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Non-orthogonal multiple access (NOMA) has recently gained much research attention as a possible multiple access solution for fifth-generation (5G) wireless communication. The NOMA can further enhance spectral performance compared with orthogonal multiple access (OMA). This paper focuses on the joint optimization problem of power control and user grouping by considering the uplink NOMA system. The power control issues are solved using a linear programming approach and three alternative algorithms solve user grouping: Randomly, 2-Opt, and the Hybrid. The numerical results show that the proposed solution for power control and user-grouping achieves significant spectral performance compared to OMA and existing schemes reported in the literature with lower system complexity for uplink NOMA systems.

Visible light communication (VLC)-enabled unmanned aerial vehicle (UAV) networks have emerged as a novel approach for simultaneous illumination and communication. Among the prominent challenges in VLC are shadowing and low reflected energy. Light-emitting diode (LED) beam-steering is a promising technique to overcome these challenges. In this paper, we consider the problem of joint UAV deployment, LED beam-steering, cell association, and power allocation to satisfy a set of illumination and data rate requirements for stochastically distributed users. Towards addressing this problem, we develop SteerVLC, a novel scheme for UAV networks equipped with steerable LEDs that jointly optimizes UAV deployment, LED beam-steering, cell association, and power allocation. While accounting for illumination interference, SteerVLC minimizes the number of UAVs needed to satisfy the illumination and data rate requirements of stochastically distributed users and minimizes the total transmission power of the steerable LEDs. Using an $\epsilon $ -controlled two-stage mixed-integer linear programming approach, SteerVLC can effectively manage the tradeoff between the required number of UAVs and the required transmission power. SteerVLC is evaluated under various system parameters, user demands, and user distributions. Our results demonstrate the superiority of SteerVLC in managing the resources of a VLC-enabled UAV network and optimizing its performance.

In this paper, we consider the problem of multi-cell interference coordination by joint beamforming and power control. Recent efforts have explored the use of reinforcement learning (RL) methods to tackle this complex optimization problem. Typically, a decentralized multi-agent framework is adopted, wherein each base station operates as an independent RL agent. This distributed coordination has gained attention because designing a reward function that effectively captures the condition of the entire cellular network is challenging for single-agent RL models. However, the distributed approach introduces unique challenges, particularly the non-stationary of the multi-agent environment, as agents continually adapt their policies to interact with one another. The non-stationary environment necessitates information exchange among agents, as local observations of each agent are insufficient to fully capture the true state of the environment. Unfortunately, this information exchange incurs a significant overhead, thereby limiting data transmission capabilities. To address these challenges, we propose a novel single-agent RL approach that eliminates the need for information exchange and the conventional reward function. Instead, we leverage success examples to guide the learning process. Simulation results show that the proposed approach outperforms the existing multi-agent method and theoretical algorithm in terms of sum rates. Additionally, our approach ensures a uniform quality of service while maximizing the overall sum rate.

Future Road transportation mainly depends upon connected vehicles. Intelligent Transportation Systems bring benefits to the road users through Vehicular Adhoc Networks (VANETs). Since VANET packet contains life critical information, security is inevitable. A rogue node called sybil node can transmit fake messages to its neighbours and disrupt the system, challenging security. Since the nodes are very dynamic, stability is also a major concern. Existing rogue node detection methods do not address this problem suitably. In the proposed work, rouge node detection is implemented in a clustered network which improves the stability of the network. The main aim of this paper is to implement a sybil attack detection method in distributed or coordinated clustered networks using a novel hybridization technique. The cluster head detects the sybil attacker by comparing the received signal strength of packets from each node based on a similarity algorithm, Longest Common SubSequence (LCSS). However, if the sybil attacker launches a power control mechanism, the similarity calculation fails. To overcome this issue, a Change Point Detection(CPD) technique by comparing the changes in mean value of RSS time series from a particular node is proposed. Coordinated attacks can be easily detected in a clustered network as the information regarding the attackers’ spreads in the network quickly so that the nodes can avoid connecting to such malicious nodes during their journey. The proposed algorithm shows significant improvement in detection rate, detection delay and false positive for varying vehicle count compared to existing techniques.

