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Non-orthogonal multiple access (NOMA) has emerged as a key enabling technology in the realm of millimeter-wave (mmWave) massive MIMO (mMIMO) systems for enhancing spectral efficiency (SE). Furthermore, it is believed that simultaneous wireless information and power transmission (SWIPT) will allow for the system’s energy efficiency (EE) to be maximised. The effectiveness of the mmWave mMIMO-NOMA system along with SWIPT has been examined in this article under multi-user (MU) scenarios. This paper’s major goal is to construct a low-complexity hybrid-precoder (HP) while taking into account the sub-connected (SC) architecture. The linear precoder is a computationally demanding technique as a result of the matrix inversion. The authors of this paper have suggested a symmetric sequential over-relaxation (SSOR) complex regularised zero-forcing (CRZF) linear precoder. The power distribution for the mmWave mMIMO-NOMA system and power splitting factors for SWIPT are jointly tuned to maximize the sum rate along with the suggested SSOR-CRZF precoder. In regards to complexity, SE, and EE, the SSOR-CRZF-HP surpasses conventional linear precoders.

Federated learning (FL) has emerged as a promising distributed machine learning technique. It has the potential to play a key role in future Internet of Things (IoT) networks by ensuring the security and privacy of user data combined with efficient utilization of communication resources. This paper addresses the challenge of maximizing energy efficiency in FL systems. We employed simultaneous wireless information and power transfer (SWIPT) and multi-carrier non-orthogonal multiple access (MC-NOMA) techniques. Also, we jointly optimized power allocation and central processing unit (CPU) resource allocation to minimize latency-constrained energy consumption. We formulated an optimization problem using a Markov decision process (MDP) and utilized a deep deterministic policy gradient (DDPG) reinforcement learning algorithm to solve our MDP problem. We tested the proposed algorithm through extensive simulations and confirmed it converges in a stable manner and provides enhanced energy efficiency compared to conventional schemes.

Considering the heterogeneity of users to be served (different receiver structures) and the diversity of service requirements in the future large-scale Internet of things, an IRS-assisted simultaneous wireless information and power transfer (SWIPT) non-orthogonal multiple access (NOMA) communication system model for heterogeneous scenarios where power splitting (PS) users and time switching (TS) users coexist was proposed. Under the condition of satisfying the quality of service of the proposed scheme was better than other schemes two types of users, the transmit power of the base station was minimized by jointly optimizing the active beamforming of the base station, the passive phase shift matrix of the IRS, the power splitting ratio of the PS users, the time switching coefficient of the TS users and the successive interference cancellation decoding order of the two types of users. In order to solve the non-convex problem, an alternating iterative method based on successive convex approximation was used to split the problem into multiple sub-problems. For the passive beamforming optimization sub-problem of IRS phase shift, the sequential rank-one constraint relaxation approach was used to solve it. Simulation results show that the base station transmission power of the IRS-assisted communication system is significantly lower than that of the non-IRS scheme, the base station transmission power of IRS-assisted NOMA communication system is lower than that of IRS-assisted orthogonal multiple access communication system, the base station transmission power of the IRS-assisted PS-SWIPT system is lower than that of the IRS-assisted TS-SWIPT system.

Simultaneous wireless information and power transfer (SWIPT) is a method through which users can simultaneously obtain energy and receive data from the base station (BS). This allows them to charge their batteries, which have limited power capacity, and enhance the quality of service (QoS). Nevertheless, this technology encounters the double near-far issue, where users located at the edges of the cell experience insufficient energy due to energy path loss, resulting in a decrease in system performance. In this investigation, we integrate the self-energy recycling technology with a D2D communication system that enables full-duplex operation. By employing this technology, the D2D cell edge user (DCEU) can harvest energy from self-interference and utilize it to transmit data to the nearest D2D cell center user (DCCU). The DCCU combines its data with the DCEU and sends it to the BS using uplink non-orthogonal multiple access (NOMA). Both the DCCU and DCEU use a significant amount of energy when transmitting data, which negatively affects the quality of service (QoS). The goal of this research is to decrease the overall energy consumption of the DCEU and DCCU while maintaining their QoS. The defined problem is complex due to time and power limitations, as well as the presence of self and NOMA interference. To address this issue, we utilize a technique that combines time and power allocation. The numerical results demonstrated that the proposed scheme consumes 28.12% and 40.67% lesser amount of energy as compared to the baseline schemes.

