SWIPT performance of the multi-antenna receiver architecture, based on the antenna switching (AS) and power splitting (PS) techniques. Aiming to further boost the network performance, we investigate a scenario where the receivers have the capability to employ a successive interference cancellation (SIC) scheme. By leveraging tools from stochastic geometry, we establish an analytical and tractable framework to evaluate the information decoding (ID) and the energy harvesting (EH) success probabilities of the considered network topologies. Our results reveal that the ID performance achieved by the MMSE receiver outperforms that of the conventional maximum ratio combining, leading to an enhanced EH performance, for a given ID reliability constraint. Moreover, by allocating an equal fraction of resources for ID and EH purpose, the PS scheme outperforms the AS in terms of both ID and EH success probabilities., �� 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

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.

Non-orthogonal multiple access (NOMA) in millimeter-wave (mmWave) multiple-input multiple-output (MIMO) (i.e., mmWave MIMO-NOMA) systems, is a promising technology to significantly enhance the spectrum efficiency of the fifth-generation (5G) mobile communication systems. Furthermore, enabling simultaneous wireless information and power transfer (SWIPT), where the energy-constrained user equipment (UE) equipped with power splitting receiver harvest both information and energy from the ambient radio-frequency (RF) signal, is crucial for energy-efficiency-maximization. In this paper, we initially design a user grouping algorithm, which preferentially groups UEs based on their channel correlation. Then, we design the analog RF precoder based on the selected user grouping for all beams, followed by a low-dimensional digital baseband precoder design, to further mitigate inter-beam interference and maximize the achievable sum-rate for the considered system. Subsequently, we equivalently transform the original optimization problem into a joint power allocation and power splitting maximization problem. Then, we propose to decouple the joint power allocation and power splitting nonconvex optimization problem into four separate optimization problems and then solved iteratively via an alternating optimization (AO) algorithm. Simulation results show that high spectrum and energy efficiency can be realized with the proposed algorithms than those of state-of-the-art designs and the conventional SWIPT-enabled mmWave MIMO-OMA system.

In an event of a disaster, the connectivity of on-scene available User Equipment (UE) to the first responders is important because of the unavailability of conventional networks. Therefore, in this paper, considering the deployment of both the Unmanned Aerial Vehicle (UAV) and Mobile Command Center (MCC), we investigate end to end connectivity of UEs to the MCC in terms of the outage. Specifically, various disaster aware clustering schemes are proposed that utilize the UAV and MCC position for the association. These schemes include multiple degrees of freedom to manage intra-cluster distances along with the flexibility to restructure the clusters. In addition, we assume the provision of simultaneous wireless information and power transfer (SWIPT) at Cluster Heads (CHs) through the UAV and MCC. The results show that the association of a UE to MCC or UAV prior to clustering can be optimized to achieve better performance. Without SWIPT at CH, the minimum distance metric to the UAV provides less outage. However, with SWIPT a weighted compromise between intra-cluster distance and CH distance to the UAV achieves less outage. We applied our proposed methods on a real man-made disaster scenario layout and determined their efficacy.

Proceeding of: IEEE 95th Vehicular Technology Conference (VTC2022-Spring), Helsinki, Finland, 19-22 June 2022 In this work, a spike-QAM, a regular QAM constellation where one to four of the elements with the largest amplitudes are placed further from the center, is proposed as the optimum constellation that minimizes the ratio of the symbolerror-rate (SER) to peak-to-average-power-ratio (PAPR) in simultaneous-wireless-information-and-power-transfer (SWIPT) applications. This constellation is capable of maximizing the SER performance for a given design PAPR, or maximize the PAPR given a SER performance. The relationship between these parameters is defined. An approximation to the SER performance is given for the spike-QAM in AWGN channels and it is demonstrated to be valid via numerical simulations. This work has received funding from the European Union Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie ETN TeamUp5G, grant agreement No. 813391, and the Spanish National Project IRENE-EARTH (PID2020-115323RB-C33) (MINECO/AEI/FEDER, UE).