For a high-speed railway relay downlink communication system based on short-packet transmission, the problem of maximizing the minimum user throughput by jointly optimizing the transmission packet length and the transmission power control of the relay device is investigated in this paper. The optimization problem is a nonconvex and mixed-integer one that is difficult to obtain an optimal solution, and a low-complexity algorithm is proposed to obtain the solution to the joint optimization problem. First, a closed-form expression of the optimal blocklength is derived by fixing the transmission power; Secondly, in the case of fixed blocklength, the non-convex optimization subproblem of transmission power is transformed into a convex problem by introducing auxiliary variables and using the successive convex approximation method. Finally, the feasibility and effectiveness of the proposed algorithm in this paper are verified by simulation.

In order to solve the resource allocation problem in scenarios of centralized wireless cellular communication with multiple cells, users and channels, a novel resource allocation algorithm based on joint Deep Deterministic Policy Gradient (DDPG) reinforcement learning and unsupervised learning is proposed. Firstly, the proposed algorithm constructs a channel allocation deep neural network based on DDPG to provide an optimized channel allocation scheme. Secondly, the proposed algorithm constructs a power control deep neural network based on unsupervised learning to provide an optimized power control scheme. In order to make the unsupervised learning have perceptions on dynamic wireless environments, the double experience replay is executed to train the channel allocation deep neural network with the DDPG reinforcement learning and the power control deep neural network with the unsupervised learning, respectively. Since the proposed joint algorithm combines the dynamic perception ability of the DDPG reinforcement learning and the continuous optimization ability of unsupervised learning, the energy efficiency can be effectively maximized. Simulation results show that the proposed algorithm outperforms other algorithms in terms of energy efficiency and transmit rate in time-varying dynamic environments. Furthermore, we discuss the implications of our results and possible future research directions. Our work contributes to the advancement of resource allocation techniques in multi-cell cellular networks to meet the increasing demands of modern wireless communication systems.

As one of the core technologies of future autonomous vehicles,Cellular-V2X(C-V2X) faces a series of developing pain points related to network connectivity,such as mobility,coverage and spectrum,while rapidly popularizing its application.The connectivity of C-V2X based cooperative vehicle-infrastructure system directly reflects the overall performance of C-V2X network connected vehicles,which is of great significance to ensure information can achieve long-distance,adaptive,low latency and high reliable transmission.Different from the traditional cellular mobile communication network,C-V2X networking vehicles have the characteristics of high moving speed,short link duration between nodes,strong predictability of wireless communication environment,and mobility model limited by road topology.To make efficient use of spectrum for communication,C-V2X networking vehicles also have the characteristics of no center and self-organization of ad hoc network.Firstly,the advantages and characteristics of C-V2X are briefly introduced,including the progress and structure of C-V2X.On this basis,research on connectivity of C-V2X network are summarized and classified based on transportation scenarios,communication mode selection,road side unit(RSU) location deployment,power control and model driven.Finally,the development trends of connectivity for C-V2X are discussed and its future application is prospected.

In recent years, Underwater Acoustic Sensor Networks (UASNs) have gained considerable attention for their unique role in detecting and monitoring the underwater environment. However, due to the long propagation time, high bit error rate, and limited bandwidth of underwater acoustic systems, the design of media access control (MAC) protocols is extremely complex, especially for the power consumption of UASNs. Therefore, this paper proposes an energy-efficient MAC protocol for three-dimensional UASNs with time synchronization and power control (TDTSPC-MAC). The proposed protocol is a hybrid access scheme for three-dimensional UASN using techniques such as time synchronization, power control, clustering, layering, and sleep mechanisms. Moreover, the TDTSPC-MAC protocol uses the hierarchical concept and distributed clustering algorithm to divide the three-dimensional space, and combines time synchronization and power control strategies to avoid collisions. Besides, energy consumption is reduced through monitoring and sleep mode. Simulation results demonstrate that the proposed TDTSPC-MAC protocol has reasonable data transmission delay time, throughput, energy consumption, and other performance.

