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Summary: Radio frequency (RF) energy harvesting (EH) for wireless networks provides a green and sustainable solution and offers an energy‐efficient system. It is most crucial for fulfilling the power requirement of the rising number of low‐powered wireless devices and achieving sustainable development goals (SDG). It ensures the longevity of devices in the network even at inaccessible remote locations. Such RF‐EH‐based mechanisms are utilized in simultaneous wireless information and power transfer (SWIPT) systems. Most of the prevailing studies have analyzed the SWIPT system over conventional fading channels. However, due to the higher rate requirements, the current paradigm shift in frequency usage shifts towards the GHz band, which also offers better EH efficiency. Hence, SWIPT system analysis over the channel that is suitable for mm‐wave signal propagation is dealt with in this study. This study evaluates SWIPT performance over fluctuating two‐ray (FTR) fading channel that is crucial since it provides the best fit for characterizing GHz signal and also provides a generalized framework for most of the conventional fading channels. This study presents new analytical results assuming time switch relaying (TSR) protocol with (i) amplify and forward (AF) and (ii) decode and forward (DF) relaying. The results are also analyzed for H branches maximal ratio combining (MRC) diversity technique and evaluated the diversity gain for both AF and DF relays. The effectiveness of the system is measured in terms of system outage probability (SOP) to envisage the reliability of SWIPT based system. This work presents the simulation and modeling of such system and its obtained results are validated by Monte Carlo simulations for their accuracy. [ABSTRACT FROM AUTHOR]

With the development of wireless communication technology, the number of devices accessing the communication network is increasing. This paper addresses critical issues such as low spectrum resource utilization and the energy constraints of devices. The investigation focuses on the system performance of the shared relay Cognitive Radio Non-Orthogonal Multiple Access (CR-NOMA) network based on Simultaneous Wireless Information and Power Transfer (SWIPT) network model. Unlike the existing CR-NOMA model in which the secondary network user do not participate in the transmission of information from the primary network, we consider the secondary network near user as shared relay. The shared relay utilizes SWIPT technology to harvest energy using a nonlinear energy harvesting model. Additionally, the shared relay assists in transmitting information from the primary network base station to primary user, as well as from the secondary network base station to far user of the secondary network. Subsequently, we conduct a series of simulations to analyze the effects of Signal-to-Noise Ratio (SNR), power distribution factor, interference threshold, and time-switching (TS) factor on system performance. Furthermore, we compare and analyze the performance of our proposed network model against CR-NOMA network across three dimensions: outage probability, throughput, and energy efficiency. Our results demonstrate that the proposed network model exhibits superior outage performance and enhances user throughput compared to the CR-NOMA network. Additionally, it demonstrates improved energy efficiency compared to the shared relay CR-NOMA network, leading to an overall improvement in network performance. [ABSTRACT FROM AUTHOR]

The article addresses the energy consumption minimization problem in wireless powered communication networks (WPCNs) and proposes a time allocation scheme, named DaTA, which is based on the Different Target Simultaneous Wireless Information and Power Transfer (DT-SWIPT) scheme such that the wireless station can share the remaining energy after transmission to the Hybrid Access Point (HAP) to those who have not transmitted to the HAP to minimize the energy consumption of the WPCN. In addition to proposing a new frame structure, the article also considers the Signal-to-Noise (SNR) constraint to guarantee that the HAP can successfully receive data from wireless stations. In the article, the problem of minimization of energy consumption is formulated as a nonlinear programming model. We employ the SQP (Sequential Quadratic Programming) algorithm to figure out the optimal solution. Moreover, a heuristic method is proposed as well to obtain a near-optimal solution in a shorter time. The simulation results showed that the proposed scheme outperforms the related work in terms of energy consumption and energy efficiency. [ABSTRACT FROM AUTHOR]

Abstract With the development of wireless communication technology, the number of devices accessing the communication network is increasing. This paper addresses critical issues such as low spectrum resource utilization and the energy constraints of devices. The investigation focuses on the system performance of the shared relay Cognitive Radio Non-Orthogonal Multiple Access (CR-NOMA) network based on Simultaneous Wireless Information and Power Transfer (SWIPT) network model. Unlike the existing CR-NOMA model in which the secondary network user do not participate in the transmission of information from the primary network, we consider the secondary network near user as shared relay. The shared relay utilizes SWIPT technology to harvest energy using a nonlinear energy harvesting model. Additionally, the shared relay assists in transmitting information from the primary network base station to primary user, as well as from the secondary network base station to far user of the secondary network. Subsequently, we conduct a series of simulations to analyze the effects of Signal-to-Noise Ratio (SNR), power distribution factor, interference threshold, and time-switching (TS) factor on system performance. Furthermore, we compare and analyze the performance of our proposed network model against CR-NOMA network across three dimensions: outage probability, throughput, and energy efficiency. Our results demonstrate that the proposed network model exhibits superior outage performance and enhances user throughput compared to the CR-NOMA network. Additionally, it demonstrates improved energy efficiency compared to the shared relay CR-NOMA network, leading to an overall improvement in network performance.

Over the past decade, there has been notable attention directed towards spectrum and energy efficiency in conjunction with simultaneous wireless information and power transfer (SWIPT), aimed at extending the operational lifespan of energy-constrained wireless devices within cooperative non-orthogonal multiple access (C-NOMA) systems. This article delves into a system model comprising a transmitter, a relay, and two users, where the time-switching receiver (TSR) protocol is employed for energy harvesting at the relay. The objective of this study is to evaluate the performance of the system in terms of outage probability (OP), and system throughput (ST), and to determine the optimal time-switching (TS) factor. Our analysis encompasses the evaluation of OP, ST, and the determination of the optimal TS factor. Numerical simulation results reveal that the Nakagami-m fading channel exhibits the lowest outage probability, and that system throughput escalates with the signal-to-noise ratio (SNR) augmentation. These findings underscore the potential of the Nakagami-m fading channel to enhance energy efficiency in C-NOMA systems and suggest promising directions for future research. [ABSTRACT FROM AUTHOR]

