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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. [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]

Recently, with the development of nanotechnology and the emergence of new materials, Wireless Nanosensor Networks (WNSNs) have been presented. To address the problems of link instability in WNSNs and poor adaptability of the EBCNF framework to network topology changes, a reliable multi-path routing based on link stability called RMRLS is proposed. Based on the EBCNF framework, this protocol introduces a path similarity judgment model to judge the similarity between paths. In the route establishment process, the link stability evaluation model is used to measure the stability of each path and as a criterion for path selection. Then alternative route is selected through the routing similarity judgment model. Optimal path and backup path are two routing paths to cope with changes in the network topology. The simulation results show that the RMRLS protocol has advantages in energy efficiency, data packet transmission success rate and average throughput, which are 28.84% lower, 53.8% higher, and more than double compared to EBCNF at a distance of 10 mm, respectively. These findings proved the RMRLS protocol's capacity to significantly boost the stability and reliability of the network. [ABSTRACT FROM AUTHOR]

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]

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. [ABSTRACT FROM AUTHOR]

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.

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]

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]

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.

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. [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]

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]

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.

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]

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.

In this paper, we propose a novel energy-efficient resource optimization scheme in non-orthogonal multiple access (NOMA) networks with simultaneous wireless information and power transfer (SWIPT). In this system, we consider practical imperfect channel information that accounts for random channel delays and channel estimation errors. Additionally, the small cell users (SCUs) in a heterogeneous network (HetNet) can harvest energy from the small base station (SBS) signal by energy harvesting. Based on the non-linear energy harvesting (NEH) model, the problem of maximizing energy efficiency with imperfect channel state information (CSI) is formulated. Since the formulated problem is a probabilistic mixed non-convex optimization problem, a two-stage algorithm is developed to jointly optimize sub-channel matching and power allocation. In particular, the problem is first transformed into a non-probabilistic problem through the relaxation method. For the sub-channels matching problem, a low-complexity many-to-many matching algorithm is designed to achieve dynamic matching based on the preference lists. For the power allocation problem, the closed-form transmission power of SCUs can be derived by the Dinkelbach method and Lagrangian dual approach. Simulation results show that the proposed scheme can achieve higher energy efficiency than existing linear energy harvesting (LEH)-NOMA and NEH-OFDMA schemes, with improvements of 37.99 % and 84.69 % , respectively. [ABSTRACT FROM AUTHOR]

The development of nanotechnology and the emergence of new materials such as graphene make wireless nanosensor networks (WNSN) based on electromagnetic communication possible. Due to the energy, computing power and transmission distance carried by nano-nodes are extremely limited, nanonetworks are usually ultra-dense, so nanonetworks are usually cluster-managed. Aiming at the problem of data transmission failure caused by poor link quality or insufficient energy in inter-cluster transmission, a relay node selection algorithm (RNS-AHP) based on simultaneous wireless information and power transfer (SWIPT) and analytics hierarchy process (AHP) is proposed. The algorithm is based on the SWIPT cooperative communication model, and uses the AHP to calculate the weights of four factors: the distance of the relay node, the channel capacity, the remaining energy of the relay node and the signal-to-noise ratio of the relay node receiver in the process of relay node selection. According to the weight, the weight of the candidate relay node is obtained as the selection criterion of the relay node. The simulation results show that the RNS-AHP algorithm can improve the average throughput, the success rate of data packet transmission and the energy efficiency. [ABSTRACT FROM AUTHOR]

In this study, we examine the performance of simultaneous wireless information and power transfer (SWIPT)-enabled two-way amplify-and-forward relay networks operating over κ − μ distributed channels. We adopt a three-node wireless communication system in which two source nodes communicate with one another in half-duplex mode through a battery-enabled relay node. In order to facilitate simultaneous energy harvesting through the radio-frequency signals and information transmission activities at the relay node, we use a time switching (TS) technique. At the destination nodes, the selection-combining technique is applied to utilize the two intended signals received through both direct and relay links. We obtain analytical expressions for the cumulative distribution function (CDF) and moment-generating function (MGF) in the system under study. We derive expressions for the outage probability (OP) and average symbol error rate (ASER) for a general-order coherent rectangular quadrature amplitude modulation scheme using the derived CDF expression. Additionally, we investigate the ASER for non-coherent modulation schemes using the derived MGF expression. The system's diversity order is examined by employing the asymptotic OP. We also emphasize the impact of the TS factor, energy conversion efficiency, and fading characteristics on the investigated network. To validate the analytical expressions, we perform Monte-Carlo simulations. [ABSTRACT FROM AUTHOR]

In scenarios where traditional ground base stations (BS) are unavailable, Unmanned Aerial Vehicles (UAVs) serve as aerial BS for enabling Internet of Things (IoT) communications. This paper introduces a UAV-based downlink communication model, specifically designed to address the challenge of UAVs' limited energy resources. Our approach innovatively employs simultaneous wireless information and power transfer (SWIPT) technology, enabling the UAV to concurrently transmit information and energy to IoT devices, a crucial capability in remote or emergency areas. The core of our contribution lies in the meticulous optimization of the UAV trajectory, power splitting (PS) ratio, and communication scheduling. These optimizations are vital for maximizing energy efficiency (EE), thereby reducing the energy consumption of the UAV while ensuring high-quality communication services. The dual objectives of amplifying EE and curtailing flight time are integrated into our model, conventional solution methods fall short in addressing this non-convex optimization problem, compounded by the complexities of UAV trajectory, PS ratio, and scheduling constraints. To overcome these challenges, we reformulate the problem as a Markov Decision Process (MDP). We then leverage the powerful reward maximization capabilities of deep reinforcement learning (DRL) to enable the UAV to take optimal, energy-efficient actions in each time slot. Our simulation results are promising, indicating that the DRL algorithm effectively optimizes the UAV trajectory and significantly enhances EE. The outcomes of our research reveal a marked improvement in UAV EE along the optimized trajectory, outperforming several alternative trajectories. Furthermore, we demonstrate that a dynamic PS ratio is more effective than a fixed ratio, highlighting the superiority of our approach. This synergy of trajectory optimization and adaptive PS ratio adjustment represents a significant advancement in efficient, sustainable UAV-enabled IoT communication, particularly under challenging conditions where conventional communication infrastructures are lacking. [ABSTRACT FROM AUTHOR]