As a clean and efficient energy, nuclear energy can replace coal for heating in winter, so as to achieve the goal of “reducing pollution and carbon” in the heating process. According to the heat supply demand index proposed by the heat supply network, based on MATLAB/Simulink simulation platform, the whole plant main system model of swimming pool-type low-temperature reactor was established, and the heat supply control scheme which can be used for reactor power regulation was put forward in this paper. The fixed value adjustment process of reactor power and the reactor response process under heat network accident conditions were analyzed in detail. The simulation results show that the control scheme can adjust the reactor power according to the fixed value demand of the heat supply network load. During the adjustment process, the main temperature parameters of the reactor are within the safety limit, and the temperature in the user room of the heat supply network can be maintained near 18 ℃. Due to the large heat capacity of the low-temperature reactor pool and there are three heat exchange circuits from the heat source to the heat network, resulting in a certain pure lag link, which makes the regulation time constant of the water supply temperature very large. At the same time, the control scheme has a certain ability to resist small load disturbance under accident conditions. In case of small load step disturbance of 2%PN caused by accidents such as fracture of heat supply network, the scheme can control the reactor power unchanged, and the temperature in the user’s room can only change within the range of 1 ℃ and be stabilized again. In addition, the control scheme can automatically trigger the flow control link of the primary circuit under the accident condition of the heat supply network, adjust the flow of the primary circuit, so that the temperature entering the reactor water tank does not exceed 68 ℃, so as to ensure that the water temperature of the water tank does not exceed the concrete temperature limit. As the primary circuit flow decreases, the core outlet temperature rises immediately. Therefore, it is necessary to place the main pump lower from the ground, so as to increase the effective NPSH (net positive suction head) of the main pump and prevent it from cavitation. In conclusion, the heating control scheme can meet the heating load demand of the heating network, maintain the stability of reactor power under the condition of small disturbance of the heating network accident, and meet the safety requirements of temperature parameters, which have a certain design reference value.

The blustery growth of high data rate applications leads to more energy consumption in wireless networks to satisfy service quality. Therefore, energy-efficient communications have been paid more attention to limited energy resources and environmentally friendly transmission functioning. Countless publications are present in this domain which focuses on intensifying network energy efficiency for uplink-downlink transmission. It is done either by using linear precoding schemes, by amending the number of antennas per BS, by power control problem formulation, antenna selection schemes, level of hardware impairments, and by considering cell-free (CF) Massive-MIMO. After reviewing these techniques, still there are many barriers to implement them practically. The strategies mentioned in this review show the performance of EE under the schemes as raised above. The chief contribution of this work is the comparative study of how Massive MIMO EE performs under the background of different methods and architectures and the solutions to few problem formulations that affect the EE of network systems. This study will help choose the best criteria to improve EE of Massive MIMO while formulating a newer edition of testing standards. This survey provides the base for interested readers in energy efficient Massive MIMO.

Abstract Fault analysis is necessary to design a protection system and circuit breakers for a power system network. The multiphase system is a new technology so very little work is found for the fault analysis of a multiphase system contrary, unlike a three‐phase system. The faults in a seven‐phase system may be either symmetrical or non‐symmetrical. A non‐symmetrical fault requires studying the sequence components of a seven‐phase system using Fortescue transformation. In the paper, non‐symmetrical fault analysis of the seven‐phase system has been analysed. For this, a new definition of sequence components of an unbalanced seven‐phase system has been proposed in this paper. Then the proposed sequence components are applied to different faults studies at the input and output sides of a seven‐phase transformer. Further, the effect of the construction of a seven‐phase transformer, that is, core type and shell type on its output is studied. Moreover, the effect of open‐phase input is analysed using simulation and hardware results. From the analysis, it is found that in certain configurations of a seven‐phase transformer, the seven‐phase output is produced even though open‐phase fault is present at the input while in other configurations, seven‐phase is not produced in the case of open‐phase fault.

To meet the needs of intensive computing and low latency,mobile edge computing pushes the service resources of cloud computing to the edge,where is closer to the terminal.The ground network faces challenges in scenarios such as complex terrain and equipment failure.With the assistance of unmanned aerial vehicles,the flexibility and robustness of network deployment can be improved.Unmanned aerial vehicle has the advantages of low cost,convenient operation and flexible mobility.Due to the limitations of volume and weight,the power,communication and computing resources are often limited,the heterogeneity and dynamic characteristics gradually emerge in multi-unmanned aerial vehicle collaboration.Therefore,how to make efficient use of the resources become a research hotspot.From the perspective of overview,the problems and challenges faced in the promotion and application of UAV edge computing networks are combed,the current research status in power control,channel allocation,computing service resource management,and resource joint optimization are analyzed and summarized,the feasible optimization solutions of resource management are summarized and compared.Finally,the future development trend of resource management optimization is analyzed and prospected.