Among diverse number of strategies which are currently under investigation for upcoming wireless networks, non-orthogonal multiple access (NOMA) seems to be noteworthy. Recent research has focused on relay selection for cooperative simultaneous wireless information and power transfer (SWIPT)-NOMA systems. Partial Relay Selection (PRS) has been identified as the most effective method for enhancing the performance of cell edge users during signal transmission. Based on these grounds, in this work, we propose a Relay Selection Decode and Forward-SWIPT-NOMA (RS-DF-SWIPT-NOMA) system and examine its performance in terms of outage probability (OP), bit error rate (BER), throughput for delay-limited transmission mode (DLT), and energy efficiency (EE) by considering both perfect and imperfect successive interference cancellation (SIC) scenarios for SWIPT enabled NOMA using PRS. The PRS protocol selects the user with the optimal channel conditions among all accessible users to serve as a relay for cell edge users. Analytical equations are formulated for these parameters, and theoretical and simulation results indicate that the proposed approach surpasses conventional DF-SWIPT NOMA systems. Furthermore, this work analyzes the performance of cell edge users with optimal power splitting factor (OPSF), and the simulation results demonstrate that OPSF based RS-DF-SWIPT-NOMA system outperforms the fixed power splitting factor (FPSF) based RS-DF-SWIPT-NOMA system.

An integrated, miniature, dual-purpose circular patch antenna is proposed for Simultaneous Wireless Information and Power Transmission (SWIPT). The design proposes a proximity-coupled feed to the radiative circular patch for Wireless Information Transfer (WIT) in ${\mathrm {5.7 \text {GHz}}}$ - ${\mathrm {6.0 \text {GHz}}}$ band and an integrated capacitive-coupled feeding network, with full-wave rectification (FWR) using regenerative opposite fringing fields from the radiating edges of the patch for energizing IoT sensors by means of wireless power transfer (WPT) at ${\mathrm {5.2 \text {GHz}}}$ . For the realization, two co-polarized fringing field harvesters are capacitively coupled to the radiating edges of the patch to regenerate those opposite fringes whose currents are effectively matched to the FWR using a pair of Schottky diodes for direct current (DC) power generation. Since the gain and efficiency of the patch, in WIT mode, are favoured when using the FWR network, the effective regenerative fields, which are deemed attractive in modern wireless sensor network (WSN) applications for boosting the lifespan of sensor nodes.

In this paper, we consider a simultaneous wireless information and power transfer (SWIPT) system adopting hybrid analog-digital beamforming where a base station (BS) with massive antennas transmits different data streams to multiple single-antenna devices. Our primary objective is to minimize the transmit-power of the BS while ensuring energy harvesting and signal-to-interference-plus-noise ratio (SINR) requirements of each device. We specifically highlight that our approach can accommodate the scenarios where users have different requirements on the harvested energy and the received SINR. We propose two suboptimal solutions in which digital and analog precoders are designed jointly. In the first solution (OptDig-ProRF), the objective function is approximated to be independent of the digital precoder and power splitting ratios, and the local minimum of the objective function is found to obtain an analog precoder. Subsequently, the optimal digital precoder and power splitting ratios are found for the obtained analog precoder using semidefinite relaxation of the original problem. In the second solution (ZfDig-SohRF), to reduce computational complexity, we newly design a zero-forcing (ZF) digital precoder which meets users’ requirements while applying the corresponding analog precoder proposed in the literature. The two precoders are iteratively found until the transmit power difference between two consecutive updates falls below a threshold. Illustrative results show that the OptDig-ProRF scheme yields a very close performance to the fully digital precoder in terms of transmit power, while the ZfDig-SohRF scheme outperforms the optimal digital precoder plus a conventional analog precoder scheme at high SINR constraints.

Non-orthogonal multiple access (NOMA) has emerged as an effective technology, aiding in latency reduction, improving security and reliability, and enhancing the spectral efficiency and capacity in Internet of Things (IoT)-enabled communication systems. In this work, an implementation of co-operative secure multiple-input single-output NOMA IoT framework is proposed and examined in a two-fold manner. First, under the consideration of standalone links, a user selection criteria which relies on the characterization of sum ergodic capacity (SEC) is investigated in the presence of an eavesdropper (ED) and beamforming constraints. Next, using the optimized beamformers, a user selection criteria which relies on the outage probability analysis is performed under cooperative relaying considerations. We demonstrate that our optimization approach achieves reduced capacity and coverage for the ED while maximizing the overall SEC and coverage of the network under multiple network configurations. The proposed optimization solution demonstrates superior performance compared to the benchmarked schemes. Derived closed-form analytical expressions are validated through simulation means.

This paper introduces an innovative hybrid wireless power transfer (H-WPT) scheme tailored for IIoT networks employing multiple relay nodes. The scheme allows relay nodes to dynamically select their power source for energy harvesting based on real-time channel conditions. Our analysis evaluates outage probability within decode-and-forward (DF) relaying and adaptive power splitting (APS) frameworks, while also considering the energy used by relay nodes for ACK signaling. A notable feature of the H-WPT scheme is its decentralized operation, enabling relay nodes to independently choose the optimal relay and power source using instantaneous channel gain. This approach conserves significant energy otherwise wasted in centralized control methods, where extensive information exchange is required. This conservation is particularly beneficial for energy-constrained sensor networks, significantly extending their operational lifetime. Numerical results demonstrate that the proposed hybrid approach significantly outperforms the traditional distance-based power source selection approach, without additional energy consumption or increased system complexity. The scheme’s efficient power management capabilities underscore its potential for practical applications in IIoT environments, where resource optimization is crucial.

