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Aiming at high energy consumption and information security problem in the simultaneous wireless information and power transfer (SWIPT) multi-user wiretap network, we propose a user-aided cooperative non-orthogonal multiple access (NOMA) physical layer security transmission scheme to minimize base station (BS) transmitted power in this paper. In this scheme, the user near from BS is adopted as a friendly relay to improve performance of user far from BS. An energy harvesting (EH) technology-based SWIPT is employed at the near user to collect energy which can be used at cooperative stage. Since eavesdropper in the downlink of NOMA system may use successive interference cancellation (SIC) technology to obtain the secrecy information of receiver, to tackle this problem, artificial noise (AN) is used at the BS to enhance security performance of secrecy information. Moreover, semidefinite relaxation (SDR) method and successive convex approximation (SCA) technique are combined to solve the above non-convex problem. Simulation results show that in comparison with other methods, our method can effectively reduce the transmitted power of the BS on the constraints of a certain level of the secrecy rates of two users.

A promising technology for addressing network lifetime and energy bottlenecks in wireless networks is the Simultaneous Wireless Information and Power Transfer (SWIPT). In this paper, a Hybrid Time switching and Power splitting-based Relaying (HTPR) protocol for SWIPT in an Amplify-and-Forward (AF) network is proposed. The network consists of a source, relay, and destination in which the relay performs Energy Harvesting (EH) from the source signal and uses the harvested energy to transmit the signal to the destination. A direct link exists between the source and destination, and the signals from the source and relay are combined by the Maximum Ratio Combining (MRC) method at the destination. Closed-form expressions for outage probability are derived under delay-limited transmission to determine the achievable throughput at the destination in different transmission schemes. For a constant data rate, HTPR protocol with uniform and optimal EH ratios are considered for throughput maximization. To solve the optimization problem, the convex optimization technique Lagrange multiplier method and Karush-Kuhn-Tucker (KKT) conditions are used. Results show that the HTPR protocol has higher throughput than other SWIPT protocols at relatively high Signal-to-Noise Ratio (SNR).

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.

Simultaneously wireless information and power transfer technology enables information and energy to be transmitted over the same radio frequency (RF) signal. We investigate a multiple input simple output (MISO) system where the multiple-antenna base station not only transmits information to single-antenna users, but also supplies all power they need. The same beamforming at base station under two modes of energy transfer and information transmission causes the problem of low system energy efficiency. To solve this, we put forward a novel transmission scheme where beamforming is divided by time switching (TS) into two parts, energy beamforming and information beamforming, and users receive by hybrid time switching and power splitting (hybrid TS-PS) correspondingly. Under constraints of information and energy, we aim to achieve the maximal energy efficiency by jointly optimize power splitting, time allocation, beamforming for energy transfer and information transmission phase respectively. In the solving process, we transfer the maximal energy efficiency problem into the minimal energy consumption problem, analyze the feasibility, then prove the existing of optimal solution. Furthermore, we put forward a semidefinite relaxation (SDR) based algorithm to solve the problem optimally and two sub-optimal designs to simplify computing complexity. Simulation results illustrate that our proposed design can achieve the optimal energy efficiency and prove the asymptotic optimality of two sub-optimal solutions.

In this paper, the secrecy performance in internet of things (IoTs) networks with cooperative eavesdroppers has been investigated, where simultaneous wireless information and power transfer (SWIPT) nodes perform as relay nodes. The secrecy energy efficiency (SEE) maximization problem for single relay node has been introduced to extend the life-time for IoT nodes without power supply. The optimization problem is firstly transformed into two sub-problems, and then each sub-problem is solved by bisection method. Furthermore, the model has been extended into multiple relay nodes and a novel relay selection algorithm for SEE maximization has been proposed. Finally, the advantage of the proposed algorithm has been verified from simulations.