In the two phase static coordinate system, the power control strategy of the current source PWM rectifier is established based on the instantaneous power theory. This article proposes a reactive power compensation scheme based on ac side filter capacitors, which enables CSR to achieve unit power factor operation under different load conditions. In order to effectively suppress the parallel resonance generated by the LC filter on the input side of the rectifier, a capacitive voltage feedback active damping loop is introduced, and the influence of different damping gains on the system performance is analyzed in detail. The dc side outer loop is converted into a linear time invariant system, the ac and dc side power calculation process is analyzed in detail, and the entire control loop is analyzed using frequency domain method to determine the controller parameters. Finally, the correctness of the control strategy proposed in this article is verified by Matlab/Simulink simulation and experimental prototype test.

Control for single‐phase cascaded H‐bridge rectifier (CHBR) under distorted grid voltage is seldom discussed in the existing control methods; a modified direct power control (DPC) scheme is therefore proposed in this paper. A simple power control structure with proportional‐integral control method is first presented, which can discard phase‐locked loop (PLL) and coordinate transformation. Then, an improved fictitious orthogonal algorithm is proposed to provide a better anti‐disturbance ability compared with the traditional second‐order generalized integrator (SOGI). Since the orthogonal component of the grid current runs concurrently with the power reference, it offers an excellent dynamic performance in inner loop. On the other hand, a voltage balancing control (VBC) model by the relationship between the difference of dc‐side voltage square and that of power is established. On this basis, an internal model VBC (IM‐VBC) method is provided to reduce the parameter tuning complexity. With this method, the dynamic performance of voltage balancing on the dc side is improved. Finally, several test results on hardware‐in‐the‐loop (HIL) and scale‐down platform are demonstrated, which validate the effectiveness and superiority of the proposed control strategy. [ABSTRACT FROM AUTHOR]

In islanded microgrids, when a short circuit or a sudden overload occurs, it provokes an abrupt increment in the currents supplied by the generation nodes, which feed the load collaboratively. This is particularly challenging for inverter‐based nodes, due to its reduced power capacity. This work takes advantage of the droop‐method basic configuration to propose an additional closed‐loop control, which ensures maximum current injection during any kind of short circuit maintaining the underlying droop control. Ensuring that any node injects its maximum rated current during the short circuit, it emulates the most common low‐voltage ride‐through protocols for grid‐feeding sources oriented to support the grid and, in this way, the voltage unbalance is reduced. To develop the control proposal, a model of the faulted system is presented in order to evaluate the stability of the closed‐loop system. A general modelling methodology is introduced in order to derive the control for any microgrid configuration. Finally, selected experimental results are reported in order to validate the effectiveness of the proposed control. [ABSTRACT FROM AUTHOR]

This document presents a novel methodology to optimize the power system frequency response based on the implementation of decentralized controllers. The proposed method focuses on the control of the internal rotor angle in the selected generator, which allows its governor to act as a decentralized controller that requires as input local measurements. Through a proposed optimization process, it is first possible to establish a set of optimal parameters for each controller and, second, to determine the required phasor measurement units (PMUs) and their locations that are necessary to be installed in a power system. This comprehensive proposal is based on the time domain evaluation of the frequency response when multiple scenarios of deviations between demand and generation occur. Finally, the new proposal is applied to the IEEE 39‐bus test system to validate its advantages; for this, the test power system as well as the proposed controllers are implemented in DIgSILENT PowerFactory, along with Python to manage the optimization process. [ABSTRACT FROM AUTHOR]