With the rapid development of the internet of things (IoT) era, IoT devices may face limitations in battery capacity and computational capability. Simultaneous wireless information and power transfer (SWIPT) and mobile edge computing (MEC) have emerged as promising technologies to address these challenges. Due to wireless channel fading and susceptibility to obstacles, this paper introduces intelligent reflecting surfaces (IRS) to enhance the spectral and energy efficiency of wireless networks. We propose a system model for IRS-assisted uplink offloading computation, downlink offloading computation results, and simultaneous energy transfer. Considering constraints such as IRS phase shifts, latency, energy harvesting, and offloading transmit power, we jointly optimize the CPU frequency of IoT devices, offloading transmit power, local computation workload, power splitting (PS) ratio, and IRS phase shifts. This establishes a multi-variate coupled nonlinear problem aimed at minimizing IoT devices energy consumption. We design an effective alternating optimization (AO) iterative algorithm based on block coordinate descent, and utilize closed-form solutions, Dinkelbach-based Lagrange dual method, and semidefinite relaxation (SDR) method to minimize IoT devices energy consumption. Simulation results demonstrate that the proposed scheme achieves lower energy consumption compared to other resource allocation strategies.

Simultaneous wireless information and power transfer (SWIPT) has emerged as a pivotal technology in 6G, offering an efficient means of delivering energy to a large quantity of low-power devices while transmitting data concurrently. To address the challenges of obstructions, high path loss, and significant energy consumption associated with long-distance communication, this work introduces a novel alternating iterative optimization strategy. The proposed approach combines active simultaneous transmission and reflection of reconfigurable intelligent surfaces (STAR-RIS) with SWIPT to maximize spectrum efficiency and reduce overall system energy consumption. This method addresses the considerable energy demands inherent in SWIPT systems by focusing on reducing the power output from the base station (BS) while meeting key constraints: the communication rate for information receivers (IRs) and minimum energy levels for energy receivers (ERs). Given complex interactions between variables, the solution involves an alternating iterative optimization process. In the first stage of this approach, the passive beamforming variables are kept constant, enabling the use of semi-definite relaxation (SDR) and successive convex approximation (SCA) algorithms to optimize active beamforming variables. In the next stage, with active beamforming variables fixed, penalty-based algorithms are applied to fine-tune the passive beamforming variables. This iterative process continues, alternating between active and passive beamforming optimization, until the system converges on a stable solution. The simulation results indicated that the proposed system configuration, which leverages active STAR-RIS, achieves lower energy consumption and demonstrates improved performance compared to configurations utilizing passive RIS, active RIS, and passive STAR-RIS. This evidence suggests that the proposed approach can significantly contribute to advancing energy efficiency in 6G systems.

In this paper, a new methodology is developed for modeling and analyzing a full-duplex UAV-assisted relay system to facilitate solving the problems of UAV energy constraints and the vulnerability of UAVs to eavesdropping in the air. Combining simultaneous wireless information and power transfer (SWIPT) technology, we model the downlink UAV eavesdropping channel and propose a secure transmission protocol for a full-duplex UAV-assisted relay system. Using this transmission protocol, we analyze and derive the connectivity and security of the entire communication link, including connection probability and lower bounds on secrecy outage probability. A key intermediate step in our analysis is to derive the signal-to-digital noise ratio of the destination and eavesdropping nodes of the full-duplex UAV relay link. The analyses show that the power allocation factor λ is a trade-off between system connectivity and security, while greater eavesdropping interference needs to be sacrificed for an equal magnitude of security performance improvement under high security demand conditions.

To balance the information security and energy harvest for massive internet-of-things (IoT) devices, an unmanned aerial vehicle (UAV)–assisted secure communication model is proposed in this paper. We extend the secure transmission model with physical layer security (PLS) to simultaneous wireless information and power transfer (SWIPT) technology and optimize the UAV trajectory, transmission power, and power splitting ratio (PSR). The nonconvex object function is decomposed into three subproblems. Then a robust iterative suboptimal algorithm based on the block coordinate descent (BCD) method is proposed to solve the subproblems. Numerical simulation results are provided to show the effectiveness of the proposed method. These results clearly illustrate that our resource allocation schemes surpass baseline schemes in terms of both transmit power and ratio of harvesting energy, while maintaining an approximately instantaneous secrecy rate.