In this paper, we investigate a low complexity technique for simultaneous wireless information and power transfer (SWIPT) in the context of cellular networks, where the multiple-antenna user equipments (UEs) employ maximum ratio combining technique. In particular, our proposed technique allocates a subset of antennas for information decoding (ID), only when their post-combiner signal-to-interference ratio exceeds a certain threshold, while the remaining antennas are allocated for energy harvesting (EH). In contrast to conventional approaches, where an uncorrelated or a fully correlated interference is considered, we develop a realistic mathematical framework that accurately captures the interference correlation effects on the performance of the proposed technique. By using stochastic geometry tools, we derive analytical expressions for both the ID and EH success probability, as well as the joint ID and EH success probability. Our results demonstrate the impact of spatial interference correlation on both the ID and the EH success probability, and we establish the optimal threshold for the proposed antenna switching scheme, that maximizes the joint ID and EH success probability., © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Extremely high reliability and energy efficiency are crucial in sixth generation (6G) mobile networks to accommodate the diverse range of end-user devices in the era of the Internet of Everything. The concept of simultaneous wireless information and power transfer (SWIPT) has been emerged as a promising solution to boost the reliability of wireless communication systems through prolonging the battery lifetime by harvesting energy from the received radio-frequency signals. In this paper, we propose a low complexity threshold-based pair switching (TbPS) technique for SWIPT in the context of large-scale cellular networks, where the multiple-antenna mobile users (MUs) employ maximum ratio combining technique and adopt the random waypoint model. Under the TbPS technique, a subset of MU's antennas is allocated for information decoding (ID), only when their post-combiner signal-to-interference ratio, exceeds a certain threshold, while the remaining antennas are allocated for energy harvesting (EH). Contrary to traditional approaches which assume the existence of either uncorrelated or fully correlated interference, our proposed technique takes into consideration the interference correlation between nearby antennas. In order to further alleviate the inter-cell interference and energy consumption, we propose a traffic load-based sleeping (TLbS) technique in the context of finite-area network deployments, where lightly-loaded cells switch into sleep mode. By leveraging tools from stochastic geometry, we derive analytical expressions for the ID, EH as well as joint ID and EH success probability of MUs based on the proposed techniques. Our results demonstrate the optimal parameters (i.e., antenna selection and traffic load threshold) of our proposed techniques, that maximize the joint ID and EH success probability. Finally, it is shown that, by properly selecting the threshold values, both the proposed TbPS scheme and TLbS mechanism outperform the conventional techniques in terms of the SWIPT capability of the MUs., �� 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

In recent times, the rapid growth in mobile subscriptions and the associated demand for high data rates fuels the need for a robust wireless network design to meet the required capacity and coverage. Deploying massive numbers of cellular base stations (BSs) over a geographic area to fulfill high-capacity demands and broad network coverage is quite challenging due to inter-cell interference and significant rate variations. Cell-free massive MIMO (CF-mMIMO), a key enabler for 5G and 6G wireless networks, has been identified as an innovative technology to address this problem. In CF-mMIMO, many irregularly scattered single access points (APs) are linked to a central processing unit (CPU) via a backhaul network that coherently serves a limited number of mobile stations (MSs) to achieve high energy efficiency (EE) and spectral gains. This paper presents key areas of applications of CF-mMIMO in the ubiquitous 5G, and the envisioned 6G wireless networks. First, a foundational background on massive MIMO solutions-cellular massive MIMO, network MIMO, and CF-mMIMO is presented, focusing on the application areas and associated challenges. Additionally, CF-mMIMO architectures, design considerations, and system modeling are discussed extensively. Furthermore, the key areas of application of CF-mMIMO such as simultaneous wireless information and power transfer (SWIPT), channel hardening, hardware efficiency, power control, non-orthogonal multiple access (NOMA), spectral efficiency (SE), and EE are discussed exhaustively. Finally, the research directions, open issues, and lessons learned to stimulate cutting-edge research in this emerging domain of wireless communications are highlighted.

Radio frequency (RF) energy harvesting systems are enabling new evolution towards charging low energy wireless devices, especially wireless sensor networks (WSN). This evolution is sparked by the development of low-energy micro-controller units (MCU). This article presents a practical multiple input multiple output (MIMO) RF energy-harvesting platform for WSN. The RF energy is sourced from a dedicated access point (AP). The sensor node is equipped with multiple antennas with diverse frequency responses. Moreover, the platform allows for simultaneous information and energy transfer without sacrificing system duplexity, unlike time-switching RF harvesting systems where data is transmitted only for a portion of the total transmission duty cycle, or power-splitting systems where the power difference between the information signal (IS) and energy signal (ES) is neglected. The proposed platform addresses the gap between those two. Furthermore, system simulation and two energy scheduling methods between AP and sensor node (SN) are presented, namely, Continuous power stream (CPS) and intermittent power stream (IPS).

