Search

In this paper, we consider a two-tier three phases simultaneous wireless information and power transfer (SWIPT)-enabled down-link cooperative non-orthogonal multiple access (NOMA) system. In inner tier, the farther central user decodes the information of the outer users, and then harvests energy from the base station to serve the outer users as a dedicated relay. In the cooperative phase, the nearer outer user is the potential relay to the further one; the users need to decode the information of the other outer user and also harvest energy for information transmission. The expressions of the achievable rate and outage probability of users are derived based on the transmit power allocation and the power splitting for the SWIPT system. A two-stage optimization problem is formulated by a resource allocation strategy, where the problem is constrained by the power allocations, the requirements of successive interference cancelation, and the outage probability. Since the primary problem of the outer optimization problem is non-convex, the problem is solved by the successive convex approximation (SCA). The rate maximization algorithm based on the dual-loop optimization is further developed. The simulation results validate that the proposed resource allocation scheme is capable of satisfying the performance requirements in a cooperative NOMA system, and the results also demonstrate the advantage of the cooperative NOMA system when implementing the SWIPT on the benchmarks of orthogonal multiple access (OMA). [ABSTRACT FROM AUTHOR]

Introducing collaborative relay and simultaneous wireless information and power transfer (SWIPT) techniques into a cognitive wireless network, named the SWIPT-enabled cognitive relay network (CRN), is considered a promising approach to deal with insufficiency and the low utilization of spectrum resources, as well as the node's energy-constrained issues in wireless networks. In this paper, to improve the network spectrum efficiency (SE) and energy efficiency (EE) of the SWIPT-enabled CRN, we design an energy-efficient adaptive bidirectional transmission strategy. To be specific, we first select an energy-constrained best relay node with the consideration of signal-to-noise ratio and global channel gain to achieve a better bidirectional relay transmission (BRT). At the same time, we let the energy-constrained best relay node transmit a signal with the SWIPT technique, which can solve the node's energy-constrained issue and improve the network EE. Then, with the selected energy-constrained best relay node, we design a total transmit power threshold (TTPT) determining algorithm to find the TTPT, which lets the total transmission rate of the BRT be equal to the bidirectional direct transmission (BDT). Based on this TTPT, we further design an adaptive bidirectional transmission strategy and let the network achieve adaptive transmission between the BRT and BDT to obtain a higher network SE. Furthermore, to further achieve the energy-efficient transmission of the adaptive bidirectional transmission strategy, we optimize the nodes' power under the requirement of primary users' interference threshold and obtain the analytical expressions of the optimal power. Simulation results show that the transmission rate, the outage probability, and the EE of the designed energy-efficient adaptive bidirectional transmission strategy in the SWIPT-enabled CRN are, respectively, 3.01, 0.07, and 3.10 times that of the non-collaborative transmission, which show the effectiveness of our designed transmission strategy. [ABSTRACT FROM AUTHOR]

This paper studies a dual-hop Simultaneous Wireless Information and Power Transfer (SWIPT)-based multi-relay network with a direct link. To achieve high throughput in the network, a novel protocol is first developed, in which the network can switch between a direct transmission mode and a Single-Relay-Selection-based Cooperative Transmission (SRS-CT) mode that employs dynamic decode-and-forward relaying accomplished with Rateless Codes (RCs). Then, under this protocol, an optimization problem is formulated to jointly optimize the network operation mode and the resource allocation in the SRS-CT mode. The formulated problem is difficult to solve because not only does the noncausal Channel State Information (CSI) cause the problem to be stochastic, but also the energy state evolution at each relay is complicated by network operation mode decision and resource allocation. Assuming that noncausal CSI is available, the stochastic optimization issue is first to be addressed by solving an involved deterministic optimization problem via dynamic programming, where the complicated energy state evolution issue is addressed by a layered optimization method. Then, based on a finite-state Markov channel model and assuming that CSI statistical properties are known, the stochastic optimization problem is solved by extending the result derived for the noncausal CSI case to the causal CSI case. Finally, a myopic strategy is proposed to achieve a tradeoff between complexity and performance without the knowledge of CSI statistical properties. The simulation results verify that our proposed SRS-and-RC-based design can achieve a maximum of approximately 40% throughput gain over a simple SRS-and-RC-based baseline scheme in SWIPT-based multi-relay networks.

For the intelligent reflecting surface (IRS)-assisted multiple input single output (MISO) simultaneous wireless information and power transfer (SWIPT) system, the beam forming vector at the base station and the reflected beam forming vector of the IRS were jointly optimized, by considering the maximum transmit power of the base station, the unit modulus constraint of the IRS reflection phase shift matrix, and the minimum energy constraint of the energy receiver. The object was to maximize the spectrum efficiency. To solve the non-convex optimization problem, a deep deterministic policy gradient (DDPG) algorithm based on deep reinforcement learning was proposed. Simulation results show that the average reward of the DDPG algorithm is related to the learning rate. Under the condition of selecting the appropriate learning rate, the DDPG algorithm can obtain an average mutual information similar to that of the traditional optimization algorithm, but the running time is significantly lower than that of the traditional non-convex optimization algorithm. Even if the number of antennas and the number of reflective units are increased, the DDPG algorithm can still converge in a short period of time. This indicates that the DDPG algorithm can effectively improve the computational efficiency and is suitable for communication services with high real-time requirements.