With the explosive increase of the types and quantity of devices in wireless networks, it is necessary to design a fast and energy-efficient decision-making strategy for the resource allocation to maintain the efficient operation of the wireless system. However, traditional resource allocation strategies designed based on optimization methods are of high complexity and poor real-time performance, which are not conducive to online decision-making. In this paper, deep learning approaches are introduced to design the optimal beamforming for Sink nodes in the SWIPT-enabled Sensor-Cloud system. First, the energy-efficiency maximization problem is first formulated with a “return/pay” form. In order to realize the application of deep learning for problem solving, a high-dimensional solvable mathematical expression is transformed from the maximization problem, and then a SWIFT-WMMSE algorithm iteratively is designed to obtain the optimal beamforming vector. At the same time, the convergence of the SWIPT-WMMSE algorithm is proved. Second, the approachability of the neural network to approximate the SWIPT-WMMSE algorithm is discussed. Furtherly, based on the error propagation in DNN approaching process, the criteria for the DNN scale design is deduced, and the approximation to the SWIPT-WMMSE algorithm is realized through the training of DNN, which is operated as an alternative algorithm to solve the optimal beamforming vectors for Sink nodes. Finally, the simulation results verify the effectiveness of SWIPT-WMMSE algorithm and DNN model, as well as the approximation effect of DNN model and its advantages in improving the system performance, especially in the aspect of complexity reducing and time saving.

In this paper, we propose one‐bit feedback‐based distributed beamforming (DBF) techniques for simultaneous wireless information and power transfer in interference channels where the information transfer and power transfer networks coexist in the same frequency spectrum band. In a power transfer network, multiple distributed energy transmission nodes transmit their energy signals to a single energy receiving node capable of harvesting wireless radio frequency energy. Here, by considering the Internet‐of‐Things sensor network, the energy harvesting/information decoding receivers (ERx/IRx) can report their status (which may include the received signal strength, interference, and channel state information) through one‐bit feedback channels. To maximize the amount of energy transferred to the ERx and simultaneously minimize the interference to the IRx, we developed a DBF technique based on one‐bit feedback from the ERx/IRx without sharing the information among distributed transmit nodes. Finally, the proposed DBF algorithm in the interference channel is verified through the simulations and also implemented in real time by using GNU radio and universal software radio peripheral.

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

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.

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

We explore physical layer security of simultaneous wireless information and power transfer (SWIPT) relay network in this paper. Modeling channel error between relay and eavesdroppers (Eves) as random channel state information (CSI) error, we present an algorithm to optimize secret rate of SWIPT in the constraints of relay forward power, receiver signal-to-interference-plus-noise ratio (SINR) and Eves SINR. A slack variable is introduced to decompose original non-convex problem into upper and lower sub-problems, meanwhile, Bernstein-type inequality is used to convert probability constraint of lower sub-problems to linear matrix inequality constraints. Simulation experiments show that the proposed algorithm obtains higher secret rate than that of zero-forcing algorithm and worst-case algorithm.

This paper considers the problem of mutual information maximization in a two-hop relay network with simultaneous wireless information and power transfer (SWIPT), where the relay nodes use the power splitting (PS) scheme to harvest the energy for information forwarding. Unlike previous research, this paper focuses on a more practical scenario, where the inputs to the network are assumed to be finite-alphabet signals. Although each node in the network is assumed to have single antenna, we show that the relay network can be regarded as an effective multiple-input multiple-output (MIMO) system. Our goal is to perform the joint optimization on the precoder at source and PS ratio at relays to maximize the mutual information. Although the formulated problem is nondeterministic polynomial-time (NP)-hard, we theoretically analyze the optimal PS ratio; then, by using the structure of optimization problem, a near optimal precoder design based on semidefinite relaxation (SDR) is proposed; further, to reduce the complexity of algorithm, another precoder design based on search technique, which exploiting the structure of precoder, is developed only with a slight performance degradation. Simulation results verify the efficacy of proposed precoder designs.

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.

Reliable communication between the primary and the secondary side is a challenge for simultaneous wireless information and power transfer (SWIPT) system. Considering many factors, such as cost, device size, and transmission efficiency, the SWIPT system transferring multiple frequencies with a single inductive link is an effective scheme to integrate reverse data communication. However, those SWIPT systems change power transfer frequency or power carrier amplitude while transferring information, then information cannot be transmitted when the inverter does not work, which reduces the reliability of communication. To solve this problem, this paper proposes an idea of establishing an independent information transfer channel, the power and information transmits at different frequencies. The information transmitted in the reverse direction no longer flows through the primary side inverter. It is guided to an independent channel after being transmitted to the primary side through the common inductive link. Its equivalent circuit model is provided to analyze the transfer gain, power transfer performance, and the relationship between the information coupling circuit and information transfer characteristics. Finally, a SWIPT prototype is built to validate the proposed SWIPT 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.

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.