In the Internet of Things, learning is one of most prominent tasks. In this paper, we consider an Internet of Things scenario where federated learning is used with simultaneous transmission of model data and wireless power. We investigate the trade-off between the number of communication rounds and communication round time while harvesting energy to compensate the energy expenditure. We formulate and solve an optimization problem by considering the number of local iterations on devices, the time to transmit-receive the model updates, and to harvest sufficient energy. Numerical results indicate that maximum ratio transmission and zero-forcing beamforming for the optimization of the local iterations on devices substantially boost the test accuracy of the learning task. Moreover, maximum ratio transmission instead of zero-forcing provides the best test accuracy and communication round time trade-off for various energy harvesting percentages. Thus, it is possible to learn a model quickly with few communication rounds without depleting the battery., Accepted to appear in the IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC) in Lucca, Italy, Sep. 2021

We investigate the performance of the simultaneous wireless information and power transfer (SWIPT)-enabled mobile networks, based on a novel coverage area-based coordinated multipoint transmission (CA-CoMP) technique. In particular, the proposed scheme exploits the cooperation technique by appropriately defining the set of cooperative base stations, aiming at reducing the handover rate of the SWIPT-enabled battery-operated mobile users (MUs). Using stochastic geometry tools, we first establish an analytical and tractable framework to investigate the achieved information decoding and energy harvesting performance of the proposed scheme, in terms of the coverage probability, the average spectral efficiency and the average harvested energy. Moreover, analytical expressions for the inter- and intra-cell handover rates are derived. Our results indicate the ability of our proposed scheme to significantly reduce the handover rate of MUs. Finally, simulation results verify that the CA-CoMP scheme achieves a higher average spectral efficiency and a higher average harvested energy compared with the conventional cooperative technique., © 2021 of publication IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Simultaneous wireless information and power transfer is an emerging technique in neurotechnology. This work presents an efficient transmitter for both power transfer and downlink data communication to multiple, miniaturised and inductively-powered chips. We designed, implemented and tested a radio-frequency transmitter operating at 433.92 MHz of the industrial, scientific and medical band. A new structure is proposed to efficiently modulate the carrier, exploiting an amplitude-shift keying modulation reaching a data rate as high as 20 Mbps together with a variable modulation index as low as 8%.

The paper focuses on designing precoding matrices in multi-cell multiple-input multiple-output (MIMO) simultaneous wireless information and power transfer networks (SWIPT) where the sets of users are selected for data transmission in each time slot and the unselected users are dedicated to energy harvesting. The precoding design for the SWIPT problem is formulated as a general multi-objective maximization problem, in which the sum-rate (SR) and sum harvested energy (SHE) are maximized simultaneously under the transmit power constraints. Since the objective function of the maximization problem is not concave in the design matrix variables, it is difficult to directly obtain the optimal solutions. To tackle this challenge, we recast the SR function into one more amenable by applying the connection between the minimum mean square error and achievable data rate. In addition, to deal with the non-concavity of the harvested energy function, we derive its concave minorant. Then, we develop an efficient iterative algorithm based on alternating optimization (AO) to obtain the optimal precoders. We also analyze the convergence and computational complexity of the proposed algorithm. Finally, by numerical simulation results we investigate the trade-offs between the SR and SHE.

Millimeter-wave (mmWave) communication is the rising technology for simultaneous wireless information and power transfer (SWIPT) unmanned aerial vehicle (UAV)-based relay networks for the abundant bandwidth and short wavelength. However, the secrecy performance of mmWave SWIPT UAV-based relay systems has not been investigated so far. In this paper, we consider secure transmissions of mmWave SWIPT UAV-based relay systems in the presence of multiple independent homogeneous Poisson point process (HPPP) eavesdroppers. Different from most existing works considering a free-space path loss model, the air-to-ground channels are modeled as Nakagami-m small-scale fading, and the effects of blockage to mmWave links on the ground and the 3D antenna gain model are considered. The closed-form expressions of the average achievable secrecy rate and energy coverage probability for amplify-and-forward (AF) and decode-and-forward (DF) relay protocols under power splitting (PS) SWIPT policy are derived to reveal the impact of various parameters on system performance. The simulation results show that there is the optimal UAV position to maximize the secrecy rate and the optimal position is closer to the node whose transmit power is relatively small. Furthermore, different carrier frequencies are suitable for different eavesdropping node density.