Next-generation communication systems demand the integration of sensing, communication, and power transfer (PT) capabilities, requiring high spectral efficiency, energy efficiency, and low cost while also necessitating robustness in high-speed scenarios. Integrated sensing and communication systems (ISACSs) exhibit the ability to simultaneously perform communication and sensing tasks using a single RF signal, while simultaneous wireless information and power transfer (SWIPT) systems can handle simultaneous information and energy transmission, and orthogonal time frequency space (OTFS) signals are adept at handling high Doppler scenarios. Combining the advantages of these three technologies, a novel cyclic prefix (CP) OTFS-based integrated simultaneous wireless sensing, communication, and power transfer system (ISWSCPTS) framework is proposed in this work. Within the ISWSCPTS, the CP-OTFS matched filter (MF)-based target detection and parameter estimation (MF-TDaPE) algorithm is proposed to endow the system with sensing capabilities. To enhance the system's sensing capability, a waveform design algorithm based on CP-OTFS ambiguity function shaping (AFS) is proposed, which is solved by an iterative method. Furthermore, to maximize the system's sensing performance under communication and PT quality of service (QoS) constraints, a semidefinite relaxation (SDR) beamforming design (SDR-BD) algorithm is proposed, which is solved using through the SDR technique. The simulation results demonstrate that the ISWSCPTS exhibits stronger parameter estimation performance in high-speed scenarios compared to orthogonal frequency division multiplexing (OFDM), the waveform designed by CP-OTFS AFS demonstrates superior interference resilience, and the beamforming designed by SDR-BD strikes a balance in the overall performance of the ISWSCPTS. [ABSTRACT FROM AUTHOR]

Most of the existing works for simultaneous wireless information and power transfer (SWIPT) focus on the robust designs via numerical approaches under the Gaussian input assumption or on the information–theoretic rate–energy tradeoff with perfect transmitter channel state information (CSIT). In contrast, this study, from an error performance perspective, investigates the optimal finite-alphabet signal structures and reveals the influence of CSIT uncertainty on the finite-alphabet rate and energy harvesting in multi-input single-output multicasting (MSM) SWIPT. To this end, we first utilize CSIT with any bounded uncertainty to establish a constellation-optimal space–time (COST) structure optimizing the worst-case minimum Euclidean distance among all the feasible sets for any given power splitting of all users under energy-harvesting constraints. The COST structure is proved to be rank-one with a multidimensional optimal constellation over ideal additive white Gaussian noise (AWGN) channels (OCIA) with a worst-case optimized beamformer within the CSIT uncertainty. Then, for the case without CSIT, Alamouti transmission of 2D OCIA is proved to be the COST structure for a two-antenna MSM-SWIPT. We further show that the above two COSTs reveal an unreported fundamental tradeoff for MSM-SWIPT among finite-alphabet rate, energy harvesting and uncertainty of CSIT. The tradeoff comparison for different levels of sphere-bounded CSIT uncertainty indicates that there exists a feasibility region where imperfect CSIT can be very helpful for enhancing the system performance of MSM-SWIPT. The observations obtained in this paper provide useful insights into the fundamental finite-alphabet structures and tradeoff in SWIPT systems. [ABSTRACT FROM AUTHOR]

This study investigates the performance of cooperative relaying-based non-orthogonal multiple access (NOMA) with simultaneous wireless information and power transfer. Assuming the batteryassisted non-linear energy harvesting (NL-EH) in which the near user (NU) works as a relay for the far user (FU) to convey data from the base station (BS); two scenarios are examined: (1) No direct link (NDL) between the BS and the FU, and (2) direct link (DL) between the BS and the FU. The DL at the FU is evaluated in two scenarios: as an optimal combination to the signal from the NU and as an interfering link to the signal from the NU. Considering the power splitting relaying (PSR) protocol with an NL-EH model and assuming imperfect successive interference cancellation (i-SIC) at the NU, we derive closed-form expressions for the NU and FU outage probability and throughput. The throughput of the FU is greatly increased by supplementing the harvested energy with a small quantity of battery energy. Furthermore, an optimal combination of the FU signals relayed from the BS and the NU considerably improves the throughput of the FU. It reduces the energy consumption at the battery compared to the scenario when there is NDL. We obtain the diversity order by deriving high signal-to-noise ratio approximations for the NU and FU outage probability in NDL and DL scenarios. Unlike linear energy harvesting, we show NL-EH leads to a loss of diversity, making it even more important to use the DL. We have formulated an equation to measure energy efficiency using the derived throughput expressions for the NDL and DL scenarios. We have also shown that selecting the optimal combination of battery energy and PS parameter is essential to achieve the highest possible throughput and energy efficiency. The residual interference generated by i-SIC significantly impacts the outage probability of the NU while having a negligible effect on the performance of the FU. Moreover, we have discovered that performance deteriorates when interference from the DL is present. We explain how the system’s performance is affected by the selection of energy harvesting parameter, power allocation coefficient, saturation threshold, self-loop interference, variable node distances and battery energy. Monte Carlo simulations have verified the accuracy of the resulting expressions.

This paper considers the interference of imperfect successive interference cancellation operation and hardware noise in the joint transmission of coordinated multipoint cooperative non-orthogonal multiple access (NOMA) networks. Presumably, the statement is that distant user (cell-edge user) and base stations have no direct contacts. According to NOMA, each base station gives the information about the distant user and the near user to the cell center user (Near user), who then decodes the information of both users using the energy acquired by simultaneous wireless information and power transfer and passes it on to the cell edge user. To evaluate the performance of the suggested system, each user’s closed-form formula is represented in terms of outage probability. The findings indicate that the involvement of residual hardware impairments (RHIs) and imperfect successive interference cancellation (ipSIC) has led to an erroneous floor in the outage probability. It has been observed that ipSIC, RHIs, and both have a considerable detrimental effect on system performance. The analytical findings are verified using Monte Carlo simulations.

This work investigates the energy-outage performance of aerial unmanned aerial vehicles (UAV)-enabled simultaneous wireless information and power transfer (SWIPT) deployments. Focus on the energy preservation challenges for battery-powered UAVs to maintain hovering in the sky, we propose two energy-based antenna approaches, including energy-based single antenna selection (ESAS) and energy-based maximal antenna transmission (EMAT), to improve the energy-outage probability (EOP). In order to evaluate EOP, we derive closed-form approximations for two proposed ESAS and EMAT schemes as well as the asymptotic EOP formulations. In addition, we deduce the system diversity gain, the performance gap between the two proposed schemes, and guidelines for some useful information in system designs. Moreover, we also carry out an optimization of aerial UAV position to minimize the EOP when dealing with certain service areas. Through the Monte-Carlo method, extensive numerical results show that: 1) Simulation results align well with our analytical approximations; 2) For achieving the same EOP requirement, the use of EMAT consumes less than 3 dB of the transmit power compared to ESAS; 3) Compared to ESAS, the adoption of EMAT with more than four antennas at the UAV supply and aerial hovering UAV nodes reduced EOP by more than 100 times; 4) The considered SWIPT-PS mechanism results in a 10 times better EOP improvement than the SWIPT-TS one; and 5) Optimizing the position of aerial hovering UAVs lead to the EOP minimization significantly.