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

In this work, circular quadrature amplitude modulation (CQAM) is investigated for simultaneous wireless information and power transfer (SWIPT). Both coded and uncoded cases are considered, under which the flexibility of CQAM for SWIPT is presented. Specifically, for uncoded transmission, CQAM is designed to achieve a controllable tradeoff between energy harvesting and information transfer performance. In the coded case, bit-interleaved coded-CQAM are designed based on the maximization of the discrete-input capacity. Our results show, in both cases, the superiority of CQAM compared to known modulation schemes (i.e. QAM, PSK, and PAM) in terms of error rate and energy harvesting., © 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.

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

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

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%.

Simultaneous wireless information and power transfer (SWIPT) is a promising technology to achieve wide-area energy transfer by sharing the same radio frequency (RF) signal and infrastructure of legacy wireless communication systems. To enlarge the effective range of energy transfer in practice, it is desirable to have a hybrid signaling SWIPT scheme, which combines a high-power multitone energy signal with a low-power broadband information signal. This paper presents a systematic study on the performance of hybrid signaling SWIPT systems with memoryless nonlinear transmitter power amplifiers (PAs). Using PA efficiency and signal-to-noise-and-distortion ratio (SNDR) as the metrics to measure the efficiency of energy transfer and information transmission, respectively, we derive the tradeoff between these two metrics for two PA classes, two nonlinear PA models, and two SNDR definitions. Our results reveal insights into the fundamental performance tradeoff inherent in SWIPT systems using hybrid signaling schemes.

Full-duplex (FD) with simultaneous wireless information and power transfer (SWIPT) in wireless ad hoc networks has received increased attention as a technology for improving spectrum and energy efficiency. This paper studies the outage performance for a SWIPT-based decode-and-forward (DF) FD relaying network consisting of a single-antenna source S, a two-antenna relay R, and a multi-antenna destination D. Specifically, we propose four protocols, namely static time-switching factor with selection combining (STSF-SC), static time-switching factor with maximal ratio combining (STSF-MRC), optimal dynamic time-switching factor with selection combining (ODTSF-SC), and optimal dynamic time-switching factor with maximal ratio combining (ODTSF-MRC) to fully investigate the outage performance of the proposed system. In particular, the optimal time-switching factor from the ODTSF-SC and ODTSF-MRC methods is designed to maximize the total received data at the destination. In this context, we derive exact closed-formed expressions for all schemes in terms of the outage probability (OP). Finally, the Monte Carlo simulations are conducted to corroborate the theoretical analysis's correctness and the proposed schemes' effectiveness. Web of Science 21 11 art. no. 3847

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 proposes a novel cooperative secure unmanned aerial vehicle (UAV) aided transmission protocol, where a source (Alice) sends confidential information to a destination (Bob) via an energy-constrained UAV-mounted amplify-and-forward (AF) relay in the presence of a ground eavesdropper (Eve). We adopt destination-assisted cooperative jamming (CJ) as well as simultaneous wireless information and power transfer (SWIPT) at the UAV-mounted relay to enhance physical-layer security (PLS) and transmission reliability. Assuming a low altitude UAV, we derive connection probability (CP), secrecy outage probability (SOP), instantaneous secrecy rate, and average secrecy rate (ASR) of the proposed protocol over Air-Ground (AG) channels, which are modeled as Rician fading with elevation-angel dependent parameters. By simulations, we verify our theoretical results and demonstrate significant performance improvement of our protocol, when compared to conventional transmission protocol with ground relaying and UAV-based transmission protocol without destination-assisted jamming. Finally, we evaluate the impacts of different system parameters and different UAV's locations on the proposed protocol in terms of ASR., 10 pages, 9 figures, Submitted for possible journal publication

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.

In this paper, we investigate the effects of residual hardware impairments (RHIs), channels estimation errors (CEEs) and imperfect successive interference cancellation (ipSIC) on the cooperative non-orthogonal multiple access (NOMA) system over Nakagami-m channels, where the amplify-and-forward (AF) relay can harvest energy from the source. The exact expressions for outage probability and ergodic sum rate are derived in closed-form. In addition, the asymptotic outage analyses in the high signal-to-noise (SNR) regime are carried out. The results show that the outage probability exists an error floor due to the existence of CEEs and compared with RHIs, CEEs have a more serious impact on the system outage performance. The close simulation results of Monte Carlo verify the accuracy of our theoretical derivation. Finally, the performance of energy efficiency is examined with RHIs, CEEs and ipSIC.