This paper investigates the secrecy performance of a wireless-powered two-way relay network in the presence of an eavesdropper. Based on adaptive time allocation (TA) and power splitting (PS), a novel secure relaying protocol is proposed. For the purpose of secrecy capacity maximization, the optimal TA ratio and PS ratio, which are adaptively adjusted according to instantaneous channel state information, are derived in high signal-to-noise ratio regime through a split-step iterative method. Numerical results show that in the case of unknown wiretap channels, the proposed protocol can also obtain near-optimal secrecy capacity. Moreover, the proposed protocol has better secrecy capacity performance than the PS relaying protocol in various scenarios.

The application of unmanned aerial vehicles (UAVs) is promising to improve the energy harvesting (EH) efficiency of simultaneous wireless and information and power transfer (SWIPT) system. However, the secure communications are challenging in UAV-assisted SWIPT systems due to the high probability of the existence of line-of-sight links between the UAV and eavesdroppers and the broadcast nature of SWIPT. In order to overcome it, a resource allocation problem is studied in an UAV-assisted SWIPT system, where the multiple eavesdroppers exist. The secrecy rate is maximized by jointly optimizing the trajectory and transmit power of the UAV. An alternative optimization algorithm is proposed to tackle the challenging non-convex problem. The simulation results demonstrate that our proposed resource allocation scheme outperforms other benchmark schemes in terms of the average secrecy rate. It is shown that our proposed algorithm is efficient to converge.

High-efficiency utilization of resources has always been the major concern and design objective in the Internet of Things (IoT). In this paper, an orthogonal frequency division multiplexing-based wireless system model for IoT is proposed, where the simultaneous wireless information and power transfer and the non-orthogonal multiple access (NOMA) are jointly used to improve the energy and spectrum utilization. Specifically, terminals can decode information and harvest energy simultaneously in the downlink and transmit signals to the access point (AP) in the uplink. Then, the AP decodes terminals' information based on NOMA. A joint uplink and downlink resource allocation scheme is proposed with the optimization objective to maximize the sum information decoding rate in the uplink under the condition that the target sum information decoding rate in the downlink is guaranteed. To solve the optimization problem, a two-step algorithm is proposed. For the first step, a joint subcarrier and power allocation algorithm is designed to maximize the harvested energy of terminals in the downlink. For the second step, a subslot optimization algorithm is designed to increase the sum information decoding rate in the uplink. Simulation results demonstrate that, compared with the conventional algorithms, the proposed algorithm can not only achieve the maximization of harvested energy but also support higher sum information decoding rate in the uplink.

The integration of simultaneous wireless information and power transfer (SWIPT) and cooperative relay (CoR) techniques has evolved as a new phenomenon for the next-generation wireless communication system. CoR is used to get energy and spectral efficient network and to solve the issues of fading, path loss, shadowing, and smaller coverage area. Relay nodes are battery-constrained or battery-less devices. They need some charging systems externally as replacing or recharging of their batteries sometimes which are not feasible and convenient. Energy harvesting (EH) is the most cost-effective, suitable, and safer solutions to power up these relays. Among various types of the EH, SWIPT is the most prominent technique as it provides spectral efficiency by delivering energy and information to the relays at the same time. This paper reviews the combination of CoR and SWIPT. From basic to advanced architectures, applications and taxonomies of CoR and SWIPT are presented, various forms of resource allocation and relay selection algorithms are covered. The usage of CoR and SWIPT in the fifth-generation wireless networks is discussed. This paper focuses on the integral aspects of the CoR and SWIPT to other next-generation wireless communication systems and techniques such as multiple-input-multiple-output, wireless sensor network, cognitive radio, vehicular ad hoc network, non-orthogonal multiple access, beamforming technique, and the Internet of Things. Some open issues and future directions and challenges are given in this paper.

In this paper, we provide a comprehensive performance analysis of simultaneous wireless information and power transfer (SWIPT) for cognitive relay networks with different relay schemes. In the considered system, the energy-constrained secondary transmitter harvests the energy from the primary signal and then employs the harvested energy to forward the primary signal along with the secondary signal simultaneously. To improve the spectral efficiency, we propose a novel cooperative spectrum sharing protocol with dynamic time-slot allocation based on energy harvesting, namely, dynamic time-power-based cooperative spectrum sharing protocol. Considering the delay-limited transmission mode, we analytically derive the exact closed-form expressions of outage probabilities and achievable throughput for both the primary and secondary networks with amplify-and-forward and decode-and-forward relaying schemes, respectively. More importantly, different from the existing works, we take into account the power outage probability at the energy-constrained secondary transmitter to better match the reality. Finally, the numerical results are provided to evaluate the effect of different key parameters on the system performance, which demonstrate that the dynamic cooperative spectrum sharing protocol improves the outage performance compared with the uniform time-slot allocation scheme.