Abstract Remote monitoring systems has emerged to automate public services, where Internet of Things (IoT) devices are deployed to collect and relay streams of status updates to a remote control centre. The freshness of collected data is of critical importance to system performance, which can be quantified by the concept of age of information (AoI). To obtain timely perception of the monitored area, each sensor tends to sample status updates at the maximum frequency, which may lead to device drop‐outs due to limited battery capacity. Simultaneous wireless information and power transfer (SWIPT) is considered as a promising technology to prolong network lifetime. In this paper, a SWIPT‐enabled two‐hop relay network, where a relay node uses power splitting protocol to assist data transmissions from multiple source nodes to the destination is considered. The impact of power splitting coefficients, data arrival pattern and time‐varying channel conditions on the averaged age performance and expected lifetime of the system is theoretically analysed. Moreover, a lightweight relay strategy which selectively forward packets based on a reward function consisting of energy level at relay node and expected age reduction is developed. Simulation results show that the proposed strategy outperforms existing schemes in collecting status updates in a timely and energy‐efficient manner.

The concept of integrating cooperative communication in non-orthogonal multiple access (NOMA) based networks (also known as cooperative NOMA) is inspired by the need to enhance network scalability with guaranteed fair resource allocation. However, sustaining the cooperative NOMA (C-NOMA) network lifetime becomes a challenging problem due to the energy bottleneck of the devices acting as relays for weak users. To alleviate this problem, the integration of radio frequency-based energy harvesting technique known as simultaneous wireless information and power transfer (SWIPT) in C-NOMA networks has been proposed. In this article, we present an extensive review of various contributions to the performance analysis of SWIPT-aided C-NOMA networks. To begin with, we identify critical guidelines needed for efficient network design. Moreover, we present an illustration of the system model in order to understand the fundamental relationship among different network components from a technical perspective. Further to this, we categorize and present an in-depth review of notable studies based on the type of relay employed, the number of relays deployed and the type of communication protocol adopted. Finally, we identify open areas worth exploring for future research works.

This study investigates the performance of user equipments (UEs) and IoT devices in a multi-user (MU) multiple-input single-output (MISO) configuration based non-orthogonal multiple-access (NOMA) system. The proposed model includes a base station surrounded by many users and a number of dispersed IoT devices. In the considered MU IoT network scenario, power allocation coefficients are set to ensure that both the relaying UE and the targeted IoT device experience increased performance. To assist the intended IoT device with weak channel conditions, an optimal user selection method is developed that picks a UE with comparatively better reception, and thereby the selected UE acts as relay forward node utilizing the simultaneous wireless information and power transfer protocol. The characterization of a key performance metric, i.e., the outage probability is derived by adopting a two-step procedure. First, quadratic forms of signal to interference plus noise ratio (SINR) at the relaying UE and the signal-to-noise ratio (SNR) and SINR at the intended IoT device are constructed. Then, using the indefinite quadratic form approach, we arrive at closed-form expressions for the outage probability (OP) of intended IoT device under linearly dependent beamformers. To validate the analytical expressions provided in this study, simulations are performed. We demonstrate that by utilizing the proposed user selection technique in MU-MISO-NOMA system decreases the OP of the intended IoT device by 40% on average. Furthermore, utilizing multiple transmit antenna elements decreases the OP of the intended IoT device by approximately 10%.

In order to improve the spectrum effectiveness, decrease the power consumption of wireless communication system, for a two-way cooperative non-orthogonal multiple access (NOMA) network with simultaneous wireless information and power transfer (SWIPT), an adaptive power splitting scheme of SWIPT was proposed.Based on the decode-and-forward protocol and the users’ distance information, the successive interference cancellation was carried out at the relay to decode the users’ messages and harvest the energy from the sources.An adaptive power splitting scheme was proposed based on users’ channel state information, which the relay could successfully decode the users’ information and harvest the most energy from the sources.Based on the harvested energy, the relay forwarded the decoded information of the users in the next time slot.According to the proposed adaptive power splitting scheme, the overall outage probability, end-to-end outage probability, and the diversity gain at high signal-to-noise ratio were derived.Compared with three-way cooperative orthogonal multiple access network with fixed power splitting of SWIPT, the proposed adaptive power splitting of SWIPT for two-way cooperative NOMA networks can achieve much better outage performance.

This paper presents the carrier harmonic modulation (CHM) for near-field data communication during wireless power transmission. The proposed CHM does not increase the coil dimension, and an additional data driver is not required. Compare to conventional modulation techniques such as frequency-shift keying (FSK) and amplitude-shift keying (ASK), the power delivered to the load (PDL) of CHM is independent of the data transmission. The prototype CHM provides a data rate of 1.1 Mbps while the power carrier frequency is also 1.1 MHz. It achieved a maximum PDL of 641 mW and the system efficiency of 17% with a 30 mm TX/RX coil diameter.