The advent of simultaneous wireless information and power (SWIPT) has been regarded as a promising technique to provide power supplies for an energy sustainable Internet of Things (IoT), which is of paramount importance due to the proliferation of high data communication demands of low-power network devices. In such networks, a multi-antenna base station (BS) in each cell can be utilized to concurrently transmit messages and energies to its intended IoT user equipment (IoT-UE) with a single antenna under a common broadcast frequency band, resulting in a multi-cell multi-input single-output (MISO) interference channel (IC). In this work, we aim to find the trade-off between the spectrum efficiency (SE) and energy harvesting (EH) in SWIPT-enabled networks with MISO ICs. For this, we derive a multi-objective optimization (MOO) formulation to obtain the optimal beamforming pattern (BP) and power splitting ratio (PR), and we propose a fractional programming (FP) model to find the solution. To tackle the nonconvexity of FP, an evolutionary algorithm (EA)-aided quadratic transform technique is proposed, which recasts the nonconvex problem as a sequence of convex problems to be solved iteratively. To further reduce the communication overhead and computational complexity, a distributed multi-agent learning-based approach is proposed that requires only partial observations of the channel state information (CSI). In this approach, each BS is equipped with a double deep Q network (DDQN) to determine the BP and PR for its UE with lower computational complexity based on the observations through a limited information exchange process. Finally, with the simulation experiments, we verify the trade-off between SE and EH, and we demonstrate that, apart from the FP algorithm introduced to provide superior solutions, the proposed DDQN algorithm also shows its performance gain in terms of utility to be up to 1.23-, 1.87-, and 3.45-times larger than the Advantage Actor Critic (A2C), greedy, and random algorithms, respectively, in comparison in the simulated environment. [ABSTRACT FROM AUTHOR]

This paper investigates the spectrum allocation and power control problems of Device-to-device enabled vehicular communications in a rapidly changing wireless channel environment. We model the above-mentioned issue as a multi-objective optimization problem to realize spectrum allocation and power control. To solve the problem, we proposed a multi-objective evolutionary algorithm. Firstly, we take the network capacity of vehicle-to-infrastructure links as the optimization objective to improve the network transmission rate while ensuring the reliability of all vehicle-to-vehicle links. Power consumption efficiency is then considered to control interference in the network and provide better energy efficiency. Computer numerical results show that our algorithm can obtain desirable solutions efficiently for various scenarios of spectrum allocation and power control in vehicular communications. [ABSTRACT FROM AUTHOR]

Summary: In recent years, many realistic wireless ad hoc networks (WANETs) have taken on three‐dimensional characteristics due to the implementation of various structures such as viaducts, tunnels, and overpasses. An increasing amount of work has also been devoted to studying the challenges posed by 3D vanet scenarios. And research on routing methods for 3D vanet scenarios is a hot topic. However, the three‐dimensional scene routing decision schemes have some problems, such as low data transmission efficiency, high energy consumption, and low end‐to‐end delays. Therefore, an energy efficiency optimization routing decision system is proposed based on the establishment of a three‐dimensional Voronoi polygon topology model. First, we define a node state‐related attribute parameter that determines whether the source node and the forward node are linked. The data forwarding node is determined by comparing attribute differences. Then, a power control mechanism based on received signal strength is proposed to solve the energy consumption, which includes deterministic and random parts. Finally, the specific state of the network node is monitored by comparing the attribute decision matrix to ensure basic maintenance of network operation and improve network transmission reliability. The simulation results show that the proposed scheme not only ensures the communication performance index in WANETs but also improves the reliability of the network. [ABSTRACT FROM AUTHOR]

Virtual synchronous generators (VSG) are considered a new generation of grid-friendly inverters with the same inertial support characteristics as synchronous generators (SG). However, the inertia support comes with the side effects of power and frequency response deterioration. The existing VSG power oscillation suppression methods have limitations such as complex controller parameter tuning, altering the frequency support characteristics, and power quality degradation. To address these issues, this paper proposes a universal VSG control strategy based on extended virtual inertia (VSG-EVI). Herein, the virtual inertia is no longer a constant or varying number; it is endowed with frequency domain characteristics to improve the VSG transient responses. Moreover, a detailed parameter design process is given in detail. Compared with the conventional VSG (CVSG), VSG-EVI significantly suppress the power and frequency oscillations. Compared with the existing VSG oscillation suppression methods, VSG-EVI addresses the issues of the reduction of frequency support capability, whereas the controller parametric design process is simplified with the proposed intuitive extended virtual inertia. Finally, the proposed VSG-EVI method is thoroughly validated by experiments under both grid-connected and stand-alone modes. [ABSTRACT FROM AUTHOR]