Summary: The intelligent reflecting surface (IRS) has recently become the most promising technology to achieve maximum beam‐forming gain with a simultaneous wireless information and power transfer (SWIPT) system. Many existing studies perform a single IRS deployment or utilize space division multiple access (SDMA) and non‐orthogonal multiple access (NOMA) schemes. However, the existing schemes face high time complexity and block signal transmission for larger indoor communications. Hence, this article introduces a dual IRS‐aided multiuser SWIPT system by implementing rate‐splitting multiple access (RSMA) systems. To enhance the minimum achievable rate and ensure the minimum harvesting energy (HE), this study proposes a joint successive convex approximation with an integrated optimization algorithm (SCA‐IOA). The proposed algorithm jointly optimizes the reflecting beam forming and power splitting (PS) coefficient of all the users effectively. The simulation results demonstrate the effectiveness of the proposed techniques and produce an outstanding performance for deploying dual IRS and implementing RSMA compared to traditional SDMA and NOMA systems. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Signal Processing is the property of Journal of Signal Processing 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.)

Abstract In this paper, we improve networks’ spectral efficiency (SE), extend networks’ lifetime, and maximize networks’ energy efficiency (EE) of two-way full-duplex (FD) relay networks. Firstly, to improve networks’ SE and to extend networks’ lifetime simultaneously, we design a two-way FD relay transmission strategy with simultaneous wireless information and power transfer and direct links (DLs). The designed transmission strategy can complete a bidirectional communication in only one time slot with the exists of DLs and the energy-constrained relay node. With the designed transmission strategy, we further give the characteristics of relay amplification factor, the analysis of the designed transmission strategy, and the EE analysis of traditional half-duplex two-way amplify-and-forward relaying. Secondly, to maximize networks’ EE, we present both the EE maximization problems and analyses of the designed transmission strategy with equal power allocation and optimal power allocation. To solve the EE maximization problems, we further propose the alternating optimal algorithm and give complexity analysis of the algorithm. Simulations show that our designed transmission strategy can improve the SE and EE of the networks.

Abstract Simultaneous wireless information and power transfer (SWIPT) has been advocated as a highly promising technology for enhancing the capabilities of 5G and 6G devices. However, the challenge of dealing with large propagation path loss poses a significant hurdle. To address this issue, massive multiple-input multiple-output (MIMO) is employed to enhance the efficiency of SWIPT in cellular-based networks with multiple small cells, and especially increase the energy for cell-edge users. In addition, by leveraging a large set of spatially distributed base stations to collaboratively serve SWIPT-enabled user equipment, the cell-free massive MIMO has the potential to provide even better performance than the conventional small-cell systems. In this work, we extend the investigation to include the application of SWIPT technology with alternating current (AC) logic in the cell-free networks and the small-cell networks and propose joint beamforming and power splitting optimization frameworks to maximize the system sum-rate, subject to the constraints on harvested energy, AC logic energy supply, and total transmit power. The optimization problem is shown to be non-convex, posing a significant challenge. To address this challenge, we resort to a two-stage decomposition approach. Specifically, we first introduce quadratic transform-based fractional programming (FP) algorithms to iteratively solve the non-convex optimization problems in the first stage, achieving near-optimal solutions with low time complexities. To further reduce the complexities, we also incorporate conventional schemes such as zero forcing, maximum ratio transmission, and signal-to-leakage-and-noise ratio for the design of beamforming vectors. Second, to determine the optimal power splitting ratio within the framework, we develop a one-dimensional (1-D) search algorithm to tackle the single variable optimization problem reduced in the second stage. These algorithms are then evaluated in the context of cell-free MIMO and small-cell networks with numerical experiments. The results show that the FP-based algorithms can consistently outperform those utilizing the conventional beamforming schemes, and the solutions of this work can achieve up to fivefold improvement in the system sum-rate than the small-cell counterpart while providing different but comparable performance trends in energy harvesting (EH).

This paper studies a multiuser multiple-input multiple-output simultaneous wireless information and power transfer cognitive radio system with the aid of an active intelligent reflecting surface (IRS). Considering the scenario that nonlinear energy harvesting models and power splitting (PS) protocols are adopted at energy receivers and that channel state information (CSI) imperfections of the channels to the primary users (PUs) are taken into consideration, we aim at designing the secondary base station (SBS) transmit precoding matrices, the IRS reflection coefficient matrix, and the secondary user (SU) PS ratios. The design objective is to maximize the system sum-rate (SR) under the transmit power constraints at the SBS, amplification power constraints at the IRS, amplitude constraints on IRS reflection elements, robust interference power (IP) constraints at the PUs, and minimum harvested energy constraints at the SUs. The formulated optimization problem is intractable to directly solve since the design variables are nonlinearly coupled, the objective function and constraints are highly nonconvex, and robust IP constraints are semi-infinite. To tackle the mathematical challenges, we derive the amenable surrogate functions and constraints while to handle the semi-infinite robust IP constraints, we transform them into linear matrix inequalities. Then, to find optimized solutions to the considered design problem, we exploit alternating optimization frames to derive an efficient iterative algorithm (IA). The convergence and computational complexity of the developed IA are shown. Simulation results illustrate the performance gains of the designed problem and robustness of IP constraints against CSI imperfections. Additionally, the numerical results show that the active IRS-aided systems exhibit superior SR performance over the passive IRS-aided systems. [ABSTRACT FROM AUTHOR]