This paper proposes the joint use of caching and simultaneous wireless information and power transfer (SWIPT) to enhance the performance of cell-edge users of down-uplink simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS)-empowered non-orthogonal multiple access (NOMA) systems. The main idea is to leverage the available caching at nearby users to establish cooperative communication while taking into account the problem of energy issues through SWIPT mechanisms, namely time-switching (TS) and power-splitting (PS) strategies. To improve the communication quality of users, STAR-RIS with an energy-splitting (ES) protocol is established and phase-shift design is formulated. Closed-form approximations and asymptotic expressions for users’ outage probability (OP) and effective ergodic capacity (EC) are derived. Based on the attained expressions, useful insights into system design, such as the impact of power allocation, imperfect successive interference cancellation, the number of transmit/reflect components on the system performance, trade-offs between the network requirement and the system performance, and trade-offs between the energy harvesting process and data transmission quality, are deduced. Numerical examples verify our derivations and show that: i) the performance of cell-edge users is improved significantly; ii) exploiting SWIPT-PS shows better OP and EC performance for nearby users compared to SWIPT-TS, while both provide comparable performance for cooperative communication; iii) as the performance of cell-edge users is mostly guaranteed, the communication quality of nearby users in downlink and source node in uplink can be improved by optimizing either the power budget or the energy harvesting factors; iv) adopting STAR-RIS with ES protocol outperforms mode-switching and time-splitting ones in terms of both OP and EC; and v) STAR-RIS-empowered NOMA has better EC performance than orthogonal-multiple access counterparts when SIC operation is properly designed.

The article addresses the energy consumption minimization problem in wireless powered communication networks (WPCNs) and proposes a time allocation scheme, named DaTA, which is based on the Different Target Simultaneous Wireless Information and Power Transfer (DT-SWIPT) scheme such that the wireless station can share the remaining energy after transmission to the Hybrid Access Point (HAP) to those who have not transmitted to the HAP to minimize the energy consumption of the WPCN. In addition to proposing a new frame structure, the article also considers the Signal-to-Noise (SNR) constraint to guarantee that the HAP can successfully receive data from wireless stations. In the article, the problem of minimization of energy consumption is formulated as a nonlinear programming model. We employ the SQP (Sequential Quadratic Programming) algorithm to figure out the optimal solution. Moreover, a heuristic method is proposed as well to obtain a near-optimal solution in a shorter time. The simulation results showed that the proposed scheme outperforms the related work in terms of energy consumption and energy efficiency.

Wireless energy and information transfer have been effectively employed to facilitate reliable operation and communication among sensor nodes of wireless body area networks (WBANs). This work, therefore, presents the recent advances related to wireless power transfer (WPT)/simultaneous wireless information and power transfer (SWIPT) applied in WBAN composed of on-/in-body sensors for healthcare monitoring. A comprehensive overview of WPT/SWIPT-enabled WBANs was provided by characterizing them regarding the system requirements, network architecture, device design, and channel modeling. Considering the system requirements, optimization and performance analysis are identified as major tools to enhance and quantify the system's efficiency. Given the power scarcity issue, it is also imperative to ensure robust, user-friendly, and long-term WBAN operation; accordingly, existing battery-assisted and battery-free device designs are discussed. Furthermore, different network topologies, varying from single-input-single-output to multiple-input-multiple-output, are required to maintain WBAN applications. Therefore, this survey includes the network architecture as an important classification category requiring close attention. Additionally, understanding propagation models is indispensable to building competent WBAN. This review describes channel modeling from the perspective of stochastic and deterministic environments. In summary, this paper aims to serve as a comprehensive reference, providing readers with an insightful exploration of WPT/SWIPT-enabled WBANs, addressing their both advantages and limitations. [ABSTRACT FROM AUTHOR]

Over the past decade, there has been notable attention directed towards spectrum and energy efficiency in conjunction with simultaneous wireless information and power transfer (SWIPT), aimed at extending the operational lifespan of energy-constrained wireless devices within cooperative non-orthogonal multiple access (C-NOMA) systems. This article delves into a system model comprising a transmitter, a relay, and two users, where the time-switching receiver (TSR) protocol is employed for energy harvesting at the relay. The objective of this study is to evaluate the performance of the system in terms of outage probability (OP), and system throughput (ST), and to determine the optimal time-switching (TS) factor. Our analysis encompasses the evaluation of OP, ST, and the determination of the optimal TS factor. Numerical simulation results reveal that the Nakagami-m fading channel exhibits the lowest outage probability, and that system throughput escalates with the signal-to-noise ratio (SNR) augmentation. These findings underscore the potential of the Nakagami-m fading channel to enhance energy efficiency in C-NOMA systems and suggest promising directions for future research.

Next-generation communication systems demand the integration of sensing, communication, and power transfer (PT) capabilities, requiring high spectral efficiency, energy efficiency, and low cost while also necessitating robustness in high-speed scenarios. Integrated sensing and communication systems (ISACSs) exhibit the ability to simultaneously perform communication and sensing tasks using a single RF signal, while simultaneous wireless information and power transfer (SWIPT) systems can handle simultaneous information and energy transmission, and orthogonal time frequency space (OTFS) signals are adept at handling high Doppler scenarios. Combining the advantages of these three technologies, a novel cyclic prefix (CP) OTFS-based integrated simultaneous wireless sensing, communication, and power transfer system (ISWSCPTS) framework is proposed in this work. Within the ISWSCPTS, the CP-OTFS matched filter (MF)-based target detection and parameter estimation (MF-TDaPE) algorithm is proposed to endow the system with sensing capabilities. To enhance the system’s sensing capability, a waveform design algorithm based on CP-OTFS ambiguity function shaping (AFS) is proposed, which is solved by an iterative method. Furthermore, to maximize the system’s sensing performance under communication and PT quality of service (QoS) constraints, a semidefinite relaxation (SDR) beamforming design (SDR-BD) algorithm is proposed, which is solved using through the SDR technique. The simulation results demonstrate that the ISWSCPTS exhibits stronger parameter estimation performance in high-speed scenarios compared to orthogonal frequency division multiplexing (OFDM), the waveform designed by CP-OTFS AFS demonstrates superior interference resilience, and the beamforming designed by SDR-BD strikes a balance in the overall performance of the ISWSCPTS.