This paper considers the transmit linear precoding problem for a multiple-input-multiple-output system with simultaneous wireless information and power transfer (SWIPT), where we assume that the transmitter only has statistical channel state information. The optimal precoder is designed based on maximizing the lower bound of average mutual information under the constraints of transmitting power and harvested energy level. Different from previous works on SWIPT, this paper formulates the design from the standpoint of realistic communication systems with finite-alphabet input signals instead of Gaussian input signals. The formulated problem is NP-hard, so a globally optimal solution cannot be found with polynomial-time complexity. However, by exploiting the structure of the problem, we develop two algorithms to obtain a near optimal solution, among which one is based on a semidefinite relaxation (SDR) technique and the other is based on power allocation. The SDR-based algorithm has more extensive applicability, while the power-allocation-based algorithm offers higher efficiency. The simulation results show the efficacy of the proposed algorithms.

In this paper, we investigate a secure transmission algorithm exploiting the vertical domain for simultaneous wireless information and power transfer (SWIPT) in a massive multiple-input multiple-output system over Rician fading channels. Each user adopts the power splitting (PS) technique to separate information and energy, which is regarded as a potential eavesdropper (ED) for the intended user. We consider the scenario, where at least one ED has the same angle of departure with the intended user. The base station (BS) applies artificial noise (AN) and deploys 3-D directional antennas to enhance the secure rate and energy transfer by adjusting the antenna tilt adaptively. We first derive the approximate ergodic achievable secrecy rate and harvested power. Based on these approximations, the optimization problem is formulated to minimize the total transmit power with individual secrecy rate and harvested power targets. We propose an iterative algorithm to jointly optimizing the BS antenna tilt, AN covariance, power allocation, and PS ratios. The numerical results verify that the approximate secrecy rate is very close to the actual values and show that the performance of the proposal approaches that of the optimal solutions from the brute-force search and outperforms the 2-D and conventional 3-D schemes, which proves the significant role of tilt adaptation in the secure SWIPT.

A generalized carrier index differential chaos shift keying with simultaneous wireless information and power transfer (GCI-DCSK SWIPT) scheme, is proposed, which is an improved scheme for CI-DCSK SWIPT. Compared to CI-DCSK SWIPT, GCI-DCSK SWIPT is not only more flexible in selecting both index bit number and index carrier number, but also is more practical for considering both path loss and the conversion noise generated by radio frequency (RF) band to baseband. The proposed scheme applied a time-switching manner to harvest the energy carried by the inactive carriers. Theoretical bit error rate (BER) expressions of the scheme over AWGN and multipath Rayleigh fading channels are derived, and the ratio of harvested energy to transmitted energy is derived to desecribe the probability of self-sufficiency on power supply. In addition, the frame-derived factor and the energy carried by inactive carriers are optimized to obtain better BER performance. Simulation results show that taking both path loss and conversion noise into consideration, the scheme is still self-sufficient with good BER performance. Furthermore, by adjusting the number of active carriers of GCI-DCSK SWIPT, some cases of GCI-DCSK SWIPT outperform conversion noise-aware CI-DCSK SWIPT in BER.

As one of the basic supporting technologies of 5G system, wireless sensor networks technology is facing a new challenge to improve its transmission energy efficiency. This paper considers combining simultaneous wireless information and power transfer (SWIPT) technique and routing technique, and applying them to multi-hop clustered wireless sensor networks (MCWSN), where each node can decode information and harvest energy from a received radio-frequency signal. And the relay nodes in MCWSN can utilize the harvest energy to forward data to their next hop nodes according to the routing scheme. First, we formulate an energy-efficient routing problem of MCWSN with SWIPT. Then, a heuristic energy efficient cooperative SWIPT routing algorithm (EECSR) is presented to find a transmission path with the maximum energy efficiency. Specifically, in EECSR, the resource allocation problem in each hop of the path is transformed to some equivalent convex optimization problems, which are resolved via dual decomposition. Moreover, a distributed routing protocol based on EECSR is proposed. As far as we know, this is the first solution that considers energy efficiency optimization based on routing and SWIPT in MCWSN. Simulation results show that our EECSR algorithm has high energy efficiency and good robustness. And our distributed routing protocol has better real-time performance than traditional protocols.