Simultaneous wireless information and power transfer (SWIPT) has been advocated as a highly promising technology for enhancing the capabilities of 5G and 6G devices. However, the challenge of dealing with large propagation path loss poses a significant hurdle. To address this issue, massive multiple-input multiple-output (MIMO) is employed to enhance the efficiency of SWIPT in cellular-based networks with multiple small cells, and especially increase the energy for cell-edge users. In addition, by leveraging a large set of spatially distributed base stations to collaboratively serve SWIPT-enabled user equipment, the cell-free massive MIMO has the potential to provide even better performance than the conventional small-cell systems. In this work, we extend the investigation to include the application of SWIPT technology with alternating current (AC) logic in the cell-free networks and the small-cell networks and propose joint beamforming and power splitting optimization frameworks to maximize the system sum-rate, subject to the constraints on harvested energy, AC logic energy supply, and total transmit power. The optimization problem is shown to be non-convex, posing a significant challenge. To address this challenge, we resort to a two-stage decomposition approach. Specifically, we first introduce quadratic transform-based fractional programming (FP) algorithms to iteratively solve the non-convex optimization problems in the first stage, achieving near-optimal solutions with low time complexities. To further reduce the complexities, we also incorporate conventional schemes such as zero forcing, maximum ratio transmission, and signal-to-leakage-and-noise ratio for the design of beamforming vectors. Second, to determine the optimal power splitting ratio within the framework, we develop a one-dimensional (1-D) search algorithm to tackle the single variable optimization problem reduced in the second stage. These algorithms are then evaluated in the context of cell-free MIMO and small-cell networks with numerical experiments. The results show that the FP-based algorithms can consistently outperform those utilizing the conventional beamforming schemes, and the solutions of this work can achieve up to fivefold improvement in the system sum-rate than the small-cell counterpart while providing different but comparable performance trends in energy harvesting (EH). [ABSTRACT FROM AUTHOR]

In this paper, we improve networks' spectral efficiency (SE), extend networks' lifetime, and maximize networks' energy efficiency (EE) of two-way full-duplex (FD) relay networks. Firstly, to improve networks' SE and to extend networks' lifetime simultaneously, we design a two-way FD relay transmission strategy with simultaneous wireless information and power transfer and direct links (DLs). The designed transmission strategy can complete a bidirectional communication in only one time slot with the exists of DLs and the energy-constrained relay node. With the designed transmission strategy, we further give the characteristics of relay amplification factor, the analysis of the designed transmission strategy, and the EE analysis of traditional half-duplex two-way amplify-and-forward relaying. Secondly, to maximize networks' EE, we present both the EE maximization problems and analyses of the designed transmission strategy with equal power allocation and optimal power allocation. To solve the EE maximization problems, we further propose the alternating optimal algorithm and give complexity analysis of the algorithm. Simulations show that our designed transmission strategy can improve the SE and EE of the networks. [ABSTRACT FROM AUTHOR]

This paper investigates a novel full-duplex (FD) simultaneous wireless information and power transfer (SWIPT) based cooperative non-orthogonal multiple access (FDS-NOMA) system, where far distant NOMA IoT users are helped by the NOMA strong user with the capability of energy harvesting (EH) and FD communications. The downlink (DL-NOMA) principle is used to transmit the superimposed signals from source i.e a base station (BS) to an energy-limited FD relay where relay harvests energy from the transmit power of the BS. The relay after detecting the superimposed signals using successive interference cancellation (SIC), retransmits the decoded signals using superposition coding to the IoT users. We derive the analytical expressions of the outage probability and ergodic rates experienced by the NOMA strong user as well as NOMA IoT users. The results shows that proposed cooperative NOMA scheme can be used to serve IoT users using EH relay. Extensive simulations are performed to verify the accuracy of the derived approximate closed-from expressions. [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]

Laser Charging means high energy laser beam to irradiate the solar cell to gain electricity power through photovoltaic generation. This kind of wireless energy transform way fits the IoT and other low energy satiation with the benefit of long-distance transmission. In this paper, we present a new way of information transferring while energy is gained which is called Simultaneous Wireless Information and Power Transfer. The main idea is to switch the laser device output power to generate the different PV current values, the dual level of laser power decides two ranges of the value. We imitate the On-Off Keying (OOK) named Low-High Keying(LHK) which turns the information into the energy code with a high or low current value. The issue of information coding is also presented with an example. And the application also provided the realization presented. The new method provides a brand way to Simultaneous Wireless Information and Power transfer without any extra equipment by contrast with others. It's suited for the long-distance, low power and limited information-connected occasions.

With an emphasis on nonlinear models for energy harvesting (EH), this article examines nonlinear approaches in advanced optimization for simultaneous wireless information and power transfer (SWIPT). The SWIPT technology suffers from optimizing system performance due to its non-linearity EH complicated nature. In this review, the aim is to investigate the current trends in the field of nonlinear optimization in SWIPT and assess the efficiency of these technologies as well as their performances, challenges and limitations. The obtained findings reveal that there has been a clear shift towards using non-linear optimization approaches that have greater accuracy when it comes to modelling EH processes compared to traditional linear methods which have been used for a long time. These techniques show superior energy efficiency (EE), data rate, and security improvements. However, significant computational complexity is involved while trying to model accurately such hybrid communication systems which integrate machine learning (ML) algorithms or Intelligent Reflecting Surfaces (IRS). This paper has three main objectives, the first is to conduct a literature review on advanced nonlinear optimization techniques employed in SWIPT to trace their evolution, the second is to critically assess the effectiveness and performance of various non-linear optimization techniques in order to improve SWIPT system capabilities, and the third is synthesizing the challenges and difficulties encountered in applying nonlinear optimization techniques in SWIPT and derives new ideas that can fully leverage all benefits offered by SWIPT in future wireless networks such as developing low-complexity algorithms, refining nonlinear EH models using empirical data and advanced simulations, simplifying integrations with IRS and ML

A new design of intelligent reflecting surface (IRS)-aided mobile edge computing (MEC) system was studied, which consisted of a hybrid access point (HAP) connected with an MEC server, an IRS equipped with radio-frequency (RF) energy harvesting (EH) circuits, and a user side with random task arrival.To reduce energy consumption at the user, a novel protocol was proposed first, in which the system was enabled to select a proper operation mode among an EH mode, an IRS-aided task offloading mode, and an IRS-inactive task offloading mode.Then, based on the proposed protocol, an optimization problem was formulated, which aimed at minimizing the amount of consumed energy at the user by optimizing the selection of system operation mode and the resource allocation in each mode.Lyapunov optimization framework was employed to solve the problem to achieve a low-complexity and efficient optimization algorithm.Simulation results show that the proposed scheme can save 50% to 90% of energy consumption for the MEC system as compared with the existing baseline schemes.