In this letter, we establish physical-layer security based on frequency diverse array (FDA) together with directional modulation (DM) for decode and forward (DF) relaying simultaneous wireless information and power transfer (SWIPT) system. The analytical expressions of the ergodic system secrecy capacity under the time switching (TS) protocol are derived. Moreover, the impacts of system parameters on secure performance are analysed. Numerical results reveal that the proposed method achieves better security performance than conventional PA solutions, especially in the range dimension. [ABSTRACT FROM AUTHOR]

Energy harvesting (EH) by power constrained nodes in simultaneous wireless information and power transfer (SWIPT) system have recently attracted a considerable research interest. However, most of the researches have investigated SWIPT in static scenario over the conventional fading channels. Analyzing SWIPT over a channel that is suitable for mmWave communications forms the key to the success of 5G and beyond technologies. Concerning to another major challenge for high-frequency communication is the high amount of fading losses leading to reduced cell size. In such, small cell scenario the impact of node mobility becomes significant and hence needs to be accounted for accurate analysis. Thus, in this paper we analyzed the cooperative SWIPT system over fluctuating two ray (FTR) fading channels that can accurately characterize fluctuations at GHz range. Additionally, we have integrated the random waypoint (RWP) mobility model to characterize the random mobility pattern of both user and relay node. We have introduced a RV parameter to quantify the impact of variable terms influenced by mobility like link distance, signal to noise ratio (SNR) and path-loss exponent. We derived the cumulative distribution function and probability density function in the form of easy tractable gamma function. Further, we derived the ergodic outage probability (EOP) for the SWIPT system for decode-and-forward (DF) and amplify-and-forward (AF) relaying protocols considering 1D, 2D and 3D topologies. The analytical results are compared with Monte–Carlo simulations to validate the analysis. [ABSTRACT FROM AUTHOR]

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This article investigates reinforcement learning (RL)-based solutions for optimizing resource allocations in simultaneous lightwave information and power transfer (SLIPT) under practical indoor mobility. Encountering the challenges of excessive outages and intermittent channels posed by practical mobility, the reinforcer for agent training is endowed with the tradeoff between energy efficiency and communication quality. Accordingly, two typical RL categories, i.e., value-based tabular RL and policy gradient-based deep RL are imposed and compared through several numerical examinations regarding information-power transfer balance, generalization ability, and complexity. The vanilla tabular RL is demonstrated to outperform the gradient-based deep RL and should be prioritized in practice if feasible.

We propose a novel interference alignment (IA) technique with receive antenna partitioning (RAP) for simultaneous wireless information and power transfer (SWIPT)-enabled downlink fog radio access networks (F-RANs). The basic idea of the proposed scheme is to apply a generalized downlink IA for each access point (AP) and to divide receive antennas at each user into two groups for information decoding (ID) and energy harvesting (EH), respectively. With the proposed scheme, an optimal receive antenna configuration at each user is obtained to maximize the weighted sum of achievable rate and the sum of harvested energy of the network. Also we develop an antenna configuration selection algorithm to obtain near-optimal performance with low computational complexity. Through extensive computer simulations, it is shown that the proposed scheme significantly improves a rate-energy region compared with existing techniques.

In this paper, we consider a power splitting (PS)-based simultaneous wireless information and power transfer (SWIPT) system, which is having I and Q (in-phase and quadrature) imbalance hardware impairment. The prime objective of this paper is to maximize the harvested energy for a SWIPT PS system, satisfying a minimum signal to noise ratio (SNR) requirement for information signal processing in the presence of IQ imbalance hardware impairment. The paper uses four types of bio-inspired algorithms like Particle Swarm Optimisation, Artificial Bee Colony, Firefly Algorithm and Invasive Weed Optimisation to attain the maximum harvested energy considering parameters of PS ratio, amplitude and phase imbalances in a Rayleigh fading environment. The simulation results show that under ideal power conversion efficiency and minimum hardware impairments, a maximum SNR of 16.7 dB and harvested energy of 11 dB is achieved for a transmit power of 20 dB in SWIPT systems for IWO bio-inspired algorithms in the 32 QAM modulation scheme. [ABSTRACT FROM AUTHOR]

The outage performance of the cognitive relay networks is analyzed based on simultaneous wireless information and power transfer (SWIPT) and non-orthogonal multiple access (NOMA). The analytical expressions of overall outage probability and asymptotic expressions on high signal-to-noise ratio (SNR) are derived for the direct link transmission mode and the two-stage communication transmission mode. The analytical expressions are validated by Monte-Carlo simulations. The simulation results demonstrate that the outage performance is improved by through the direct link transmission. Furthermore, compared with the conventional cognitive relay networks with orthogonal multiple access (OMA), superior outage performance and high energy efficiency are achieved for the cognitive relay networks based on SWIPT-NOMA. [ABSTRACT FROM AUTHOR]

The outage performance of the cognitive relay networks is analyzed based on simultaneous wireless information and power transfer (SWIPT) and non-orthogonal multiple access (NOMA). The analytical expressions of overall outage probability and asymptotic expressions on high signal-to-noise ratio (SNR) are derived for the direct link transmission mode and the two-stage communication transmission mode. The analytical expressions are validated by Monte-Carlo simulations. The simulation results demonstrate that the outage performance is improved by through the direct link transmission. Furthermore, compared with the conventional cognitive relay networks with orthogonal multiple access (OMA), superior outage performance and high energy efficiency are achieved for the cognitive relay networks based on SWIPT-NOMA. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicle (UAV)-assisted simultaneous wireless information and power transfer (SWIPT) systems have recently gained significant attraction in internet-of-things (IoT) applications that have limited or no infrastructure. Specifically, the free mobility of UAVs in three-dimensional (3D) space allows us good-quality channel links, thereby enhancing the communication environment and improving performance in terms of achievable rates, latency, and energy efficiency. Meanwhile, IoT devices can extend their battery life by harvesting the energy following the SWIPT protocol, which leads to an increase in the overall system lifespan. In this paper, we propose a secure UAV-assisted SWIPT system designed to optimize the secrecy energy efficiency (SEE) of a ground network, wherein a base station (BS) transmits confidential messages to an energy-constrained device in the presence of a passive eavesdropper. Here, we employ a UAV acting as a helper node to improve the SEE of the system and to aid in the energy harvesting (EH) of the battery-limited ground device following the SWIPT protocol. To this end, we formulate the SEE maximization problem by jointly optimizing the transmit powers of the BS and UAV, the power-splitting ratio for EH operations, and the UAV’s flight path. The solution is obtained via a proposed algorithm that leverages successive convex approximation (SCA) and Dinkelbach’s method. Through simulations, we corroborate the feasibility and effectiveness of the proposed algorithm compared to conventional partial optimization approaches.

Activating Wireless Power Transfer (WPT) in Radio-Frequency (RF) to provide on-demand energy supply to widely deployed Internet of Everything devices is a key to the next-generation energy self-sustainable 6G network. However, Simultaneous Wireless Information and Power Transfer (SWIPT) in the same RF bands is challenging. The majority of previous studies compared SWIPT performance to Gaussian signaling with an infinite alphabet, which is impossible to implement in any realistic communication system. In contrast, we study the SWIPT system in a well-known Nakagami-m wireless fading channel using practical modulation techniques with finite alphabet. The attainable rate-energy-reliability tradeoff and the corresponding rationale are revealed for fixed modulation schemes. Furthermore, an adaptive modulation-based transceiver is provided for further expanding the attainable rate-energy-reliability region based on various SWIPT performances of different modulation schemes. The modulation switching thresholds and transmit power allocation at the SWIPT transmitter and the power splitting ratios at the SWIPT receiver are jointly optimized to maximize the attainable spectrum efficiency of wireless information transfer while satisfying the WPT requirement and the instantaneous and average BER constraints. Numerical results demonstrate the SWIPT performance of various fixed modulation schemes in different fading conditions. The advantage of the adaptive modulation-based SWIPT transceiver is validated.

