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Summary: With the rapid increase in energy utilization and the tremendously growing number of connected devices in wireless sensor networks (WSNs), alternate power transfer methods have not only become significant for scholastic purposes but also the growth of WSNs and the reduction of operational costs. Simultaneous wireless information and power transfer (SWIPT) is an emerging technology that has the potential to boost the lifespan of WSNs. This work presents an innovative approach to improving the energy efficiency of WSNs. Here, a WSN is considered, and energy‐aware communication is established in six phases, such as setup, steady state, energy prediction, SWIPT‐based power transfer, communication/route discovery, and route maintenance. Further, a hybrid approach named tangent sine search optimization (TSSO) is created to identify the ideal node as cluster head (CH). Later, the age of the neighboring nodes is forecasted utilizing the deep long short‐term memory (DLSTM), whose trainable parameters are selected using the proposed TSSO algorithm. A SWIPT‐based power transfer is also performed for harvesting the energy to avoid node failures. The proposed TSSO‐DLSTM+SWIPT is investigated given various metrics, like delay, residual energy, throughput, and trust, and the values attained are 0.784 s, 0.790 J, 0.970 Mbps, and 0.997, respectively without any attacks. The proposed TSSO‐DLSTM+SWIPT obtained performance improvement of 11.08%, 10.07%, 7.99%, and 5.83% than the Iterative algorithm in terms of delay, residual energy, throughput, and trust. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The conventional reconfigurable intelligent surface (RIS) is limited to reflecting incident signals, thereby imposing constraints on the placement of the transmitter and receiver, which hinders achieving comprehensive signal coverage across an entire area. This paper investigates a simultaneously transmitting and reflecting (STAR)-RIS-aided simultaneous wireless information and power transfer (SWIPT) system with a nonlinear energy harvesting model under three different RIS transmission protocols: energy splitting (ES), time switching (TS), and mode switching (MS). The objective of this paper is to maximize the weighted sum power (WSP) of all energy harvesting receivers (EHRs) while ensuring fairness in the collected power among them. This is achieved by jointly optimizing the transmit beamforming at the base station (BS) and the transmission and reflection coefficients at the STAR-RIS, subject to rate constraints for information decoding receivers (IDRs), transmit power constraint at the BS, and coefficient constraints of each element at the STAR-RIS corresponding to the three protocols. Solving this optimization problem poses challenges because of the complicated objective function and numerous coupled optimization variables of the ES STAR-RIS. To address this complexity, an efficient alternating optimization (AO) approach is proposed as an iterative solution method that achieves suboptimal results. The AO algorithm is then extended to MS STAR-RIS and TS STAR-RIS. Specifically, for MS STRA-RIS, binary constraints in the STAR-RIS coefficient optimization subproblem are handled using the first-order approximation technique along with the penalty function method. For TS STAR-RIS, apart from optimizing BS transmit beamforming and STAR-RIS coefficients subproblems, the transmission and reflection time allocation of STAR-RIS also needs optimization. Numerical findings demonstrate that compared to conventional RIS-aided systems, utilizing three different protocols in a STAR-RIS-aided system can enhance power collection at EHRs while expanding the receiver placement range. Furthermore, TS STAR-RIS performs best when the IDRs do not require high achieved rates. Otherwise, ES is the best choice. [ABSTRACT FROM AUTHOR]

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.

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. [ABSTRACT FROM AUTHOR]

This study considers a simultaneous wireless information and power transfer (SWIPT) system where a single base station (BS) serves multiple Internet of Things (IoT) devices. The BS performs beamforming using multiple antennas, while a terminal uses a single antenna. We consider that a portion of the channel randomly changes, leading to inaccurate channel estimation. To design a reliable system, we introduce retransmission to the system and proposes two schemes: one that does not use previous received signals for decoding (SWIPT-ARQ) and the other one that combines previous received signals with the last received signal (SWIPT-CC). Both schemes use a 2-bit feedback signal. Furthermore, we formulate optimization problems for finding beamforming matrices and power splitting ratios in order to minimize transmission power at each (re)transmission and provide solutions. Simulation results show that the power efficiency of SWIPT-CC achieves up to 69% of the power efficiency assumed under perfect channel estimation, and SWIPT-ARQ achieves up to 44%. [ABSTRACT FROM AUTHOR]