Computation of active and reactive powers is a crucial step in droop‐controlled single‐phase voltage source inverters (VSIs) in standalone microgrid since the performance and stability of the power‐sharing strategy are strongly influenced by its speed and accuracy, especially in the case of non‐linear loads. Here, an improved performance of power‐sharing among single‐phase droop‐controlled VSIs in an islanded microgrid, considering DC component and nonlinear loads is presented. To achieve this goal, an enhanced power‐sharing control scheme including a Multiple Enhanced Second‐Order Generalized Integrator Frequency‐Locked Loop (MESOGI‐FLL) for power calculation is proposed. As a result, the proposed power computation technique provides high rejection capability of DC component and current harmonics, hence, perfect estimation of the fundamental component of the inverter output current and its 90◦ phase‐shifted component. This strategy makes the power calculation method‐based control scheme immune to disturbance effects of the DC component and the high current harmonics. Detailed analysis, mathematical modelling of MESOGI, as well as a comparison with recent methods, are also provided. Simulation and experimental tests were carried out and the obtained results have shown the effectiveness and robustness of the proposed power‐sharing controller even under nonlinear load operating conditions. [ABSTRACT FROM AUTHOR]

Power control in an RS-coded orthogonal frequency division multiplex (OFDM) system with error-and-erasure correction decoding in Rayleigh fading channels was investigated. The power of each symbol within a codeword was controlled to reduce the codeword error rate (WER). Several RS-coded OFDM systems with power control are proposed. The WERs of the proposed systems as a function of the signal-to-noise ratio per bit were derived. We found that channel inversion at the transmitter in combination with the erasure generation by ordering fading amplitudes at the receiver provided the lowest WER among the considered systems. Furthermore, the erasure generation by ordering fading amplitudes was found to be better than the erasure generation by comparing fading amplitudes with a threshold. [ABSTRACT FROM AUTHOR]

Copyright of Steel Pipe is the property of Steel Pipe Magazine 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.)

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.)

A transformer‐less unified power flow controller (UPFC) is a power electronic device consisting of series and shunt voltage source converters (VSCs) that are not connected to a common DC bus. It can control power flow in medium voltage (MV) distribution networks without the need for interfacing transformers. Hence there is a significant reduction in size and cost compared to a conventional UPFC. This paper investigates the operating range of a transformer‐less UPFC in an MV distribution network and the required power ratings of the series and shunt converters. The results showed that a transformer‐less UPFC is able to provide active power control using partially rated converters. However, its ability to control reactive power is limited by the current ratings of the converters. The analysis was verified using software simulation and hardware experiment. [ABSTRACT FROM AUTHOR]

The co‐channel interference and frequent handoff are two important issues that have a great impact on the spectrum and energy efficiency in the non‐orthogonal multiple access (NOMA) with successive interference cancellation (SIC) in the small cell networks (SCN). This paper investigates the performance of SIC decoding order based on the users' channel state information (CSI) and random SIC decoding order under the perfect and imperfect conditions for the handoff optimization in SCNs with NOMA. The effect of SIC decoding order in the joint base station association and power control problem is studied by considering the motion of mobile users (MUs). Two optimization problems are formulated using the number of associated MUs, the number of handoffs, and the transmit power of all MUs, under the maximum allowable transmit power and minimum average‐rate constraints. Two objectives are combined into a single‐stage optimization problem through the weighted sum method. The formulated problem is solved using a game theory‐based algorithm and primal decomposition theory. The simulation results show that changing the SIC decoding order can lead to performance improvement in the uplink NOMA‐ based SCNs. Also, it is shown that the proposed algorithm can significantly reduce the frequent handoffs in small cell networks. [ABSTRACT FROM AUTHOR]

In grid-connected power generation systems, power factor fluctuations caused by non-linear power circuits used between the grid and source should be controlled with the help of voltage source inverters (VSI). In addition, in order to improve the quality of the electrical energy injected into the grid and to prevent possible electrical faults, the total harmonic distortion (THD) in the grid current should be controlled in accordance with IEEE-519 standards. In other respects, uncontrolled injected energy may causes losses, excessive electrical energy demand and overloading. In this study, an artificial neural network based active and reactive power control method is proposed for grid-connected single-phase Proton Exchange Membrane Hydrogen Fuel Cell (PEMFC). The aim of the proposed control structure is to have low harmonic distortion, high power factor performance as well as an easy and understandable structure. The proposed method was applied to a 6 kW prototype. Five different scenarios and nine different activation function were tried to verify the performance of the proposed control method. As a result of these processes, the power factor was measured as unity (>0.99) and the total harmonic distortion (THD) of the grid current, under all operation states, is <2%. In addition, it has been observed that the success rate of artificial neural networks is >97%. [Display omitted] • Modeling and computer application of single-phase grid-tied PEMFC circuit. • Implementing a two closed-loop pi-based control algorithm for DC-Link control. • Creation of intelligent control structure for active and reactive power control. • Ensuring high power factor regulation and low harmonic distortion performance. • Operating the system under variable conditions and different training functions. [ABSTRACT FROM AUTHOR]