Wireless power transfer (WPT) is an emerging paradigm that will enable using wireless to its full potential in future networks, not only to convey information but also to deliver energy. Such networks will enable trillions of future low-power devices to sense, compute, connect, and energize anywhere, anytime, and on the move. The design of such future networks brings new challenges and opportunities for signal processing, machine learning, sensing, and computing so as to make the best use of the RF radiations, spectrum, and network infrastructure in providing cost-effective and real-time power supplies to wireless devices and enable wireless-powered applications. In this paper, we first review recent signal processing techniques to make WPT and wireless information and power transfer as efficient as possible. Topics include power amplifier and energy harvester nonlinearities, active and passive beamforming, intelligent reflecting surfaces, receive combining with multi-antenna harvester, modulation, coding, waveform, massive MIMO, channel acquisition, transmit diversity, multi-user power region characterization, coordinated multipoint, and distributed antenna systems. Then, we overview two different design methodologies: the model and optimize approach relying on analytical system models, modern convex optimization, and communication theory, and the learning approach based on data-driven end-to-end learning and physics-based learning. We discuss the pros and cons of each approach, especially when accounting for various nonlinearities in wireless-powered networks, and identify interesting emerging opportunities for the approaches to complement each other. Finally, we identify new emerging wireless technologies where WPT may play a key role -- wireless-powered mobile edge computing and wireless-powered sensing -- arguing WPT, communication, computation, and sensing must be jointly designed., Comment: Overview paper submitted for publication

This paper proposes a simultaneous wireless information and power transfer (SWIPT) energy-harvesting relay jamming based mixed RF/FSO system, and studies its security performance optimization in the presence of an eavesdropper. In this work, the RF and FSO channels experience Nakagami-m fading distribution and Málaga(M) turbulence, respectively. A two-hop decode-and-forward (DF) relay is presented in the system, and the effect of pointing errors is considered. The presence of a nearby single antenna eavesdropper that attempts to eavesdrop on the transmission is also modeled. In order to prevent eavesdropping, the relay introduces the SWIPT structure to control information delivery and wireless energy recharging. The closed expressions of secrecy outage probability (SOP) and average secrecy capacity (ASC) of the mixed RF/FSO system are derived for the above system model. In addition, the closed-form expression of the asymptotic results for SOP and ASC are derived when signal-to-noise ratios at relay and legitimate destinations tend to infinity. The correctness of these expressions is verified using the Monte Carlo method. The influence of various key factors on the safety performance of the system is analyzed by simulations. The results show that the safety performance of the system is considerably improved under good weather conditions as well as by increasing the signal-interference noise ratio, number of interferer antennas, power distribution factor and energy conversion efficiency. This study provides a new system structure and a good theoretical basis for evaluating the physical layer security performance of the mixed RF/FSO system.

This article investigates fast deep learning based transmit beamforming design for simultaneous wireless information and power transfer in the multiuser multiple-input-single-output downlink, with specific absorption rate (SAR) constraints. The problem of interest is to maximize the received signal-to-interference-plus-noise ratio and the energy harvested for all receivers, while satisfying the transmit power and the SAR constraints. The optimal solution can be obtained via convex optimization but incurs a high complexity. To reduce the computational complexity, this article proposes a model-driven deep learning technique that only needs to predict key features of the problem with much reduced dimension but enhanced performance compared to widely used data-driven machine learning. Simulation results demonstrate that our proposed algorithms can significantly reduce the algorithm execution time, while maintaining satisfactory performance.

In this paper, we investigate the resource allocation scheme for an unmanned-aerial-vehicle-enable (UAV-enabled) two-way relaying system with simultaneous wireless information and power transfer (SWIPT), where two user equipments (UEs) exchange information with the help of UAV relay and harvest energy through power splitting (PS) scheme. Under the transmission power constraints at UEs and UAV relay, a non-convex intractable optimization problem is formulated which maximizes the sum retained energy of two UEs while satisfying the minimum signal-to-noise ratio requirement. We decouple the complicated beamforming and PS factors optimization problem into three solvable subproblems and propose an efficient alternating optimization scheme. Subsequently, in order to reduce the complexity, a robust scheme based on generalized singular value decomposition (GSVD) is designed. Finally, numerical results verify the robustness and effectiveness of two proposed schemes.