This paper presents a Simultaneous Lightwave Information and Power Transfer (SLIPT) system for implantable biomedical applications composed of an external and internal (i.e., implantable) unit designed at a transistor level in TMSC 0.18 µm standard CMOS Si technology, requiring Si areas of 200 × 260 µm2 and 615 × 950 µm2, respectively. The SLIPT external unit employs a semiconductor laser to transmit data and power to the SLIPT internal unit, which contains an Optical Wireless Power Transfer (OWPT) module to supply its circuitry and, in particular, the data receiver module. To enable these operations, the transmitter module of the SLIPT external unit uses a novel reverse multilevel synchronized pulse position modulation technique based on dropping the laser driving current to zero so it produces laser pulses with a reversed intensity profile. This modulation technique allows: (i) the SLIPT external unit to code and transmit data packages of 6-bit symbols received and decoded by the SLIPT internal unit; and (ii) to supply the OWPT module also in the period between the transmission of two consecutive data packages. The receiver module operates for a time window of 12.5 µs every 500 µs, this being the time needed for the OWPT module to fully recover the energy to power the SLIPT internal unit. Post-layout simulations demonstrate that the proposed SLIPT system provides a final data throughput of 6 Mbps, an energy efficiency of 7 pJ/bit, and an OWPT module power transfer efficiency of 40%. [ABSTRACT FROM AUTHOR]

One of the most well-known uses of smart cities has been massive multimedia offerings. But the enormous demand for device-to-access point (D2A) communication has significantly increased the energy consumed and the greenhouse impact. As a result, energy-harvesting-based two-way access points (AP) and space shift keying (SSK) modulation are used to analyse the error performance of smart users in the smart city. Communication between smart users and a centralised AP is crucial in a smart metropolis. In this instance, energy harvesting at the two-way AP over the Saleh–Valenzuela channel has been taken into consideration using the simultaneous wireless information and power transmission (SWIPT) system. For smart users, SWIPT can remove the need for battery replacement or meet energy needs. In contrast, SSK modulation is a less complex method that does not need as many radio-frequency chains, inter-antenna synchronisation, or inter-channel interference for multiple-input-multiple-output transmission. Applying multi-user selection combining, smart sensors' average bit error probability efficiency is derived in closed form. The numerical and simulation assessment results demonstrate how energy harvesting affects the system's effectiveness. [ABSTRACT FROM AUTHOR]

Neighbourhood area network (NAN) performance is analyzed with space shift keying (SSK) modulation and energy harvesting-based cooperative amplify-and-forward (AF) relaying. Wifi-enabled home appliances (HAs) can transfer the information to the utility control centre through the smart meter (SM) in the NAN. The HAs in NAN work on a power-saving mechanism, and they drastically increase the spectral efficiency. The Markov chain dynamically models the number of active HAs in the smart grid (SG) network. Moreover, simultaneous wireless information and power transfer combined with AF relaying-based SM helps overcome the rising demands of SG communication by providing an enhanced data rate, low latency, shorter coverage, widespread connectivity of the massive number of devices along with energy-efficiency. Mathematical expressions for average bit error probability are derived for NAN over mixed Saleh–Valenzuela and Rician fading channel based on the multi-user selection combination. The Monte Carlo simulation verifies the numerical results. The result illustrates that the SG NAN performance can be improved by combining SSK modulation with energy harvesting schemes. [ABSTRACT FROM AUTHOR]

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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.