Methods for controlling the electron beam power in a source based on a low-pressure arc discharge with layer stabilization of the emission plasma boundary are described. The control is carried out by the method of amplitude and latitude modulation within the duration of the submillisecond beam current pulse with a time resolution of 10 μs. Two ways to control the power of the electron beam are implemented: the first one is based on changing the concentration of the emission plasma by modulating the arc discharge current and the second method uses grid control (the mode of operation of the plasma triode) at the constant discharge current. Simplified diagrams of the power supply sources of the discharge and intergrid control voltage, typical oscillograms of the main currents of the discharge system, a graph of a quick-acting power change, and a control characteristic of a plasma triode are presented. [ABSTRACT FROM AUTHOR]

This paper considers a downlink resource-allocation problem in distributed interference orthogonal frequency-division multiple access (OFDMA) systems under maximal power constraints. As the upcoming fifth-generation (5G) wireless networks are increasingly complex and heterogeneous, it is challenging for resource allocation tasks to optimize the system performance metrics and guarantee user service requests simultaneously. Because of the non-convex optimization problems, using existing approaches to find the optimal resource allocation is computationally expensive. Recently, model-free reinforcement learning (RL) techniques have become alternative approaches in wireless networks to solve non-convex and NP-hard optimization problems. In this paper, we study a deep Q-learning (DQL)-based approach to address the optimization of transmit power control for users in multi-cell interference networks. In particular, we have applied a DQL algorithm for resource allocation to maximize the overall system throughput subject to the maximum power and SINR constraints in a flat frequency channel. We first formulate the optimization problem as a non-cooperative game model, where the multiple BSs compete for spectral efficiencies by improving their achievable utility functions while ensuring the quality of service (QoS) requirements to the corresponding receivers. Then, we develop a DRL-based resource allocation model to maximize the system throughput while satisfying the power and spectral efficiency requirements. In this setting, we define the state-action spaces and the reward function to explore the possible actions and learning outcomes. The numerical simulations demonstrate that the proposed DQL-based scheme outperforms the traditional model-based solution. [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.)

The upcoming wireless technology developments in the next generations are expected to substantially transform the vehicle-to-everything (V2X) communication network. The challenge of limited spectrum resources in V2X communication, caused by the need for high data rates, necessitates a thorough analysis of spectrum resource allocation and power control. This complex problem falls under the domain of mixed-integer nonlinear programming; a strategic approach is implemented to overcome these issues, which divides the main challenge into two sub-problems. The issue of resource allocation is addressed by implementing a multiaccess spectrum allocation method, which is deliberately designed to optimize the utilization of the spectrum resources that are currently accessible. Concurrently, the power control issue is resolved by employing a continuous convex approximation technique, which effectively converts non-convex power-allocation issues into convex equivalents. This approach helps to alleviate interference between users. Finally, the simulation results prove that the proposed approaches can improve vehicle performance. The algorithms proposed in this article significantly improve the system throughput and access rate of vehicular user equipment (VUEs) while ensuring the data rate of cellular user equipment (CUEs).

When marine animals and underwater acoustic sensor networks (UASNs) share spectrum resources, problems such as serious harm caused to marine animals by underwater acoustic systems and scarcity of underwater spectrum resources are encountered. To address these issues, a mammal-friendly underwater acoustic sensor network channel power allocation algorithm is proposed. Firstly, marine animals are treated as authorized users and sensor nodes as unauthorized users. Considering the interference level of sensor nodes on authorized users, this approach improves network service quality and achieves a mammal-friendly underwater communication mechanism. Secondly, to maximize the utility of unauthorized users, the algorithm incorporates a network interference level and node remaining energy into a game-theoretical framework. Using channel allocation and power control, a game model is constructed with a unique Nash equilibrium point. Finally, through simulation, it can be found that the proposed algorithm can obtain a stable optimal power value, and with the increase of network load, the system capacity of the proposed algorithm is significantly improved than that of the traditional cognitive radio technology and the common spectrum allocation algorithm, and the transmitted power of nodes can be controlled according to the size of the residual energy, so as to comprehensively improve the overall performance of the network.