We study the information-energy capacity region (IE-CR) of an additive white Gaussian noise (AWGN) channel in the presence of high-power amplifier (HPA) nonlinearity. Specifically, we consider a three-node network consisting of one transmitter, one information receiver and one energy receiver and we study the capacity-achieving input distribution under i) average-power, peak-power constraints at the transmitter, b) HPA nonlinearity at the transmitter, and c) nonlinearity of the energy harvesting circuit at the energy receiver. We prove that the input distribution is discrete and finite and we derive closed form expressions for the special cases of maximizing the harvested energy and maximizing the information capacity. We show that HPA significantly reduces the achievable IE-CR; to compensate HPA nonlinearity, a predistortion technique is also discussed and evaluated in terms of IE-CR performance., IEEE International Symposium on Information Theory (IEEE ISIT 2020)

Cooperative communication networks have received more attention due to its ability to improve the signal quality of terminal devices by spatial diversity. Under recent advance in internet of things, In order to extend the service life of terminal devices powered by battery, simultaneous wireless information and power transfer (SWIPT) technique has been emphasize. The terminal devices can harvest energy and decode information from the same radio frequency (RF) signal using by SWIPT technique. In this paper, we combine both techniques to study the performance of both conventional cooperative relaying networks without SWIPT and cooperative relaying networks with SWIPT under an amplify-and-forward (AF) relaying network. To the best of our knowledge, no one simultaneously studies and compares the performance of both systems. Therefore, the outage probabilities of both systems are carried out, and numerical results are compared in this paper. The main results include: (1) Compared with conventional cooperative communication, the cooperative communication with SWIPT has better outage probability only when the distance between relay node and source node is less than one. It implies that, to outperform the conventional cooperative communication, the relay node should harvest enough energy for signal transmission. (2) With the diversity of direct path and relay path, the outage probability of cooperative communication with EH under an AF relaying network has been significantly reduced.

This paper considers the physical layer security (PLS) of a simultaneous wireless information and power transfer (SWIPT) relay communication system composed of a legitimate source–destination pair and some eavesdroppers. Supposing a disturbance of channel status information (CSI) between relay and eavesdroppers in a bounded ellipse, we intend to design a robust beamformer to maximum security rate in the worst case on the constraints of relay energy consumption. To handle this non-convex optimization problem, we introduce a slack variable to transform the original problem into two sub-problems firstly, then an algorithm employing a semidefinite relaxation (SDR) technique and S-procedure is proposed to tackle above two sub-problems. Although our study was conducted in the scene of a direct link among source, destination, and eavesdroppers that is non-existing, we demonstrate that our conclusions can be easily extended to the scene for which a direct link among source, destination and eavesdroppers exist. Numerical simulation results compared with the benchmark scheme are provided to prove the effectiveness and superior performance of our algorithm.

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. Science Foundation Ireland

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.

In this paper, we study a simultaneous wireless information and power transfer (SWIPT) system aided by the intelligent reflecting surface (IRS) technology, where an AP transmits confidential information to the legitimate information receiver (IR) in the presence of an energy harvesting (EH) receiver that could be a potential eavesdropper. We aim to maximize the secrecy rate at the legitimate IR by jointly optimizing the information beamforming vector and the energy transfer beamforming vector at the access point (AP), and the phase shift matrix at the IRS, subject to the minimum harvested power required by the EH receiver. The semi-definite relaxation (SDR) approach and the alternating optimization (AO) method are proposed to convert the original non-convex optimization problem to a series of semi-definite programs (SDPs), which are solved iteratively. Numerical results show that the achievable secrecy rate of the proposed IRS-assisted SWIPT system is higher than that of the SWIPT system without the assistance of the IRS.

Simultaneous wireless information and power transfer (SWIPT) has drawn significant research interest in recent years. In this paper, we investigate the information theoretic secrecy of a SWIPT system under Weibull fading channel. To be specific, we analyze the information security in the presence of an energy harvesting and information decoding eavesdropper. All links are subjected to Weibull fading which is more complex than traditional Rayleigh fading. Moreover, we derive closed-form expressions for the probability of strictly positive secrecy capacity and the ergodic secrecy capacity. We evaluate the effect of Weibull shape parameter and power splitting factor on the secrecy performance of SWIPT system. Numerical and simulation results are provided to demonstrate that our findings are instantly applicable on the design of wireless power networks.