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. [ABSTRACT FROM AUTHOR]

This work aims at achieving the secrecy rate (SR) enhancement in amplify-and-forward (AF) relay-aided simultaneous wireless information and power transfer (SWIPT)-NOMA network via control-jamming (CJ) whilst satisfying the constraints on total transmit power budget. Here, in order to coordinate the information processing and energy-harvesting (EH), power-splitting (PS) protocol is deployed at the relay. For comparison purposes, in addition to CJ, the SR of with-jamming (J) and without-jamming (WJ) conditions are also highlighted in the existence of an eavesdropper (Eve). Moreover, the analytical expression for Ergodic SR is evaluated at the NOMA users under the CJ scenario. Next, to maximize the SR of the users further, an optimal power allocation (OPA) scheme has been adopted, which involves both particle swarm optimization (PSO) and Lagrangian multiplier (LM)-based approaches to acquire the optimized power factors of various nodes of the network. In addition, we analyzed the affect of major parameters such as: J → E v e distance, transmit signal-to-noise ratio (SNR), and R → E v e distance on the SR by exploiting distinct jamming scenarios. Finally, a significant secrecy performance gain in terms of SR is verified with proposed CJ over other jamming conditions and OPA over the fixed power allocation (FPA) and it is confirmed through Monte-Carlo based simulations. [ABSTRACT FROM AUTHOR]

This study examined the implementation of rate-splitting multiple access (RSMA) in a multiple-input single-output system using simultaneous wireless information and power transfer (SWIPT) technology. The coexistence of a base station and a power beacon was considered, aiming to transmit information and energy to two sets of users. One set comprises users who solely harvest energy, whereas the other can decode information and energy using a power-splitting (PS) structure. The main objective of this optimization was to minimize the total transmit power of the system while satisfying the rate requirements for PS users and ensuring minimum energy harvesting (EH) for both PS and EH users. The non-convex problem was addressed by dividing it into two subproblems. The first subproblem was solved using a deep learning-based scheme, combining principal component analysis and a deep neural network. The semidefinite relaxation method was used to solve the second subproblem. The proposed method offers lower computational complexity compared to traditional iterative-based approaches. The simulation results demonstrate the superior performance of the proposed scheme compared to traditional methods such as non-orthogonal multiple access and space-division multiple access. Furthermore, the ability of the proposed method to generalize was validated by assessing its effectiveness across several challenging scenarios. [ABSTRACT FROM AUTHOR]

The cluster communication of the beyond 5G Heterogeneous Network (Hetnet) is dependent on multiple access techniques. Reconfigurable intelligent surface (RIS) is the potential benefit of 5G when it is combined with nonorthogonal multiple access (NOMA). Although NOMA has been suggested as a way to improve energy efficiency, wireless networks are now denser than before. As a result, the issue with distance, spectrum and energy use gets worse. Due to the limited energy supply, it is necessary to create control over the channel and revolutionary energy efficiency that maximises both total rate and power optimisation. We jointly optimize the transmit power and optimal phase shift to change the weak environment in order to increase the signal-to-noise ratio (SNR) and multiplex data streams in the spatial domain, RIS arrays are used to form beams in the required directions. By decoupling sub channel allocation, a low-complexity sub channel matching method is suggested in order to maximise energy efficiency. In the proposed work, It is demonstrated that the RIS-assisted NOMA system provides promising solutions for users at different scenarios and exhibit significant results in error performance and achievable data rates even in the presence of system imperfections. [ABSTRACT FROM AUTHOR]

This paper examines the performance of Full-Duplex Cooperative Rate Splitting (FD-CRS) with Simultaneous Wireless Information and Power Transfer (SWIPT) support in Multiple Input Single Output (MISO) networks. In a Rate Splitting Multiple Access (RSMA) multicast system with two local users and one remote user, the common data stream contains the needs of all users, and all users can decode the common data stream. Therefore, each user can receive some information that other users need, and local users with better channel conditions can use this information to further enhance the reception reliability and data rate of users with poor channel quality. Even using Cell-Center-Users (CCUs) as a cooperative relay to assist the transmission of common data can improve the average system speed. To maximize the minimum achievable rate, we optimize the beamforming vector of Base Station (BS), the common stream splitting vector, the cooperative distributed beam vector and the strong user transmission power under the power budget constraints of BS and relay devices and the service quality requirements constraints of users. Since the whole problem is not convex, we cannot solve it directly. Therefore, we propose a low complexity algorithm based on Successive Convex Approximation (SCA) technology to find the optimal solution to the problem under consideration. The simulation results show that FD C-RSMA has better gain and more powerful than FD C-NOMA, HD C-RSMA, RSMA and NOMA. [ABSTRACT FROM AUTHOR]