Due to the excellent broadcasting characteristics of radio signals, simultaneous wireless information and power transfer (SWIPT) can transmit both information and energy, and provide users with stable power supply. Wireless channel has the characteristics of openness, which will lead to the leakage of information in the SWIPT system. It is one of the research hotspots in the industry to ensure the secure transmission of information in SWIPT system where there are differences in the transmission of energy and information. This paper proposes an ‘information-energy’ dynamic switching opportunistic secure transmission scheme. First, a model considering three factors of multi-cell, multi-user and multiple eavesdropper is established which assumes that the user adopts a time-domain switching receiver that collects energy in a nonlinear model. Then, combined with the time-varying wireless channel, a dynamic information energy switching transmission scheme based on signal-to-interference noise ratio threshold is proposed. Finally, the energy and information transmission performance of the scheme are comprehensively analysed.

Physical layer security (PLS) and simultaneous wireless information and power transfer (SWIPT) in cooperative relaying have gained great interest as technologies for security and energy enhancement in Internet-of-Things (IoT) networks. In this work, we investigate PLS for a SWIPT- and AF-enabled cooperative wireless IoT system, consisting of one source, multiple energy harvesting (EH) relays, and one destination, in the presence of an eavesdropper that tries to overhear the confidential information. Furthermore, an EH-friendly jammer is deployed to transmit jamming signals aimed at the eavesdropper to improve the security system. In this context, a low-complexity, sub-optimal, but efficient relay selection method is proposed. More specifically, the relay is selected to convey information such that it has the best channel to the source. Based on the proposed system model, the performance analysis of the intercept probability (IP), asymptotic IP, and non-zero secrecy probability (NZSP) is analyzed by considering the time switching (TS)-based relaying strategy. Particularly, the exact closed-form expression of IP is achieved by applying modified Bessel function expansion. Monte-Carlo simulations are employed to corroborate the correctness and efficiency of our mathematical analysis. The time splitting factor $\alpha $ makes variations on the IP of about $3\times $ as $\alpha \in [{0.1, 0.8}]$ . However, a dramatic reduction of the IP up to $317\times $ is observed as $\alpha $ increases from 0.8 to 0.9.

In this paper, we evaluate the secrecy performance in terms of secrecy outage probability (SOP) for Internet of things (IoT) enabled multi-relaying non-orthogonal multiple access (NOMA) networks with energy harvesting over Nakagami-m fading channels. Specifically, we consider the scenario that a power-constrained source and N (N⩾1) IoT relays first harvest energy from a dedicated power beacon under a time switching mode, and then the source sends a confidential information to a legitimate user via a selected IoT relay, which forwards the decoded signal together with its own information data under a NOMA protocol to two legitimate users in the presence of an eavesdropper. Moreover, a two-stage relay selection criterion is also adopted to enhance the system’s secrecy performance. As a benchmark, we also adopt a random relay selection scheme to analyze the secrecy performance. To clearly reveal the benefits of our proposed schemes, the analytical expressions for SOP under those two schemes have been obtained and validated through Monte-Carlo simulations.

Abstract Simultaneous wireless information and power transfer (SWIPT) has recently attracted researchers and may help to satisfy future technology demands. SWIPT allows wireless power transfer (WPT) and wireless information transfer (WIT) to coexist based on shared resources. Recent studies have shown that, due to the nonlinearity of the rectifiers, high-PAPR (peak to average power ratio) waveforms provide better performance in terms of energy harvesting, making the design of power signals essential. In addition, these power signals should consume the smallest amount of resources for the WIT. In this paper, a new waveform design is proposed where the information and power signals are superposed using the same frequency and time resources. The power signal is composed of a high peak modulated rectangular wave sent during the cyclic prefix of the orthogonal frequency-division multiplexing (CP-OFDM) system, which is discarded at the information receiver, such that it does not interfere with the OFDM data symbol. Although the pulse is restricted to be within the cyclic prefix, there might be a small amount of interference caused by channel dispersion. Simulations and measurements show that a good choice of signal parameters can minimize interference on the information symbols and simultaneously provide good performance in terms of energy harvesting.

In this paper, we study secure energy efficiency (SEE) for simultaneous wireless information and power transfer (SWIPT) in a distributed antenna system (DAS) based IoT network. We consider a system in which both the legitimate user (Bob) and the eavesdropper (Eve) rely on the energy harvested from the received radio signal. Firstly, with perfect channel state information (CSI), we formulate the maximization of SEE as a constrained optimization problem. In this problem, we aim to highlight the advantage of SWIPT in exploiting the Eve’s energy harvesting requirement. This is achieved by defining a charge constraint in the SEE optimization problem which ensures that the Eve is deprived of its only energy source. Next, considering the fact that perfect CSI is hard to achieve in practice, we characterize the system performance in terms of the outage probability (OP) of SEE. For the given SWIPT-in-DAS setup, we derive the closed form expression for the OP of SEE and with the help of numerical results, we study the effect of transmit power levels, number of distributed antenna (DA) ports and the PS ratio of devices. To the best of our knowledge, this is the first attempt to define the OP of SEE for SWIPT-in-DAS.