© 2013 IEEE. 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.

In this paper, we investigate simultaneous wireless information and power transfer in a cooperative communication network consisting of one source, one battery-enabled relay, and one destination node. An amplify-and-forward relaying method is considered, where the relay node harvests energy from the received signal power to charge its battery, which is used to forward the received signal to the destination. We also consider a direct link between the source and the destination. The direct link signal can be combined with the relaying signal at the destination node using maximum ratio combining. Under the delay-limited transmission mode, closed form expressions for outage probability are derived for a battery-enabled relay. Our analytical results reveal the advantage of cooperative relay networks with a direct link. Also, we extend our design to a multiple-relay scenario, where the best relay is selected from the available number of relays, based on the information of relay locations. Finally, we demonstrate from simulation results based on outage probability that our proposed methods are efficient in comparison with Monte Carlo simulations.

This paper studies a simultaneous wireless information and power transfer multi-input single-output cognitive radio network in which a multi-antenna secondary transmitter sends data streams to multiple single-antenna secondary receivers (SRs) equipped with a power-splitting (PS) structure for information decoding and energy harvesting in the presence of multiple single-antenna primary users (PUs). First, the max-min fair SRs' harvested energy problem is formulated and solved by combining the tight semidefinite relaxation (SDR)-based solution of the transmit power minimization problem with the bisection search method. Second, the balancing problem examines the tradeoff between the worst-user harvested energy at the SR and the interference power at the PU. The proposed solution for this challenging non-convex problem includes two steps. First, the problem with fixed PS ratios is solved using the SDR technique and the tight solution is proved; then, the approximately optimal PS ratios are found using the particle swarm optimization method. Additionally, the closed-form solutions of transmit power minimization and harvested energy maximization problems are derived for the special case where only one SR and one PU are present. Finally, the numerical results demonstrate the effectiveness of the proposed approaches in comparison with two baseline schemes.

In this paper, the secrecy outage performance of a three-node amplify-and-forward relay network with an untrustworthy relay is investigated. To enable a secure transmission, we consider a destination-based jamming technique to prevent the relay from successfully decoding the secret messages between the source and the destination. In addition, the relay is assumed to be an energy-constrained device, thus being first energized by the source in order to be able to retransmit the information to the destination. In doing so, a time switching-based simultaneous wireless information and power transfer scheme is used. A closed-form asymptotic expression for the secrecy outage probability is derived in order to obtain a tight approximation at medium-to-high signal-to-noise ratio. The accuracy of the performed analysis is corroborated by Monte Carlo simulations through different illustrative cases. Numerical results show the impact of key system parameters on the secrecy performance, such as the time allocation factor between the energy harvesting and information transmission phases, the power allocation factor between source and destination for cooperative jamming, and the relay position, so as to provide insights on the design criteria for energy efficient and secure networks.

International audience; We introduce a tractable approach for studying the feasibility of multiple-antenna cellular networks, where low-energy devices decode information data and harvest power simultaneously. Tools from stochastic geometry are used to quantify the information rate vs. harvested power tradeoff. Our study unveils that large-scale antenna arrays and ultra-dense deployments of base stations are both necessary to harvest, with high reliability, an amount of power of the order of a milliwatt.

This paper investigates relaying schemes in an amplify-and-forward multiple-input multiple-output relay network, where an energy-constrained relay harvests wireless power from the source information flow and can be further aided by an energy flow (EF) in the form of a wireless power transfer at the destination. However, the joint optimization of the relay matrix and the source precoder for the energy-flow-assisted (EFA) and the non-EFA (NEFA) schemes is intractable. The original rate maximization problem is transformed into an equivalent weighted mean square error minimization problem and optimized iteratively, where the global optimum of the nonconvex source precoder subproblem is achieved by semidefinite relaxation and rank reduction. The iterative algorithm finally converges. Then, the simplified EFA and NEFA schemes are proposed based on channel diagonalization, such that the matrices optimizations can be simplified to power optimizations. Closed-form solutions can be achieved. Simulation results reveal that the EFA schemes can outperform the NEFA schemes. Additionally, deploying more antennas at the relay increases the dimension of the signal space at the relay. Exploiting the additional dimension, the EF leakage in the information detecting block can be nearly separated from the information signal, such that the EF leakage can be amplified with a small coefficient., Comment: Submitted for possible journal publication