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 a conventional cognitive radio (CR) network, only when the primary user's (PU) frequency bands are sensed to be free, secondary users (SUs) can utilize these frequency band resources. Therefore, spectrum sensing (SS) can improve spectrum utilization. Spectrum sharing means that the SUs are allowed to utilize the licensed spectrum bands belonging to the PU to transmit information with PU simultaneously. Spectrum sharing performs well under the conditions that the interference to the PU is assured to be less than a certain threshold. Non-orthogonal multiple access (NOMA) has attracted considerable interests in recent years, which is seen as an important wireless access scheme for the coming 5G wireless communication system. Simultaneous wireless information and power transfer (SWIPT) is proposed as a popular technique to extend the operation duration of power-supply-limited wireless networks. The CR-NOMA is seen as a special form of the power-domain NOMA, wherein the requirements of the SU and PU are strictly met so that excellent system performance can be achieved. In this paper, a joint frame structure is described, wherein SUs first perform SWIPT for spectrum sensing and then transmit information via an overlay and underlay mode. Moreover, the optimization problem to maximize the achievable throughput for the CR network is presented to obtain the optimal sensing slot, while the total transmission power and the minimum rate requirements of the SUs are both constrained. A joint power allocation and sensing time optimizing algorithm based on dichotomy method are proposed to achieve the optimal solution. The simulation results show that there is a maximal throughput via setting an optimal sensing time for the secondary network.

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.

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.

Communication between the primary and secondary sides is pivotal to the wireless power transfer (WPT) system. The system control commands and feedback information need simultaneous wireless information and power transfer (SWIPT). In this paper, a FSK-based SWIPT system with full-duplex communication via a shared channel is provided. Considering the complexity of the coupling relationship in this kind of full-duplex SWIPT system, this paper proposes an analysis method based on the transmission channel, studies the crosstalk between the power channel and the information channel, and between the forward and reverse transfer of information. A design method of full-duplex communication SWIPT system based on shared coupling channels is provided. A 60 W SWIPT prototype with a full-duplex communication rate of 20 kbps is built to verify the proposed method. Web of Science 14 16 art. no. 4918

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

We present the design for an ultra-low latency and low energy Internet of Things (IoT) network inspired by the emerging cooperative Non-Orthogonal Multiple Access (NOMA) wireless communication technique. The IoT network model consists of a source at the center of the network, a near device inside the network, and a far device outside the network. The far device is in the near proximity of the near device, however. We deploy the near device as a relay to assist the far device. The near device is assumed to be a low energy node. As a result, the near device cannot forward signals to the far device through its own power. We therefore design the IoT network to apply the Simultaneous Wireless Information and Power Transfer (SWIPT) technique so that the near device would be able to harvest energy and use it to forward signals. Two cooperative IoT network scenarios are examined: Half-Duplex (HD) and Full-Duplex (FD) relaying, each with and without eavesdroppers. The design also exploits Power Splitting (PS) factors for fairness in Quality of Service (QoS) for the devices. Novel analysis expressions are obtained accuracy and approximation of closed-forms for Outage Probability (OP), secrecy OP, system throughput and Jain's fairness index. The analysis results are proved and verified by Monte Carlo simulation results. Web of Science 9 61512 61489

The deployment of relays between Internet of Things (IoT) end devices and gateways can improve link quality. In cellular-based IoT, relays have the potential to reduce base station overload. The energy expended in single-hop long-range communication can be reduced if relays listen to transmissions of end devices and forward these observations to gateways. However, incorporating relays into IoT networks faces some challenges. IoT end devices are designed primarily for uplink communication of small-sized observations toward the network; hence, opportunistically using end devices as relays needs a redesign of both the medium access control (MAC) layer protocol of such end devices and possible addition of new communication interfaces. Additionally, the wake-up time of IoT end devices needs to be synchronized with that of the relays. For cellular-based IoT, the possibility of using infrastructure relays exists, and noncellular IoT networks can leverage the presence of mobile devices for relaying, for example, in remote healthcare. However, the latter presents problems of incentivizing relay participation and managing the mobility of relays. Furthermore, although relays can increase the lifetime of IoT networks, deploying relays implies the need for additional batteries to power them. This can erode the energy efficiency gain that relays offer. Therefore, designing relay-assisted IoT networks that provide acceptable trade-offs is key, and this goes beyond adding an extra transmit %Quality Control Editor: Abbreviations and acronyms are often defined the first time they are used within the abstract and again in the main text and then used throughout the remainder of the manuscript. Please consider adhering to this convention. The target journal may have a list of abbreviations that are considered common enough that they do not need to be defined. RF chain to a relay-enabled IoT end device. There has been increasing research interest in IoT relaying, as demonstrated in the available literature. Works that consider these issues are surveyed in this paper to provide insight into the state of the art, provide design insights for network designers and motivate future research directions.