Clustering protocols and simultaneous wireless information and power transfer (SWIPT) technology can solve the issue of imbalanced energy consumption among nodes in energy harvesting-cognitive radio sensor networks (EH-CRSNs). However, dynamic energy changes caused by EH/SWIPT and dynamic spectrum availability prevent existing clustering routing protocols from fully leveraging the advantages of EH and SWIPT. Therefore, a multi-hop uneven clustering routing protocol is proposed for EH-CRSNs utilizing SWIPT technology in this paper. Specifically, an EH-based energy state function is proposed to accurately track the dynamic energy variations in nodes. Utilizing this function, dynamic spectrum availability, neighbor count, and other information are integrated to design the criteria for selecting high-quality cluster heads (CHs) and relays, thereby facilitating effective data transfer to the sink. Intra-cluster and inter-cluster SWIPT mechanisms are incorporated to allow for the immediate energy replenishment for CHs or relays with insufficient energy while transmitting data, thereby preventing data transmission failures due to energy depletion. An energy status control mechanism is introduced to avoid the energy waste caused by excessive activation of the SWIPT mechanism. Simulation results indicate that the proposed protocol markedly improves the balance of energy consumption among nodes and enhances network surveillance capabilities when compared to existing clustering routing protocols. [ABSTRACT FROM AUTHOR]

Network energy resources are limited in communication systems, which may cause energy shortages in mobile devices at the user end. Active Reconfigurable Intelligent Surfaces (A-RIS) not only have phase modulation properties but also enhance the signal strength; thus, they are expected to solve the energy shortage problem experience at the user end in 6G communications. In this paper, a resource allocation algorithm for maximizing the sum of harvested energy is proposed for an active RIS-assisted Simultaneous Wireless Information and Power Transfer (SWIPT) system to solve the problem of low performance of harvested energy for users due to multiplicative fading. First, in the active RIS-assisted SWIPT system using a power splitting architecture to achieve information and energy co-transmission, the joint resource allocation problem is constructed with the objective function of maximizing the sum of the collected energy of all users, under the constraints of signal-to-noise ratio, active RIS and base station transmit power, and power splitting factors. Second, the considered non-convex problem can be turned into a standard convex problem by using alternating optimization, semi-definite relaxation, successive convex approximation, penalty function, etc., and then an alternating iterative algorithm for harvesting energy is proposed. The proposed algorithm splits the problem into two sub-problems and then performs iterative optimization separately, and then the whole is alternately optimized to obtain the optimal solution. Simulation results show that the proposed algorithm improves the performance by 45.2% and 103.7% compared to the passive RIS algorithm and the traditional without-RIS algorithm, respectively, at the maximum permissible transmitting power of 45 dBm at the base station. [ABSTRACT FROM AUTHOR]

Intelligent reflecting surface (IRS) is widely recognized as a promising technique to enhance the system performance, and thus is a hot research topic in future wireless communications. In this context, this paper proposes a robust BF scheme to improve the spectrum and energy harvesting efficiencies for the IRS-aided simultaneous wireless information and power transfer (SWIPT) in a cognitive radio network (CRN). Here, the base station (BS) utilizes spectrum assigned to the primary users (PUs) to simultaneously serve multiple energy receivers (ERs) and information receivers (IRs) through IRS-aided multicast technology. In particular, by assuming that only the imperfect channel state information (CSI) is available, we first formulate a constrained problem to maximize the minimal achievable rate of IRs, while satisfying the harvesting energy threshold of ERs, the quality-of-service requirement of IRs, the interference threshold of PUs and transmit power budget of BS. To address the nonconvex problem, we then adopt triangle inequality to deal with the channel uncertainty, and propose a low-complexity algorithm combining alternating direction method of multipliers (ADMM) with alternating optimization (AO) to jointly optimize the active and passive beamformers for the BS and IRS, respectively. Finally, our simulation results confirm the effectiveness of the proposed BF scheme and also provide useful insights into the importance of introducing IRS into the CRN with SWIPT.

Copyright of Acta Scientiarum Naturalium Universitatis Sunyatseni / Zhongshan Daxue Xuebao is the property of Sun-Yat-Sen University 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.)

In the scenario of a natural or human-induced disaster, traditional communication infrastructure is often disrupted or even completely unavailable, making the employment of emergency wireless networks highly important. In this paper, we consider an industrial Supervisory Control and Data Acquisition (SCADA) system assisted by an unmanned aerial vehicle (UAV) that restores connectivity from the master terminal unit (MTU) to the remote terminal unit (RTU). The UAV also provides power supply to the ground RTU, which transmits the signal to the end-user terminal (UT) using the harvested RF energy. The MTU-UAV and UAV-RTU channels are modeled through Nakagami-m fading, while the channel between the RTU and the UT is subject to Fisher–Snedecor composite fading. According to the channels' characterization, the expression for evaluating the overall probability of outage events is derived. The impact of the UAV's relative position to other terminals and the amount of harvested energy on the outage performance is investigated. In addition, the results obtained based on an independent simulation method are also provided to confirm the validity of the derived analytical results. The provided analysis shows that the position of the UAV that leads to the optimal outage system performance is highly dependent on the MTU's output power. [ABSTRACT FROM AUTHOR]