In this paper, we investigate the trust-degree-based secure relay selection in simultaneous wireless information and power transfer (SWIPT)-enabled relay networks. In particular, we optimize the interference power by selecting the appropriate relay and time division ratio on the condition of both the secure transmission and trust degree. First, by applying the security capacity constraint, we derive the expressions of the time division ratio and relay interference power concerning the trust degree. Then, we discuss the different results for different trust degrees and determine the set of trust degrees to guarantee secure communications. Finally, according to the different trust degrees, we compute the needed interference power for each relay and make a selection to obtain the optimal performance under relay networks. Simulation results show that with the known trust degree the proposed algorithm obtains the appropriate relay and time division ratio, reduces energy consumption, and guarantees an achievable security rate. [ABSTRACT FROM AUTHOR]

Summary: FSO links have attracted a significant amount of interest in the recent years driven by the paramount importance of their license‐free spectrum and ease of deployment in wireless networks. Besides, the energy harvesting (EH) paradigm allows recharging terminals via ambient and/or external sources and prolongs battery lifetime operation. Thereby, facilitating free space optical (FSO) in EH networks creates potential scenarios for the future sixth‐generation (6G) communication systems. In this study, an EH system performing simultaneous wireless information and power transfer (SWIPT) while adopting FSO and resonant beam charging (RBC), RBC–SWIPT system is thoroughly analyzed. The performance of RBC‐SWIPT system is analyzed through Monte Carlo simulations, where average bit error ratio (ABER) and energy efficiency (EE) are studied and evaluated. In addition, channel capacity is derived along with the mutual information and studied over indoor line of sight (LOS) optical channel. Monte Carlo simulation results corroborate the accuracy of the derived formulas. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Data Acquisition & Processing / Shu Ju Cai Ji Yu Chu Li is the property of Editorial Department of Journal of Nanjing University of Aeronautics & Astronautics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Non-orthogonal multiple access (NOMA) and simultaneous wireless information and power transfer (SWIPT) have emerged as two promising techniques to achieve high spectrum efficiency and energy efficiency, respectively. This paper introduces an energy-efficient resource allocation algorithm for heterogeneous SWIPT-NOMA systems. Considering the minimum rate requirements of users, energy harvesting, and transmission power of heterogeneous radio access technologies, we present a hybrid resource allocation framework for maximizing energy efficiency performance jointly with power and time scheduling management. Due to the non-linear and non-convex issues, we utilize Dinkelbach and Lagrangian Duality theory to obtain the global optimal solution. Simulation results show that the proposed energy-efficiency resource allocation algorithm can improve the energy efficiency performance compared with the other existing schemes.

In this work, we investigate the performance of a reconfigurable intelligent surface (RIS)-aided multi-user simultaneous wireless information and power transfer (SWIPT) network, where a multiple-input multiple-output (MIMO) base station (BS) serves multiple MIMO information receivers (IRs) while ensuring a minimum harvested power at multiple MIMO energy receivers (ERs). In order to improve the energy efficiency (EE) of the network, we consider a pricing-based performance metric called network utility. We then establish an optimization framework to jointly optimize the transmit precoding matrix (TPM) and phase shift matrix (PSM) to maximize the network utility function with constraints on the available transmit power at BS, minimum harvested power required at each ER, and unit modulus phase shift condition at RIS. Due to the non-convex nature of this problem, we divide it into two sub-problems where a sub-optimal solution of TPM and PSM are obtained separately using successive convex approximation and bisection search-based algorithms. Further, we propose an EE maximization (EEM) algorithm based on the block coordinate descent method to achieve the optimal solution of the master problem by iteratively obtaining the sub-optimal TPM, PSM, and network price using their respective algorithms. Moreover, we also prove that the solution obtained for each problem using their respective algorithm converges to the Karush-Kuhn-Tucker (KKT) optimum point of that problem. We also show the efficacy of the proposed algorithm using simulation results. In particular, we highlight the importance of using RIS in a multi-user MIMO SWIPT network and demonstrate the effect of various parameters on the network’s EE performance.

In this article, we consider a multi-user multiple-input single-output underlay cognitive radio system with simultaneous wireless information and power transfer (SWIPT) based on the rate-splitting multiple access (RSMA) framework. The system model is composed of a set of secondary users that only decode information, and another set of secondary users that simultaneously decode information and harvest energy based on a power-splitting (PS) ratio. Precoders are designed to minimize the transmission power of the secondary transmitter subject to a minimum rate requirement, an energy harvesting requirement, and maximum allowable interference with the primary network. The optimization problem is non-convex and challenging. Thus, we divide it into two subproblems where the outer problem is solved by a deep neural network (DNN)-based scheme with an autoencoder, and the inner problem is solved based on the semidefinite relaxation (SDR) technique. The inner problem takes the solution of the DNN-based scheme to provide the precoder vectors and PS ratios based on SDR, where a penalty function is proposed to guarantee feasible solutions to the problems. Our simulation results prove that the proposed framework based on RSMA outperforms the conventional methods and can achieve performance close to that of the optimal solutions, with a significant reduction in computational complexity.

Mobile Edge Computing (MEC) technology and Simultaneous Wireless Information and Power Transfer (SWIPT) technology are important ones to improve the computing rate and the sustainability of devices in the Internet of things (IoT). However, the system models of most relevant papers only considered multi-terminal, excluding multi-server. Therefore, this paper aims at the scenario of IoT with multi-terminal, multi-server and multi-relay, in which can optimize the computing rate and computing cost by using deep reinforcement learning (DRL) algorithm. Firstly, the formulas of computing rate and computing cost in proposed scenario are derived. Secondly, by introducing the modified Actor-Critic (AC) algorithm and convex optimization algorithm, we get the offloading scheme and time allocation that maximize the computing rate. Finally, the selection scheme of minimizing the computing cost is obtained by AC algorithm. The simulation results verify the theoretical analysis. The algorithm proposed in this paper not only achieves a near-optimal computing rate and computing cost while significantly reducing the program execution delay, but also makes full use of the energy collected by the SWIPT technology to improve energy utilization. [ABSTRACT FROM AUTHOR]