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 novel fairness-aware harvested energy efficiency-based green transmission scheme for wireless information and power transfer (SWIPT) aided sensor networks is developed for active beamforming of multi-antenna transmitter and passive beamforming at intelligent reflecting surfaces (IRS). By optimizing the active beamformer assignment at the transmitter in conjunction with the passive beamformer assignment at the IRS, we aimtomaximize the minimum harvested energy efficiency among all the energy receivers (ER) where information receivers (IR) are bound to the signal-interference-noise-ratio (SINR) and the maximum transmitted power of the transmitter. To handle the non-convex problem, both semi-definite relaxation (SDR) and block coordinate descent technologies are exploited. Then, the original problem is transformed into two convex sub-problems which can be solved via semidefinite programming. Numerical simulation results demonstrate that the IRS and energy beamformer settings in this paper provide greater system gain than the traditional experimental setting, thereby improving the fairness-aware harvested energy efficiency of the ER. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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.

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.

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.

To solve the problems of complex energy supply and poor communication effect of cell-edge users, combining the advantages of simultaneous wireless information and power transfer (SWIPT) and collaborative non-orthogonal multiple access (CNOMA), two novel protocols are proposed. By employing the PS and TS strategies in SWIPT, respectively, two protocols are named: SWIPT-CNOMA-PS and SWIPT-CNOMA-TS. Based on the protocols, a new method for selecting relays is first established by considering two factors—energy state and channel condition. To further improve energy efficiency, the relay harvests the energy of the signal sent by the source and stores it. We establish a one-dimensional Markov chain with the energy state as the system state to analyze the variation of the relay energy. Exploiting the conservation equation, the probability of energy sufficiency of the node and outage probabilities of users are derived. Finally, the impact of the energy threshold and the number of relays on the outage probability of users is revealed. The protocol in this paper shows better performance than the OMA protocol when the transmit signal-to-noise ratio (SNR) is less than 14 dB and the protocol in the literature when the transmit SNR is less than 11 dB. [ABSTRACT FROM AUTHOR]

To further address the energy constraint problem and improve the secrecy performance of unmanned aerial vehicle (UAV) systems in the fifth generation (5G)-enabled Internet of Things, we consider a secure UAV system with simultaneous wireless information and power transfer in the presence of a full-duplex active eavesdropper, which eavesdrops on confidential information and transmits malicious jamming signals simultaneously. In particular, the UAV is powered by a constrained onboard battery that can harvest energy from the ambient radio frequency signals. The trajectory of the UAV, power splitting ratio, and transmitting power are jointly optimized to maximize the secrecy rate of the system. Owing to the non-convexity of the problem, we propose an alternative optimization algorithm by applying successive convex approximation and block coordinate descent methods. The simulation results show the proposed joint optimization algorithm can promote the average secrecy rate of the system as compared with other benchmark schemes. [ABSTRACT FROM AUTHOR]

The general interference is the imperative trouble for simultaneous wireless information and power transfer (SWIPT) system. Although interference has bad influences on the performance of the system, it carries energy simultaneously. In this paper, the energy-constrained relay of the SWIPT system needs to spend much time on energy collecting (EC) in the information transmission (IT) period. Therefore, we propose the scheme of interference signal energy collecting (ISEC) when the interference is strong, and the SWIPT system does not carry out IT. The relay of the system continues to collect energy and stores it until the interference has minimal impact on IT. Then the system performs IT. We divide the collected interference energy equally into several parts, and each IT block receives one part. The proposed scheme is appealing because it can reduce the time of EC in IT period to make the relay spends more time forwarding the received signal in order to improve the performance of the system throughput. Furthermore, we propose a time-switching (TS) protocol based on EC at the relay. And it allows the relay forwarding signal at an appropriate power. Under the protocol, the time of EC can be flexible according to the forwarding power that we give so that the collected energy can be used more efficiently. We give the expressions of the system throughput according to the proposed scheme and protocol. Moreover, the influence of the interference power on the system throughput is also studied. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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.

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%.