In the next-generation network, intelligent reflecting surface (IRS), non-orthogonal multiple access (NOMA), and simultaneous wireless information and power transfer (SWIPT) are promising wireless communication techniques to effectively improve system sum rates. In traditional unmanned aerial vehicles (UAV) communication systems, the sum rate and coverage are greatly affected when there is an occlusion on the direct transmission link. To solve this problem, the IRS technology is introduced to improve the poor channel conditions. However, most of the previous research on IRS-assisted UAV to optimize system sum rate only considers frameworks that utilize the partially joint-combining techniques of IRS, NOMA, and SWIPT. In this paper, in order to further improve the sum rate of the system, we simultaneously integrate IRS, NOMA, and SWIPT technologies and establish a sum rate maximization optimization problem when the direct link is blocked. Then, an alternative optimization (AO) algorithm based on the maximizing system sum rate is proposed to solve the non-convex optimization problem, in which the IRS location and phase, the reflecting amplitude coefficient, UAV forwarding altitude, and power splitting factor are considered. To let the non-convex and non-linear function be transformed into a convex one, we first use an iterative approach to optimize the position of the IRS. After that, an optimization problem is constructed to maximize the system sum rate with the constraints of the IRS phase shifts, successful successive interference cancellation (SIC), maximum transmit power of base station (BS), and UAV. Numerical results show that the proposed algorithm outperforms the traditional orthogonal multiple access (OMA) and algorithms without IRS-assisted links in terms of the system sum rate. [ABSTRACT FROM AUTHOR]

Copyright of Journal on Communication / Tongxin Xuebao is the property of Journal on Communications Editorial Office 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 paper investigates the effect of hardware impairments (HIs) and imperfect channel state information (ICSI) on a SWIPT-assisted adaptive nonorthogonal multiple access (NOMA)/orthogonal multiple access (OMA) system over independent and nonidentical Rayleigh fading channels. In the NOMA mode, the energy-constrained near users act as a relay to improve the performance for the far users. The OMA transmission mode is adopted to avoid a complete outage when NOMA is infeasible. The best user selection scheme is considered to maximize the energy harvested and avoid error propagation. To characterize the performance of the proposed systems, closed-form and asymptotic expressions of the outage probability for both near and far users are studied. Moreover, exact and approximate expressions of the ergodic rate for near and far users are investigated. Simulation results are provided to verify our theoretical analysis and confirm the superiority of the proposed NOMA/OMA scheme in comparison with the conventional NOMA and OMA protocol with/without HIs and ICSI.

For the cognitive relay network based on simultaneous wireless information and power transfer (SWIPT) and non-orthogonal multiple access (NOMA), which is termed as SWIPT-NOMA-CR network, considering the practical situation of imperfect successive interference cancellation (SIC) and channel state information (CSI), the outage performance of secondary users was studied by using three relay transmission schemes including ideal, time switching (TS) and power splitting (PS).The analytical expressions of outage probability were derived for the secondary users, and the theoretical derivations were validated by Monte Carlo simulations.The results show that the outage performance of secondary users is impaired due to the imperfect SIC and CSI.Compared with the imperfect CSI, the imperfect SIC causes more severe loss to the outage performance of the system.Moreover, the outage probability of PS relay transmission scheme is lower than that of TS scheme.When the imperfect SIC and CSI conditions are changed, the outage probability gap with PS scheme is less than that with TS scheme, which indicates that the reliability of PS relay transmission scheme is superior to that of TS scheme.

Intelligent reflecting surfaces (IRS) are considered one of the prominent technologies to be adopted in 6G and beyond networks. However, one of the main IRS limitations is restricting the communication to the reflective dimension, which means that users located behind the IRS surface cannot benefit from it. In this paper, we make use of intelligent omni-surfaces (IOS), as an alternative to IRS, in addition to unmanned aerial vehicles (UAV) to achieve secure communication in an Internet-of-Things (IoT) communication system. Specifically, we propose IOS-UAV assisted communication wherein an access point (AP) tries to send confidential information to a legitimate IoT device in presence of an eavesdropper. The UAV serves two fold; it acts as a friendly jammer that is trying to degrade the signal quality at the eavesdropper and as a source of energy to power up the IoT device via simultaneous wireless information and power transfer (SWIPT) to address the limited power available to it. We formulate an average secrecy rate maximization problem, which jointly optimizes the AP and UAV transmission powers, the UAV trajectory, IOS phase shifts and power splitting factor. The formulated problem is non-convex, therefore we exploit successive convex approximation (SCA) to tackle this issue. Simulation results show that the iterative SCA solution converges rapidly. Besides, the proposed scheme outperforms the traditional system without IOS by a gap of 140% in terms of the secrecy capacity.

Power Line Communication (PLC) and Simultaneous Wireless Information and Power Transfer (SWIPT) are popular examples of applications, where power and information are transmitted simultaneously. In most cases, different devices have been used to generate the power and communication signals independently. Usually, the information is superimposed onto the power signal using an external modulator. Recently, power converters have been used to generate pulses not just for power conversion but also for information transfer simultaneously. This approach represents a fundamental difference because it exploits the signal processing potential of Pulse Width Modulation (PWM), where for power conversion only the average pulse width is used, while the information is represented by the harmonics instead of being filtered out, as typically done in power electronics. The concept of embedding information into the switching ripple generated by a switched-mode power converter has recently been dubbed Talkative Power (TP), in this paper referred as Talkative Power Conversion (TPC). TPC technologies are reviewed in non-isolated and isolated converters in this paper. Potential applications include visible light communications, battery management systems, switching reluctance generators/motors, microgrids, and wireless electric vehicle charging stations. Finally, trending topics are identified.