This article proposes a simultaneous wireless information and power transfer (SWIPT)-enabled Internet of Things (IoT)-based cognitive nonorthogonal multiple access (NOMA) with coordinated direct and relay transmission (CDRT) system. It incorporates overlay cognitive radio (CR) and time switching (TS)-based SWIPT technology to enhance spectrum utilization and energy efficiency (EE). The proposed system comprises a primary network having a primary transmitter and its intended NOMA receivers (UE1 and UE2), accompanied by an energy-constrained secondary transmitter (ST) and its designated receiver (IoT-U). The primary transmitter communicates directly with its strong user UE1 and exploits the ST as an IoT relay to communicate with a weak user UE2. The IoT-relay node employs a TS-based receiver architecture and a decode-and-forward (DF) protocol to convey the weak user’s information along with its own information by following the NOMA principle. We evaluate the performance of the proposed system by considering both the perfect and imperfect successive interference cancellation (SIC) at the legitimate users over Nakagami- ${m}$ fading in terms of outage probability (OP), system throughput, and EE. Moreover, we propose an iterative algorithm to minimize the OP by optimizing the TS factor. Furthermore, the impact of key parameters is also highlighted, which lays the guidelines for the practical design of energy-efficient and spectrum-efficient futuristic wireless communication networks. [ABSTRACT FROM AUTHOR]

This paper presents an investigation of the transmitting power consumption of a base station (BS) in a simultaneous wireless information and power transfer (SWIPT) system enhanced by a reconfigurable intelligent surface (RIS). The aim is to optimize the total transmitting power consumption when sending information signals and energy from the BS to ground sensors. To this end, the transmitting power consumption of the BS is optimized by satisfying the sensor's minimum signal-to-interference-plus-noise ratio (SINR), the phase shift constraints of the RIS, and each sensor's power-splitting (PS) ratio. In order to decouple the optimization variables, we use the technique of block coordinate descent (BCD) to transform the total problem into subproblems. In the second subproblem, the unit modulus constraints are approximated using the successive convex approximation (SCA) method, allowing the optimal solutions to be obtained by solving subproblems in an iterative manner. Our numerical simulation results show that transmitting power consumption can be significantly decreased by adding RIS to an SPWIT system, even in nonlinear harvest models of real application scenarios. [ABSTRACT FROM AUTHOR]

In this article, a two-hop simultaneous wireless information and power transfer relay network using a decode-and-forward strategy is considered. In order to improve the spectral efficiency, the relay node performs in full-duplex (FD) mode, and each node is equipped with multiple antennas. First, the end-to-end achievable rate is formulated for FD and half-duplex (HD) modes under imperfect channel state information (ICSI). Then, the optimal closed-form expressions for power allocation at the source and relay, as well as the energy harvesting ratios, are derived for primal variables associated with the dual variables through analytical solutions. We propose an iterative primal-dual algorithm based on the ellipsoid method so as to obtain final answers. Numerical results demonstrate the FD achievable rate superiority over the HD mode under proper self-interference cancellation (SIC). According to the existing results, there is an immense discrepancy between the achievable rates in perfect CSI and ICSI cases. Also, the impact of the relay distance from the source node, the number of antennas, and different SIC modes are investigated on the end-to-end achievable rate. [ABSTRACT FROM AUTHOR]

In this article, we consider the millimeter-wave simultaneous wireless information and power transfer nonorthogonal multiple access (NOMA) relay networks in the presence of multiple passive eavesdroppers, where the near and far Internet of Things (IoT) devices with different communication requirements are served by one source with the help of the relays, and stochastic geometry is used to characterize the distribution of multiple nodes. First, a NOMA pairing and relay selection scheme is designed. Then, the closed-form expressions for the energy-information coverage probability (EICP) and the effective secrecy throughput of the near IoT devices are derived. Finally, the EICPs of the far IoT device under random relay selection and opportunistic relay selection schemes are obtained. Moreover, the asymptotic expressions of the EICP for both the near and far IoT devices are derived, which show that the asymptotic EICP when the number of antennas at the source or relay tends to infinity is only dependent on the location distribution of nodes and blockage environment. The simulation results show that NOMA can outperform orthogonal multiple access, and the advantage of the opportunistic relay selection scheme over the random relay selection scheme is more obvious when the density of the relay is relatively large. [ABSTRACT FROM AUTHOR]

In the Industrial Internet of Things (IIoT), non-orthogonal multiple access (NOMA) has emerged as a viable multiple access method due to its superior efficiency. In this paper, a new power allocation technique for NOMA-enabled IIoT devices is presented with trade-offs between increasing energy efficiency and decreasing power consumption. We present a joint optimization of transmission rate and energy harvesting in simultaneous wireless information and power transfer (SWIPT) NOMA-enabled IIoT devices. With the power splitting (PS) approach, we examine how to improve overall transmission rate and harvested energy, simultaneously, while fulfilling the minimum rate and harvested energy needs of each IIoT device in a SWIPT-enabled NOMA system. An objective function is established by adding transmission rates obtained from information decoding and the transformed throughput from energy harvesting. The combination of management approaches with Industry 4.0 technology provides a viable strategy to decrease industrial production's energy use. Several performance metrics may be utilized to study manufacturing process optimization. The efficiency of production equipment may be measured by looking at the overall effectiveness (OE) of the equipment in use. We divide the non-convex optimization problem into two sub-problems, based on the Lagrangian duality method, and solve them to find the optimal solution for the non-convex problem. The approach is validated based on physical layer parameter settings that represent potential factory of the future scenarios. Simulation results confirm the effectiveness of the presented method in a SWIPT-enabled NOMA system, provide considerable performance gains over the classic rate maximization strategy, and demonstrate the energy efficiency of the presented method compared with the conventional system. The results show huge potential of our solutions to reduce the future huge energy demand related to factory automation. [ABSTRACT FROM AUTHOR]

Wireless power transfer (WPT) technology has been widely used in industrial and household fields. This technology is of great significance in the field of motor drives. However, if the WPT technology is applied to the motor drive and control system, power and control signals need to be transmitted at the same time, which will cause the problem of mutual interference between signals of different frequencies, and will also increase the difficulty of frequency decomposition on the secondary side. To solve the above problems, a dual-frequency simultaneous wireless information and power transfer (SWIPT) system using a tapped coil structure scheme is proposed and the design principle of the tapped coil is given. Based on this scheme, a multi-frequency pulse width modulation (MFPWM) method is used to generate two components of different frequencies by the same inverter, which are automatically decoupled by the tapped coil, and finally transmitted to drive and control the motor. A closed-loop control strategy is used to solve the problem of precise motor speed control when the driving voltage of the wireless motor fluctuates. In the experiment, the motor speed increased from 1965 rpm to 2265 rpm, and the DC voltage corresponding to the set reference speed increased from 1.26 V to 2.30 V. The experimental results show that the scheme can control the BLDC motor speed stably and accurately. [ABSTRACT FROM AUTHOR]