This paper presents an optimal resource allocation scheme based on time slot switching (TS) for point-to-point single-input single-output (SISO) simultaneous wireless information and power transfer (SWIPT) systems, aiming to maximize the average achievable rate. The proposed scheme considers the nonlinear energy harvesting (EH) characteristic, and thus, the problem is formulated as a nonconvex optimization problem in the presence of a binary TS ratio. Hence, solving the problem is performed using the time-sharing strong duality theorem and Lagrange dual method. Simulations showed that the proposed scheme improves energy efficiency with respect to different transmission powers by 20%, 10%, and 3% for high-SNR, medium-SNR, and low-SNR regions, respectively. Improvement with respect to average energy efficiency versus other system performance metrics has also been noted for the proposed scheme.

In this paper, we optimize the secrecy capacity of the legitimate user under resource allocation and security constraints for a multi-antenna environment for the simultaneous transmission of wireless information and power in a dynamic downlink scenario. We study the relationship between secrecy capacity and harvested energy in a power-splitting configuration for a nonlinear energy-harvesting model under co-located conditions. The capacity maximization problem is formulated for the vehicle-to-vehicle communication scenario. The formulated problem is non-convex NP-hard, so we reformulate it into a convex form using a divide-and-conquer approach. We obtain the optimal transmit power matrix and power-splitting ratio values that guarantee positive values of the secrecy capacity. We analyze different vehicle-to-vehicle communication settings to validate the differentiation of the proposed algorithm in maintaining both reliability and security. We also substantiate the effectiveness of the proposed approach by analyzing the trade-offs between secrecy capacity and harvested energy.

This paper investigates the power control and resource allocation problem in a simultaneously wireless information and power transfer (SWIPT)-based cognitive two-way relay network, in which two secondary users exchange information through a power splitting (PS) energy harvesting (EH) cognitive relay node underlay in a primary network. To enhance the secondary networks’s transmission ability without detriment to the primary network, we formulate an optimization to maximize the minimum transmission rates of the cognitive users by jointly optimizing power allocation at the sources, the time allocation of transmission frames and power splitting at the relay, under the constraint that the transmission power of the cognitive network is set not to exceed the primary user interference threshold to ensure primary work performance. To efficiently solve this problem, a sub-optimal algorithm named the joint power control and resource allocation (JPCRA) scheme is proposed, in which we decouple the non-convex problem into convex problems and use alternative steps in the optimization algorithm to get final solutions. Numerical results reveal that the proposed scheme enhances transmission fairness and outperforms three traditional schemes.

In order to achieve the efficient interconnection of everything, under the limitations of terminal devices’ batteries and network coverage, the intelligent reflecting surface (IRS) technology was introduced to build a new IRS-aided simultaneous wireless information and power transfer (SWIPT) network.To further improve the total throughput of the network, a resource allocation (RA) scheme aiming at sum-rate maximization was proposed.Considering that the constraints of the maximum transmit power of a base station, the minimum energy requirement of each device and the phase shifts on an IRS, a joint transmit beamforming, power splitting (PS) ratio and phase shift optimization problem was formulated.Due to the non-convex problem and coupled variables, a block coordinate descent (BCD)-based algorithm was proposed.Then, the joint transmit beam forming design, PS ratio optimization and phase shift design were solved by using the successive convex approximation (SCA) and Riemannian manifold methods, respectively.Simulation results show that the proposed RA scheme performs better than the existing RA schemes in terms of sum-rate.

Increasing number of devices connected to the networks, applications and demands of new generation wireless communications cause very high energy consumption resulting in large amount of carbon emission. Thus, energy harvesting solutions together with accomplishing information transmission are required for energy efficient communications of new wireless communications generations such as 5G and 6G (i.e., 5G+). As such, due to the promise of energy efficient green communications, simultaneous wireless information and power transfer (SWIPT) techniques are expected to be indispensable component of 5G+. In this survey, the literature of multiuser SWIPT communications is reviewed for 5G+. Different multiuser SWIPT scenarios including multi-antenna communications, cooperative communications, network coding, communications security, and unmanned aerial vehicle (UAV)-enabled communication systems based on multiuser diversity and multiple access methods are thoroughly reviewed. The experimental studies are also discussed.