Copyright of Journal of Chongqing University of Posts & Telecommunications (Natural Science Edition) is the property of Chongqing University of Posts & Telecommunications 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 letter studies an OFDM based intelligent reflecting surface (IRS)‐aided multiuser simultaneous wireless information and power transfer (SWIPT) system. With subcarrier allocation, users use the assigned subcarriers for information decoding (ID), and use signals received on subcarriers allocated to other users for energy harvesting (EH). An optimization problem is formulated to maximize the system energy efficiency by jointly optimizing subcarrier and power allocation and IRS reflection coefficients matrix. It can be solved by an alternating optimization algorithm. Simulation results reveal that energy efficiency can be enhanced in our proposed scheme compared with the benchmark schemes. [ABSTRACT FROM AUTHOR]

Simultaneous wireless information and power transfer (SWIPT) technology can effectively extend the lifecycle of energy-constrained networks. In order to improve the energy harvesting (EH) efficiency and network performance in secure SWIPT networks, this paper studies the resource allocation problem based on the quantitative EH mechanism in the secure SWIPT network. Based on a quantitative EH mechanism and nonlinear EH model, a quantified power-splitting (QPS) receiver architecture is designed. This architecture is applied in the multiuser multi-input single-output secure SWIPT network. With the goal of maximizing the network throughput, the optimization problem model is established under the conditions of meeting the legal user's signal-to-interference-plus-noise ratio (SINR), EH requirements, the total transmit power of the base station, and the security SINR threshold constraints. Due to the coupling of variables, the problem is a nonconvex optimization problem. To deal with the nonconvex optimization problem, a hierarchical optimization method is adopted. Firstly, an optimization algorithm based on the optimal received power of EH circuit is proposed, and a power mapping table is constructed through the optimization algorithm, from which the optimal power ratio to meet the user's EH requirements is obtained; then, the nonconvex problem is transformed into a convex problem by using variable substitution, semidefinite relaxation, dichotomous optimization, etc. The simulation results show that compared with the power splitting receiver architecture, the input power threshold range of the QPS receiver architecture is larger, which can avoid the EH circuit falling into the saturated working area and maintain high network throughput. [ABSTRACT FROM AUTHOR]

This study proposes an integrated framework of single-selection distributed antenna systems (DAS) and simultaneous wireless information and power transfer (SWIPT) with orthogonal multiple access (OMA), and analyzes the synergetic effects of SWIPT and DAS. To demonstrate the performance gains of the proposed SWIPT-enabled OMA with DAS, we jointly optimize power allocation for the OMA and power splitting (PS) ratio for energy harvesting of SWIPT with three different optimization goals: sum-rate maximization, user fairness, and energy efficiency. Although all of the above optimization problems are non-convex, the closed-form solutions of the problems maximizing the sum-rate and fairness are presented. Owing to difficult analytical tractability of the problem maximizing the energy efficiency, the problem is divided into three subproblems: power allocation for the base station (BS), power allocation for radio remote unit (RRU), and PS ratio assignment. Then, an iterative algorithm is presented to provide the energy-efficient SWIPT-enabled OMA with DAS. Theoretical findings are validated by numerical results, which show that the framework of applying DAS to SWIPT-OMA improves data rates and energy efficiency compared to SWIPT-OMA without DAS, while satisfying the minimum rate and harvested energy requirements. [ABSTRACT FROM AUTHOR]

Simultaneous wireless information and power transfer (SWIPT) technology provides an efficient solution to energy-limited communication terminals in a wireless network. However, in the current application scenario of SWIPT technology, relays use all the collected energy forwarding to assist communication between source nodes, while ignoring the fact that relays can accumulate and store energy. This is of great practical significance in collaborative communication. By using a transmission scheme of a time-division broadcast for the direct transmission link, improvement of the system diversity gain through combining the technology at the receiver can be realized. Based on the above, we propose a two-way relay energy accumulation communication system, which is extended from a single relay system to a multi-relay system. The instantaneous transmission rate of the system link and the system equivalent profit are optimized by jointly optimizing the relay selection, time slot allocation factor, power splitting factor and relay transmit power. Compared with the comparison algorithm, the proposed algorithm shows a significant improvement in the performance of the system. [ABSTRACT FROM AUTHOR]

This paper investigates the effect of hardware impairments (HIs) and imperfect channel state information (ICSI) on a SWIPT‐assisted adaptive nonorthogonal multiple access (NOMA)/orthogonal multiple access (OMA) system over independent and nonidentical Rayleigh fading channels. In the NOMA mode, the energy‐constrained near users act as a relay to improve the performance for the far users. The OMA transmission mode is adopted to avoid a complete outage when NOMA is infeasible. The best user selection scheme is considered to maximize the energy harvested and avoid error propagation. To characterize the performance of the proposed systems, closed‐form and asymptotic expressions of the outage probability for both near and far users are studied. Moreover, exact and approximate expressions of the ergodic rate for near and far users are investigated. Simulation results are provided to verify our theoretical analysis and confirm the superiority of the proposed NOMA/OMA scheme in comparison with the conventional NOMA and OMA protocol with/without HIs and ICSI. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Xinyang Normal University Natural Science Edition is the property of Journal of Xinyang Normal University Editorial Office 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 paper studies the effect of co-channel interference (CCI) on energy harvesting (EH) from radio frequency (RF) signal and the performance of reliable communication. An overlay mode of cooperative cognitive radio network (CCRN) model is considered that may support one-way communication between primary users (PUs) and two-way communications between secondary users (SUs). Closed form PU and SU outage expressions are derived in presence of CCI at two SU nodes and multiple antennas at PU transmitter. The absolute impact of CCI on the performance of the proposed system is analysed with respect to various parameters like, transmission power, interference-to-noise-ratio (INR), power splitting factor, number of CCI sources and number of antennas. About 20% and 15% improvements are achieved for PU and SU outage using two antennas compared to single antenna system model. [ABSTRACT FROM AUTHOR]