In this paper, we investigate a two-hop simultaneous wireless information and power transfer (SWIPT) amplify-and-forward (AF) multiple-input multiple-output (MIMO) relay communication system with an energy-limited relay node. The relay node harvests energy based on the radio-frequency (RF) signal transmitted from the source node through the time-switching (TS) protocol and fully uses the harvested energy to precode and forward the information to the destination node. The non-linear energy harvesting models are considered at the relay node. With the consideration of the channel estimation error, the joint optimization of the TS factor, source and relay precoding matrices is proposed with robustness against the channel state information (CSI) mismatch to maximize the mutual information (MI) between the source and destination nodes. The optimal structure for the source and relay precoding matrices is derived to simplify the transceiver optimization problem. Numerical simulations show that the system performance provided by the proposed algorithms with robustness is better than the non-robust algorithm. [ABSTRACT FROM AUTHOR]

This paper studies the harvested energy maximization in an intelligent reflecting surface (IRS) aided multiuser multiple-input multiple-output (MIMO) simultaneous wireless information and power transfer (SWIPT) system in which the users can exploit power-splitting (PS) techniques for information decoding and energy harvesting (EH) simultaneously. A design problem is mathematically formulated as a joint optimization problem of transmit precoding (TPC) matrices at the base station (BS), the phase shifts at the IRS, and EH PS factors at the users to maximize the total harvested energy at the users while guaranteeing the quality of service requirements in terms of minimum achievable user rates and minimum harvested energy at each user. Considering the nonlinear EH models of the practical EH circuits at the users and unit-modulus constraints of the IRS phase shifters, the design problem becomes a highly nonlinear and non-convex optimization problem of the coupled matrix variables. To tackle the mathematical challenges in seeking the optimal solutions, we adopt alternating optimization to decompose the original design problem into two subproblems. The first subproblem is to jointly determine the TPC matrices at the BS and PS factors at the users while the second subproblem is to obtain the phase shifts at the IRS. Since each subproblem is still a non-convex optimization problem, we employ the minorization-maximization method to devise lower bound concave functions for the nonlinear EH and user rate functions and find the appropriate convex inner sets of the feasible sets to transform the optimization problems into convex ones. Verified by simulation results that the convergence of the proposed iterative algorithm is guaranteed and the total harvested energy is significantly improved as the multiuser MIMO SWIPT system is aided by the IRS with optimal phase shifts. [ABSTRACT FROM AUTHOR]

This paper studies the simultaneous wireless information and power transfer multi-antenna network with heterogeneous users and intelligent reflecting surface (IRS). Information decoding (ID) users, energy harvesting (EH) users, and power-splitting (PS) hybrid users require data and energy at the same time from the base station (BS) in the assistance of IRS. In the system model, the IRS reflects the incoming signal at each element by collaboratively adjusting phase shift to enhance the received signal at the users. In addition, the PS users exploit the PS circuit structure to simultaneously decode information and harvest energy via PS ratios. The target is to maximize the total PS-EH harvested power at PS and EH users with the non-linear EH model and limitation of BS transmit power while satisfying the signal-to-interference-plus-noise ratio requirements at ID and PS users. The information vectors at the BS, phase-shift vector at the IRS, and PS ratios at the hybrid users are jointly optimized by alternating optimization, semidefinite relaxation, sequential parametric convex approximation, and Gaussian randomization methods in the challenging non-convex problem. The numerical experiments present the convergence and effectiveness of the proposed algorithm. For certain parameters, the proposed IRS-assisted method enhances 17.65% total harvested power than the No-IRS one. [ABSTRACT FROM AUTHOR]

This research aims to develop an ultra-wideband millimeter-wave system with Simultaneous Wireless Information and Power Transfer (SWIPT), and Wireless Power Transmission (WPT) for the relays. As a large attenuation of a millimeter-wave path requires beamforming technology and relay for transmission, high- and low-resolution phase adjustments are used for optimizing beamforming. And a multi-objective function with the preset highest Bit Error Rate (BER) for SWIPT is presented. We discovered that the optimization of the beamforming by applying the adaptive differential algorithm has increased the harvesting power. To do so, we optimize the radiation pattern to meet the BER constraint for SWIPT and increase the harvested power ratio for the system simultaneously. In other words, our algorithms focus on increasing the harvesting power as soon as the information criteria is achieved. With WPT and SWIPT, the ratio of the total energy harvesting for the high-resolution array antennas is two times larger than that for the low-resolution ones. Numerical results also show that the harvesting power for the relay pointing to multiple targeted antennas simultaneously is about two times larger than that of pointing to each antenna by the time division techniques. [ABSTRACT FROM AUTHOR]

Antenna beamforming for Simultaneous Wireless Information and Power Transfer (SWIPT) and Wireless Power Transfer (WPT) in an indoor 6G communication system is presented in this paper. The objective function is to maximize the total harvesting power for the SWIPT and WPT nodes with the constraints of the bit error rate and minimum harvesting power. In the study, the power-splitting ratio between harvesting power and decoding information can be adjusted for the SWIPT node. Due to the non-convex problem, we use Self-Adaptive Dynamic Differential Evolution (SADDE) to optimize the designed multi-objective function. We use a symmetric antenna array to study three situations of distance—closer, farther, and similar—between the transmitting antenna and the individual SWIPT and WPT nodes in this paper. Experimental results show that the overall harvesting efficiency is improved, especially in the case of SWIPT nodes closer to the transmitter. The total harvesting power can be improved by 86.7% in the total short-distance case, and by 7.87% in the total long-distance case. [ABSTRACT FROM AUTHOR]

Owing to the factors such as controllable mobility, ready-to-use technology, low cost, easy implementation, and so on, unmanned aerial vehicle (UAV) possesses tremendous potential to be one of the primary candidates for next-generation (6G) wireless networks. This paper presents a UAV-assisted multiuser communication network where a multiple antenna UAV base station (BS) serves multiple single antenna ground users (GUs). UAV-BS uses a laser source-based charging mechanism to fulfill its power requirement and applies simultaneous wireless information and power transfer (SWIPT) in the downlink in order to provide desired power to energy-constrained GUs. Also, a clustering-based hybrid multiple access technique is used that combines both orthogonal multiple access (OMA) and non-orthogonal multiple access (NOMA) signaling to transmit the information to all GUs, simultaneously. Due to the involved analytical complexity corresponding to the multiple antennas and users, we use a hybrid beamforming method for efficient communication. Next, we analyze the performance of the proposed framework in terms of user outage probabilities, their respective throughput, and average power harvested considering non-linear energy harvesting and derive expressions of these performance metrics. Moreover, we formulate an optimization problem where the throughput of one GU is maximized by optimally choosing the power allocation parameter while ensuring the desired target throughput at other GU in each cluster. We also illustrate how crucial is the optimal selection of the target rates to maximize the network performance. Simulation results are provided to validate the accuracy of derived expressions and to highlight the dominance of hybrid beamforming and hybrid NOMA compared to conventional methods on the performance of the considered network. [ABSTRACT FROM AUTHOR]