In the present paper, we investigate the performance of the simultaneous wireless information and power transfer (SWIPT) based cooperative cognitive radio networks (CCRNs). In particular, the outage probability is derived in the closed-form expressions under the opportunistic partial relay selection. Different from the conventional CRNs in which the transmit power of the secondary transmitters count merely on the aggregate interference measured on the primary networks, the transmit power of the SWIPT-enabled transmitters is also constrained by the harvested energy. As a result, the mathematical framework involves more correlated random variables and, thus, is of higher complexity. Monte Carlo simulations are given to corroborate the accuracy of the mathematical analysis and to shed light on the behavior of the OP with respect to several important parameters, e.g., the transmit power and the number of relays. Our findings illustrate that increasing the transmit power and/or the number of relays is beneficial for the outage probability. Web of Science 21 22 art. no. 7653

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.

Compared with the conventional simultaneous wireless information and power transfer (SWIPT) based relaying with &ldquo, harvest-then-forward&rdquo, protocol, the battery-assisted SWIPT relaying is more practical and powerful due to the joint use of the harvested energy and supplementary battery. However, to the best of our knowledge, the performance of a battery-assisted power splitting (PS)-SWIPT decode-and-forward (DF) relay system has not been studied. In this paper, for a given amount of energy from the relay&rsquo, s battery, we propose to maximize the outage and ergodic capacities by optimizing the static and dynamic PS ratios that rely on statistical and instantaneous channel state information (CSI), respectively, and derive their corresponding outage and ergodic capacities. Computer simulations validate our analytical results and demonstrate the advantages of the dynamic PS over the static PS in terms of the outage and ergodic capacities, as well as the energy efficiency.

Non-orthogonal multiple access (NOMA) was recently regarded as a potential technique for next generation wireless networks. Recent works on relay selection for cooperative NOMA systems have mainly addressed the best relay selection to forward its received signals to terminal nodes. Nonetheless, in practical scenarios, the best relay may be unavailable due to non-ideal conditions such as scheduling and overload constraints or possibly due to channel feedback delay. Therefore, there is compelling need to consider a more practical solution, in which the best available relay is selected. In this article, we examine the error rate performance for simultaneous wireless information and power transfer (SWIPT)-enabled NOMA, while considering the selection of the mth best available relay. In particular, we present an exact pairwise error probability (PEP) expression to obtain a bit error rate (BER) upper bound. The asymptotic PEP is investigated to evaluate the achievable diversity order for NOMA users. Finally, simulation results are provided to verify the accuracy of the derived PEP expressions and to give more insights into the system performance. publishedVersion

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 consider the resource allocation problem to maximize the minimum (max&ndash, min) user&rsquo, s secure energy efficiency (SEE) in downlink massive multiple-input multiple-output (MIMO) systems with simultaneous wireless information and power transfer (SWIPT). First, transmission power and power splitting ratio are designed to achieve the max&ndash, min user&rsquo, s SEE subject to harvested energy threshold, the constraints of transmission power, and power splitting ratio. Secondly, the optimization problem is non-convex and very difficult to tackle. In order to solve the optimization problem, we converted to a series of parameter optimization subproblems by fractional programming. Then, we employ the first-order Taylor expansion and successive convex approximation (SCA) method to solve parameter optimization problems. Next, a secure energy-efficient resource allocation (SERA) algorithm with the bisection method is proposed to find the max&ndash, min SEE of the system. Finally, simulation results show the effectiveness and superiority of the SERA algorithm.

Simultaneous wireless information and energy transfer based on radio frequency (RF) energy harvesting can transmit power and information at the same time and can use the same wireless signal to decode the information and to charge the battery. In order to improve spectrum efficiency of energy-constrained networks, we consider combining cooperative relay with simultaneous information and energy transfer in this paper. The optimal relay power allocation and relay selection algorithms based on statistical channel state information (CSI) and perfect CSI are proposed, respectively. Specifically, the system first selects the relay nodes that can correctly decode the source information and, then among them, selects the node with the best second hop channel condition. We derive the exact analytical outage probability of the proposed algorithms by using order statistical tool. The analytical results are compared and verified by Monte Carlo simulations. It is observed that the outage probabilities of our proposed algorithms based on statistical CSI and perfect CSI are all lower than that of the corresponding traditional max&ndash, min algorithms.

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.

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

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