Background and Objectives: The purpose of a wireless body area network (WBAN) is to collect and send vital body signals to the physician to make timely decisions, improve the efficiency of medical informatics systems, and save costs. The sensors of the WBAN network have limited size and energy, and hence, to extend the lifetime of these sensors, they can be powered wirelessly. Our focus in this paper is on a two-tier full-duplex (FD) cooperative WBAN in which sensors, in addition to transmitting physiological information, harvest energy from radio frequency (RF) coordinator signals and body sources. Our goal is to maximize average weighted sum throughput (AWST) under the constraints of each sensor, including meeting the minimum data rate, delay limitation, energy and transmission power constraints. Methods: The resources allocated to solve this optimization problem are the time slots, the transmission rates of the sensors and coordinator, and the transmission powers of sensors in each time slot. The time scheduling problem in the first step is modeled in the form of a mixed-integer linear programming (MILP) problem and the second step problem is convex. Also, Karush–Kuhn–Tucker (KKT) conditions are presented for power and rate allocation.Results: In the optimal allocation (OA) mode, contrary to the equal time allocation (ETA) one, with increasing the relay power, the AWST increases despite increasing self-interference (SI). Energy harvesting from the body, nevertheless the power consumption for transmission, makes positive the slope of the instantaneous energy curve for the motion sensor and reduces the corresponding slope for the electrocardiogram (ECG) one. Comparison of the proposed method with previous methods shows that the proposed method has better control over the information flow of sensors, and also in allocating rate to users, fairness is satisfied.Conclusion: According to the simulation results in our method, the system showed better performance than the equal time allocation mode. We also used the FD technique and with the help of the optimal time scheduling index, we were able to control the SI.

In full-duplex multi-relay cooperative simultaneous wireless information and power transfer (SWIPT) networks,traditional relay selection algorithms have not taken into account the idle utilization of unselected relays.As a result,the performance waste of the network becomes more serious as the number of relays increases.How to exploit the remaining potential of unselec-ted relays becomes the key to improve network performance.For this,a new HTT (Harvest then Transmit) power consumption scheme is proposed,which increases the transmit power of the selected relay by making full use of the energy harvesting module at the relay,thereby further improving the system capacity.In addition,for the proposed HTT power consumption scheme,two practical scenarios,BIKT (Battery Information Known at Transmitter) and BIUT (Battery Information Unknown at Transmitter) are considered.The result of simulation experiments show that three relay selection algorithms,namely single relay selection,greedy relay selection and exhaustion search,can effectively benefit from the proposed HTT power consumption scheme in terms of system capacity and outage probability whether applied to BIKT scenarios or BIUT scenarios.

Simultaneous Wireless Information and Power Transfer (SWIPT) network is a promoting mode which provides continuous energy for the energy limited scenarios. Combining the relay transmitting mode and power–time-splitting mode, the optimization problem of minimizing the energy consumption is formulated. Different from the common consumption that the energy receiver can harvest energy in linear way, the nonlinear SWIPT model is taken into consideration, which is more realistic, and the causality of energy consumption and requirements of transmission rate are included as the constraints. To solve the nonlinear and coupled optimization problem, a decomposed mode in two layers is proposed. In the outer layer, the optimization of EH architecture is performed, in the inner layer, the joint optimization of beamforming vector, time division factor and power division factor are performed. Due to the coupled variables and the existence of nonlinear constraints, solving the inverse function by variable substitution is introduced, and the primary problem is transformed to a linear form. Finally, the Lagrangian function of the transformed optimization problem is solved, and the optimal solution of the problem is obtained by performing several iterations of the projection gradient method and the CVX solver alternatively. The simulations verify that the nonlinear-multi-EH circuits model is effective to improve energy conversion efficiency and reduce the energy consumption of the base station, and the results show that there is at least 26.4% improvement on energy saving compared to the benchmark schemes. [ABSTRACT FROM AUTHOR]

Network energy resources are limited in communication systems, which may cause energy shortages in mobile devices at the user end. Active Reconfigurable Intelligent Surfaces (A-RIS) not only have phase modulation properties but also enhance the signal strength; thus, they are expected to solve the energy shortage problem experience at the user end in 6G communications. In this paper, a resource allocation algorithm for maximizing the sum of harvested energy is proposed for an active RIS-assisted Simultaneous Wireless Information and Power Transfer (SWIPT) system to solve the problem of low performance of harvested energy for users due to multiplicative fading. First, in the active RIS-assisted SWIPT system using a power splitting architecture to achieve information and energy co-transmission, the joint resource allocation problem is constructed with the objective function of maximizing the sum of the collected energy of all users, under the constraints of signal-to-noise ratio, active RIS and base station transmit power, and power splitting factors. Second, the considered non-convex problem can be turned into a standard convex problem by using alternating optimization, semi-definite relaxation, successive convex approximation, penalty function, etc., and then an alternating iterative algorithm for harvesting energy is proposed. The proposed algorithm splits the problem into two sub-problems and then performs iterative optimization separately, and then the whole is alternately optimized to obtain the optimal solution. Simulation results show that the proposed algorithm improves the performance by 45.2% and 103.7% compared to the passive RIS algorithm and the traditional without-RIS algorithm, respectively, at the maximum permissible transmitting power of 45 dBm at the base station.