In this article, we study the optimization of energy efficiency in wireless device-to-device (D2D-underlaid cellular networks where multiple D2D pairs adopt simultaneous wireless information and power transfer functionality. We formulate the optimization problem, which is a NP-hard combinatorial problem with nonlinear constraints. First, we use optimization-based-iterative techniques such as exhaustive search (ES) and gradient search (GS) with barrier, which are generally used to obtain the global optimum and local optimum of the nonconvex optimization problem, respectively. Considering that these techniques require a centralized unit to share information with each other, we propose multiagent deep reinforcement learning to solve this optimization problem in a distributed manner, which provides optimal decision making together with efficient deep network training under inequality constraints including transmit power, power splitting ratio, and minimum requirement data rate for D2D and cellular users. In this proposed method, we consider the virtual environment in which each agent can train their model according to shared information, and then, we deploy the trained model into the actual environment where each agent can only know their channel gain, interference power, and required minimum throughput. Simulation results show that the proposed algorithm can afford a near-global-optimum solution with much lower computation complexity than ES and outperforms the GS. [ABSTRACT FROM AUTHOR]

This study focuses on the downlink (DL) transmission of massive multiple-input-multiple-output (MIMO) with the support of simultaneous wireless information and power transfer (SWIPT) system based on a power-splitting (PS) scheme. To reach the green design target in the concept of wireless communication networks, this paper maximizes the system’s energy efficiency (EE) using joint system-level optimization. First, the closed-form expressions of the harvested energy and achievable data rate are first derived. Then, we formulated the EE maximization problem by jointly optimizing user equipment (UE) pilot transmission time allocation, the received PS ratios, a base station (BS) transmit power allocation, and a number of BS antennas while considering the minimum data rate as user’s quality-of-service (QoS) requirement and the maximum BS power transmission constraint. However, the formulated EE maximization problem is non-convex and non-linear which is difficult to solve. Hence, we propose an efficient low-complex alternative optimization (LCAO) algorithm to solve the non-convex problem iteratively with an acceptable computational complexity level. Simulation results are provided to evaluate the derived closed-form expressions and validate the proposed LCAO algorithm’s efficiency. The optimality, convergence, and complexity of the LCAO algorithm are analytically investigated. Results indicate that the proposed LCAO algorithm outperforms the equal power allocation (EPA) scheme by 15% better EE gain and 4% better than the max-min fairness scheme when the BS power transmission capacity is higher than 3 (Watt). [ABSTRACT FROM AUTHOR]

Magnetic Induction (MI) based transmissions, where the typical applications are wireless power transfer (WPT) and MI communications, have gained substantial attention in recent years. Existing works related to MI based transmissions mainly focus on the case with single resonant frequency. However, from the perspective of practical applications, it is highly demanded to achieve multi-frequency access for MI based transmissions. Although multiple coils can be used to generate additional resonant frequencies, each coil is often with one resonant frequency. In this paper, we develop the Multi-frequency Resonating Compensation (MuReC) coil based Multiple-band, Multiple-Input, and Multiple-Output (MbMIMO) simultaneous wireless information and power transfer (SWIPT), which can generate multiple resonant frequencies with one coil. The access point (AP) is equipped with multiple MuReC coils as well as delivers power and data to single-coil receivers (RXs) with different resonant frequencies. We propose the magnetic beamforming scheme for MuReC-MbMIMO-SWIPT, which aims to minimize the transmit power as well as guarantee the network throughput, total delivered power, and individual requirements of each channel. The beamforming schemes for two special cases of MuReC-MbMIMO-SWIPT, that is, MuReC-MbMIMO-communications and MuReC-MbMIMO-WPT, are also given. The optimal beamforming scheme in closed-form for MuReC-MbMIMO-communications is derived. In addition, the parameter design scheme for MuReC coils, which can support an arbitrary number of resonant frequencies, is developed. Numerical results verify our theoretical analyses and show that MuReC-MbMIMO transmissions and the proposed beamforming schemes can fully use antenna resources and effectively support multi-frequency access. [ABSTRACT FROM AUTHOR]

In this paper, two full-duplex (FD) relaying non-orthogonal multiple access (NOMA) schemes are proposed with simultaneous wireless information and power transfer (SWIPT) in which a near user employs energy harvesting (EH) to both decode its own information and assist a far user. By adapting the power allocation coefficient (PAC) and exploiting (EH) of self-residual interference (RSI) signal inherent to FD relaying, the proposed schemes can achieve superior performance over their counterparts. In particular, we derive a closed form expression for the outage probability (OP) of both near and far users. Simulation results verify our analysis and ensure the enhanced performance of both near and far users over the related schemes. [ABSTRACT FROM AUTHOR]

Abstract Non-orthogonal multiple access (NOMA) technology provides an effective solution to massive access with a high data rate demand in new-generation mobile networks. The paper combinations with NOMA and simultaneous wireless information and power transfer (SWIPT) relay to maximize the sum rate in the downlink system. To that end, it is critical how to select effectively users access system and power allocation for the access user. This paper proposes a user selection and dynamic power allocation (USDPA) scheme in the NOMA-SWIPT relay system based on neural network because traditional optimization methods have difficulty solving nonlinear and non-convex problems. We establish a user selection network utilizing a deep neural network (DNN) and propose a power allocation network using deep reinforcement learning. The simulation results show that the proposed scheme achieves better performance than other related schemes, especially for high quality of service requirements.

The rapid deployment of fifth-generation (5G) mobile communication systems demands sustainable power solutions. This paper introduces a novel joint design for wireless energy transmission and dynamic power management in full-duplex relay systems, aiming to ensure a continuous power supply for relay nodes. Our approach integrates energy harvesting from RF signals and dynamic battery management, focusing on optimizing throughput via energy allocation and precoding design. Simulation results demonstrate that our scheme significantly outperforms conventional non-battery half-duplex schemes in system throughput. Notably, we observe performance increments in throughput compared to all mentioned traditional methods, highlighting the efficacy of our design in enhancing 5G network sustainability and efficiency. This innovative approach presents a promising solution for effective power management in next-generation mobile networks. • Energy harvesting and battery management are employed in full-duplex systems. • A novel joint design for wireless energy and dynamic power management. • The throughput is optimized via dynamic energy management and precoding design. • Significant improvements over conventional, non-battery, half-duplex schemes. • A promising sustainable power solution for 5G network power management. [ABSTRACT FROM AUTHOR]