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. [ABSTRACT FROM AUTHOR]

In next-generation heterogeneous networks, device-to-device communications are a key enabler to support a wider and diverse range of applications. They play an important role to guarantee the performance and quality of service requirements for the future ultra-dense networks. D2D-enabled cellular networks allow user equipment to communicate directly without any or with a partial association with macro base stations or with small base stations. In this paper, we propose a distance-based dynamic approach to minimize the interference and to guarantee QoS for diverse types of users equipment, such as macro user, small user and D2D user. The mode selection is used for minimize the interference and to guarantee QoS for both cellular and D2D communication links. Moreover, we investigated hybrid simultaneous wireless information and power transfer to achieve the higher data rates while guaranteeing the minimum harvested energy. Additionally, our scheme employs a transmit antenna selection criterion to exploit the spatial diversity gain of a multiple antennas for small base station. Results obtained show that coverage probability is improved in macro and small base stations links, when compared with traditional neighbor-based methods, we validate the theoretical findings and demonstrate that significant performance gain over orthogonal multiple access scheme in terms of spectral efficiency can be achieved by the proposed algorithms in a SWIPT-enabled NOMA system where we show the energy efficiency. [ABSTRACT FROM AUTHOR]

We study a downlink cooperative non-orthogonal multiple access (NOMA) system in which a base station (BS) serves two paired users on the same frequency band simultaneously, and the near user acts as an energy-constrained relay for the far user since there is no direct link between the BS and the far user due to physical obstacles or heavy shadowing. To replenish energy of the near user for relaying, we enable the near user to harvest energy from BS signals by adopting the simultaneous wireless information and power transfer (SWIPT) technique. Different from the linear energy harvesting (EH) model used in most of the existing literature, we adopt a non-linear model for EH. By considering the non-linear features of the practical circuits, we aim to minimize the BS energy consumption while ensuring the minimum required transmission rate of both users. Since the formulated problem contains coupled power and time resource variables, it is challenging to solve it directly. Thus, we propose an optimal power-time resource allocation algorithm by decoupling the variables properly. Simulation results verify the theoretical analysis and show the performance of the considered system. [ABSTRACT FROM AUTHOR]

This paper considers an unmanned aerial vehicle (UAV)-assisted communication system with simultaneous wireless information and power transfer (SWIPT). In modeling the composite channel, the probability of line-of-sight (LoS)/non-LoS is taken into account, along with log-normal shadowing. Moreover, for small-scale fading, Nakagami-m and Rayleigh distributions are considered for the LoS and non-LoS (NLoS) conditions, respectively. For enabling radio-frequency (RF) energy harvesting, a hybrid power-splitting (PS) and time switching (TS) based architecture is considered at the UAV. In order to provide relay cooperation to the remote mobile user, the UAV performs decode-and-forward (DF) operation. To examine the system performance, we first derive the outage probability (OP) expression utilizing the Gauss–Hermite quadrature for different shadowing and fading channel combinations. In addition, the system throughput and energy efficiency expressions are obtained for both shadowed and un-shadowed channels and verified through Monte Carlo simulations. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

In cooperative communication, relay reduces the stored energy for its own transmission due to the energy consumption for forwarding the information from source node. In this paper, simultaneous wireless information and power transfer (SWIPT) for OFDM-based cooperative communication is proposed to save the relay's energy by harvesting the radio frequency (RF) energy from source node. Subcarrier allocation based SWIPT (SA-SWIPT) is designed to use different subcarrier sets for information decoding and energy harvesting. In the first phase, the relay uses the SA-SWIPT to receive information and energy from source node. And in the second phase, the relay forwards the information both from source node and itself to the destinations using the energy collected from source node. The transmission rates of the relay in DF and AF modes are maximized by jointly optimizing subcarrier allocations and subcarrier powers, respectively, while ensuring the required transmission rate of source node and the energy supply of relay. An efficient iterative optimization algorithm is proposed to solve the proposed optimization problem through Lagrangian dual decomposition. Simulation results show the convergence of the optimization algorithm after very few iterations and explains the potential benefits for using SA-SWIPT in the OFDM-based cooperative communication. [ABSTRACT FROM AUTHOR]