In this paper, we address the problem of energy consumption associated with mixed signal components such as analog-to-digital components in millimeter-wave (mmWave) massive MIMO systems. We employ non-orthogonal multiple access (NOMA) in millimeter-wave (mmWave) massive MIMO systems to further enhance the spectrum efficiency. The simultaneous wireless information and power transmission technology (SWIPT) will be used in mmWave massive Multiple-Input multiple-Output MIMO systems. The utilization of SWIPT contributes to prolonging the battery life of mobile users (MUs) and enhances the system energy efficiency (EE), especially in the NOMA scenario where the inter-user interference can be reused for energy harvesting (EH). However, we initially designed a user grouping algorithm based on the affinity propagation clustering algorithm, which preferentially groups the user equipment (UE) based on their channel correlation and distance. 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 transform the original optimization problem into a joint power allocation and power-splitting maximization problem. The considered non-convex optimization problem is arduous to tackle, resulting from the presence of coupled variables and inter-user interference. To cope with this problem, a decoupled approach is adopted, in which the power allocation and power splitting are separated, and the corresponding sub-problems are solved using the Lagrangian duality method. Simulation results confirm the effectiveness of the proposed method and demonstrate that the proposed method is near-optimal and enjoys higher spectrum and energy efficiency compared with state-of-the-art designs and the conventional SWIPT-enabled mmWave MIMO-NOMA system.

Recently, the demand for spectral and energy efficiency has significantly been increased along with new breakthroughs in programmable meta-material techniques. The integration of an intelligent reflecting surface (IRS) into simultaneous wireless information and power transfer (SWIPT) systems has attracted much attention from operators in advanced wireless communication networks (WCNs) such as fifth-generation (5G) and sixth-generation (6G) networks. In addition, an IRS-assisted SWIPT system faces many security risks that can easily be compromised by eavesdroppers. In this paper, we investigate the physical-layer secure and transmission optimization problem in an IRS-assisted SWIPT system where a power-splitting (PS) scheme is installed in the user equipment (UE). In particular, our purpose is to maximize the system secrecy rate by jointly finding optimal solutions for transmitter power, PS factor of UE, and phase shifts matrix of IRS under the required minimum harvested energy and maximum transmitter power. We propose the alternating optimization (AO)-based scheme to obtain optimal solutions. The proposed AO-based scheme can effectively solve both convex and non-convex problems; however, applying them in practice still poses some difficulties due to the complexity and long computation time. This is because many mathematical transformations are used and the optimal solution needs a number of iterations to achieve convergence. Therefore, we also propose 5 types of data and DNN structures to potentially achieve efficiency in computations by using a deep learning (DL)-based approach. The simulation results indicate that the proposed IRS scheme provides an improvement in terms of the average secrecy rate (ASR) by up to 38.91% when the number of reflecting elements is high (30 elements) compared to a scheme without an IRS. We also observe that the DL-based approach not only provides similar performance to the AO-based scheme but it also significantly reduces computation time.

This paper investigates the reconfigurable intelligent surface (RIS)-empowered dynamic power splitting designs for simultaneous wireless information and power transfer (SWIPT) systems while adopting various practical hardware issues. Specifically, we adopt the physical size of the RIS and the placement of the RIS plane to phase-align the reflected signals towards the desired direction. The analytical phase shift model for the reflecting elements is presented to characterize an intertwined relationship between amplitude and phase responses, which captures the amplitude variations depending on phase in RIS elements. Furthermore, an additive distortion noise incorporates the residual transceiver hardware impairments (RTHIs). The stringent signal-to-interference-plus-noise ratio requirement is facilitated using both the direct and indirect, i.e., RIS cascaded, links. To made complicated analysis become tractable, we exploit the statistical properties of the effective channel power which follows a Gamma distribution. The tight bounds for the achievable rates and residual energy are derived and the tradeoffs between the achievable rate and residual energy for the time switching and static power splitting designs are characterized. Finally, the numerical results confirm the accuracy of the developed framework and demonstrate the selection of the system parameters.

Although there are many articulations of SWIPT architecture implementations, the hardware impairment aspect involved in the SWIPT architecture system is not given much attention. This paper evaluates the performance of SWIPT PS Reciever architecture in the presence of IQ imbalance hardware impairment with 16-QAM transmitter and AWGN channel. The parameters SNR, BER is evaluated in the presence of amplitude, phase imbalance, and PS factor at the SWIPT receiver side. Further, the IQ imbalance is estimated and compensated using a blind compensation algorithm. The system achieved a maximum BER of 10−7 in the presence of amplitude and phase imbalance of 0.2 and 1.6 respectively.

Abstract 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.

To solve the problems of high complexity and poor real-time performance caused by traditional wireless resource management based on optimization methods, the energy efficiency maximization problem of sink node and its mathematical model were established for SWIPT-enabled sensor-cloud system, then the deep learning method was introduced to realize the solving and online decision-making with lower complexity and higher real-time performance.The mathematical model was transformed into a high-dimensional solvable form, and then a SWIFT-WMMSE algorithm with iterated forms was designed to solve optimal beamforming vector.The convergence of SWIPT-WMMSE algorithm was proved.Then, based on error propagation of DNN approximation, the scale design criteria for the DNN was deduced, and the approximation was realized through DNN training.Finally, the simulation results verify the effectiveness of SWIPT-WMMSE and DNN algorithm, as well as the approximation effect of DNN and its system performance gains.