Clustering protocols and simultaneous wireless information and power transfer (SWIPT) technology can solve the issue of imbalanced energy consumption among nodes in energy harvesting-cognitive radio sensor networks (EH-CRSNs). However, dynamic energy changes caused by EH/SWIPT and dynamic spectrum availability prevent existing clustering routing protocols from fully leveraging the advantages of EH and SWIPT. Therefore, a multi-hop uneven clustering routing protocol is proposed for EH-CRSNs utilizing SWIPT technology in this paper. Specifically, an EH-based energy state function is proposed to accurately track the dynamic energy variations in nodes. Utilizing this function, dynamic spectrum availability, neighbor count, and other information are integrated to design the criteria for selecting high-quality cluster heads (CHs) and relays, thereby facilitating effective data transfer to the sink. Intra-cluster and inter-cluster SWIPT mechanisms are incorporated to allow for the immediate energy replenishment for CHs or relays with insufficient energy while transmitting data, thereby preventing data transmission failures due to energy depletion. An energy status control mechanism is introduced to avoid the energy waste caused by excessive activation of the SWIPT mechanism. Simulation results indicate that the proposed protocol markedly improves the balance of energy consumption among nodes and enhances network surveillance capabilities when compared to existing clustering routing protocols.

The combination of non-orthogonal multiple access (NOMA) and simultaneous wireless information and power transfer (SWIPT) technologies can improve spectrum efficiency of wireless system and solve the power supply problem of user nodes.However, when energy-harvesting receivers want to maliciously eavesdrop on confidential information sent by the base station, the information security transmission of SWIPT-NOMA system will be threatened.To enhance its physical layer security (PLS) performance, the PLS model of SWIPT-NOMA system with transmit antenna selection and power split strategies was proposed.When the spatial location randomly distributed energy-harvesting receivers obey the Poisson point process, the approximate expressions for the secrecy outage probability and non-zero secrecy capacity probability of SWIPT-NOMA system were derived by using the spatial Poisson probability generation function.Numerical and simulation results verify the accuracy of the expressions.The above expressions can also be used to study the influence of eavesdropper density, the distance between the base station and the far and near information receivers, the number of transmitting antennas and the power split factor on PLS performance of SWIPT-NOMA system.

In this paper, the security of two-way relay communications in the presence of a passive eavesdropper is investigated. Two users communicate via a relay that depends solely on energy harvesting to amplify and forward the received signals. Time switching is employed at the relay to harvest energy and obtain user information. A friendly jammer is utilized to hinder the eavesdropping from wiretapping the information signal. The eavesdropper employs maximal ratio combining and selection combining to improve the signal-to-noise ratio of the wiretapped signals. Geometric programming (GP) is used to maximize the secrecy capacity of the system by jointly optimizing the time switching ratio of the relay and transmit power of the two users and jammer. The impact of imperfect channel state information at the eavesdropper for the links between the eavesdropper and the other nodes is determined. Further, the secrecy capacity when the jamming signal is not perfectly cancelled at the relay is examined. The secrecy capacity is shown to be greater with a jammer compared to the case without a jammer. The effect of the relay, jammer, and eavesdropper locations on the secrecy capacity is also studied. It is shown that the secrecy capacity is greatest when the relay is at the midpoint between the users. The closer the jammer is to the eavesdropper, the higher the secrecy capacity as the shorter distance decreases the signal-to-noise ratio of the jammer. [ABSTRACT FROM AUTHOR]

In order to verify the impact of transceiver hardware impairments on the performance of communication system, we explore the robust transmission design of an intelligent reflecting surface (IRS) aided simultaneous wireless information and power transfer (SWIPT) communication system in consideration of hardware impairments of transceiver. Under the constraints of maximum transmitting power of base station, the minimum receiving energy of the energy collector and IRS passive beamforming, the optimization objective is set to maximize the weighted sum rate of all information receivers. And the block coordinate descent (BCD) algorithm is used to decompose the optimization problem into multiple optimization subproblems for alternate optimization. The Lagrange dual method and maximization minimization (MM) algorithm are respectively adopted to solve the optimization problems of active beamforming and IRS passive beamforming. Simulation results validate the impact of transceiver hardware impairments on system performance, and also confirm that the hardware impairment at information receiver is more obvious than the hardware impairment at base station transmitter. [ABSTRACT FROM AUTHOR]

In order to achieve high spectral efficiency and high energy efficiency for large-scale millimeter-wave(mmWave) multiple- input multiple-output(MIMO) systems, the non-orthogonal multiple access iterative optimization algorithm and cluster head selection algorithm were used to study the hybrid precoding problem in simultaneous wireless information and power transfer scenarios. The simulation results show that the proposed algorithm can achieve higher spectral efficiency and energy efficiency compared with the traditional hybrid precoding algorithm for orthogonal multiple access simultaneous wireless information and power transfer. [ABSTRACT FROM AUTHOR]

Abstract Smart Internet of Vehicles (IoV) as a promising application in Internet of Things emerges with the development of the fifth generation mobile communication (5G). Nevertheless, the heterogeneous requirements of sufficient battery capacity, powerful computing ability and energy efficiency for electric vehicles face great challenges due to the explosive data growth in 5G and the sixth generation of mobile communication (6G) networks. In order to alleviate the deficiencies mentioned above, this paper proposes a mobile edge computing (MEC) enabled IoV system, in which electric vehicle nodes upload and download data through an anchor node which is integrated with a MEC server. Meanwhile, the anchor node transmitters radio signal to electric vehicles with simultaneous wireless information and power transfer technology so as to compensate the battery limitation of eletric vehicles. Moreover, the spectrum efficiency is further improved by multi-input and multi-output and full-duplex technologies which is equipped at the anchor node. In consideration of the issues above, we maximize the average energy efficiency of electric vehicles by jointly optimize the CPU frequency, vehicle transmitting power, computing tasks and uplink rate. Since the problem is nonconvex, we propose a novel alternate interior-point iterative scheme (AIIS) under the constraints of computing tasks, energy consumption and time latency. Results and discussion section verifies the effectiveness of the proposed AIIS scheme comparing with the benchmark schemes.