Abstract 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.

To improve the performance of 5G communication system, a full duplex Internet of things (IoT) relay system model was built by introducing the non-orthogonal multi-access (NOMA) technology.For the relay system of simultaneous wireless information and power transfer (SWIPT), it was considered that the relay node can harvest the energy of the source node, the self-interference signal of the loop channel and the free energy access point (EAP), and NOMA technology was used to forward the source node signal and its own signal to different destination nodes.Based on the model, a power distribution collaboration SWIPT relay selection strategy was proposed to optimize system throughput.Firstly, the problem model was established based on the constraints of communication quality of service and transmission power of source nodes.And then, the original nonlinear 0-1 programming problem was converted into a pair of coupling optimization problem by mathematical transformation, and the optimal relay selection of outer optimization problem was solved based on the optimal solution of the internal optimization problem.Finally, an optimal relay selection algorithm was used to maximize system throughput.Simulation results show that the proposed model and strategy are superior to the traditional maximum-minimum relay selection schemes in terms of throughput gain, and the consideration of EAP can significantly improve the interrupt performance.

Non-orthogonal multiple access (NOMA) has recently attracted wide attention as a promising multiple access technology adopted in 5G cellular networks.In order to improve the spectrum efficiency, coverage and anti-noise performance of NOMA technology, while reduce the energy consumption of the system, a simultaneous wireless information and power transfer (SWIPT) cooperative network uplink NOMA transmission system based on orthogonal index modulation multiple access (IMMA) technology was designed, hereafter was denoted as QIMMA-SWIPT.Specifically, the QIMMA system was formed by multiple remote users, and it improved the spectrum efficiency and anti-noise performance as well as expanded the communication coverage and reduced the energy consumption of the system by decoding and forwarding relay cooperative transmission with SWIPT technology.The theoretical upper bound of the average bit error rate of QIMMA-SWIPT was derived.Simulation and analysis demonstrate that, under the same spectrum efficiency, the bit error rate performance of the cooperative QIMMA-SWIPT system is better than that of the cooperative IMMA-SWIPT and SCMA-SWIPT systems.In addition, the effects of power cut factor and source-to-relay distance on bit error performance were also deeply analyzed.

Abstract 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.

Abstract 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.

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.

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.

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, 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.

Simultaneous wireless information and power transfer (SWIPT) constitutes an emerging paradigm that prolongs the lifetime of energy-constrained devices, such as wireless sensors and Internet-of-Things (IoT) nodes. Its frequency-domain (FD) variant enables energy harvesting (EH) by using (low-power) local oscillators/mixers. In this paper, a novel FD-SWIPT waveform design that minimizes the multitone interference induced to the information signal by the energy signal, thus eliminating the need for using receive filters to this end, is described. The inherent interference suppression of the proposed strategy allows also for applying modulation classification (MC). This functionality is highly desirable in contemporary networks, where the access points utilize adaptive transmission. In this context, we analytically derive the average error probability of the proposed waveform over a Rayleigh fading channel for various modulation schemes under non-zero interference and frequency synchronization errors. Furthermore, we optimize the power of the energy tones, such that the signal-to-interference-ratio at the information signal is maximized subject to the EH and transmission power constraints. In addition, we investigate the coexistence of SWIPT with blind MC under this framework. Numerical simulation results reveal that the proposed approach substantially increases both the data rate and the harvested power in comparison to the conventional power-splitting method at the cost of a negligibly higher error probability. Also, they indicate that the employed MC scheme achieves a high success rate even in the low signal-to-noise-ratio regime. The proposed concept is validated experimentally in a realistic indoor environment by using a testbed based on software-defined radio units.

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).

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.

Abstract 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 equipment 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 factor 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 the two proposed schemes.

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

The secure energy efficiency (SEE) problem was investigated for the millimeter wave (mmWave) multiple input multiple output (MIMO) non-orthogonal multiplex access (NOMA) systems with simultaneous wireless information and power transfer (SWIPT) in the presence of multiple legitimate receiver (LR) and an eavesdropper.LR was first grouped according to the channel state information and the cluster heads of each group were selected,then the LR of each cluster was served by each beam with NOMA and hybrid precoding technology.Based on this,a SEE maximization problem was formulated by optimizing power allocation and power splitting factors.The Dinkelbach algorithm and first order Taylor approximation were proposed to transform the original non-convex problem into a convex one,and an iterative algorithm was developed to solve it.Finally,numerical results show that the proposed scheme can effectively improve the SEE.