Fast growing number of cellular telecommunication technology resulting on the increasing number of the user equipment. This condition increased the eNodeB load. To overcome this problem, the device-to-device (D2D) underlaying communication is introduced. In underlaying scheme, the D2D user equipment (DUE) will do the communication process using the same radio resources with the conventional cellular user equipment (CUE). To avoid a severe interference between these two types of user in the system, a good resource allocation is needed. In this work, a power control scheme using particle swarm optimization (PSO) is proposed, to manage the transmit power on each user on the system. The power control scheme take place after the greedy scheduling algorithm, after all user is given a resource block (RB) to do the communication process. The power transmit for each user is managed to reach a better system capacity, and to reduce the power consumed in one communication process. From the simulation, the PSO power control can improve the sumrate and spectral efficiency up to 12.97% and 3.38% respectively. The PSO power control also can reduce the power consumed by the system up to 8.84%. The fairness happens among the CUEs also can be maintained, despite of the decreasing fairness among DUEs.

Aiming at the optimization of uplink resource allocation in cognitive heterogeneous cellular networks, a resource allocation algorithm based on improved discrete mayfly algorithm was proposed.In the cognitive heterogeneous cellular network model, the power control strategy was introduced to control the interference suppression of transmitted power, and the improved discrete mayfly algorithm was used to optimize and solve the optimal distribution scheme based on the user’s quality of service (QoS) requirements and interference threshold constraints to maximize the energy efficiency (EE).In order to improve the convergence rate and search ability of the mayfly algorithm, the dynamic adaptive weights of incomplete Gamma and Beta distribution functions and the golden sine position updating strategy were introduced.The simulation results show that the closed-loop power control based on SINR can dynamically adjust the transmitting power of users and effectively restrain the interference between users.The GSWBMA has good optimization efficiency and convergence performance to solve the resource allocation problem, effectively improve the energy efficiency of the system and the transmission rate of users, and ensure the QoS requirements of users.

With the increase in the integration of renewable energy resources in the grid and ongoing growth in load demand worldwide, existing transmission lines are operating near their loading limits which may experience voltage collapse in a small disturbance. System stability and security can be improved when the closeness of the system to collapse is known. In this research, voltage stability of IEEE 30 bus test network is analyzed and assessed under continuously increasing load condition, utilizing the Critical Boundary Index (CBI); and improved with continuous integration of battery energy storage system (BESS). BESS is considered to be a hybrid combination of storage units and voltage source converter to have a controllable real and reactive power output. Security constraint optimal power flow is utilized for optimally sizing the installed BESS. It is evident from the outcome of the research that the voltage stability of the system is controlled to be above the acceptable range of 0.3 pu CBI in all lines and the system voltage is kept within the acceptable and constrained range of 0.9–1.1 pu.

Abstract In urban areas, the network operators deploy small-cell sites and install a large number of base stations to support densely populated cellular users. A similar small-cell deployment in rural areas is not feasible for the operators, as it will significantly increase the capital expenditure, and the return on the investment will also be comparatively lower. Hence, the most feasible way to provide cellular connectivity to rural areas is the deployment of large-cell sites. However, the technology developed for International Mobile Telecommunications (IMT)-Advanced standard (or 4G) was evaluated for an inter-site distance of 1.732 km, making the large-cell connectivity required for rural areas an afterthought. For cellular last-mile rural connectivity to be a reality through IMT-2020 (or 5G), the key is to have future technologies supporting large cells. In large-cell sites, the users experience comparatively more path loss, and thus, have poor signal coverage. Further, compared to downlink, the transmission power in uplink is limited, and therefore, uplink transmissions define the coverage of the communication system. Motivated by this, we propose several coverage solutions for uplink, considering an extremely large-cell site scenario. We initially analyze the received signal-to-noise ratio with 4G/5G systems at various distances based on the link budget evaluation. At larger inter-site distances, we show that it is infeasible to achieve cellular coverage with the current 4G/5G specifications. We then propose enhancements related to the waveform, modulation and coding schemes, resource allocation, and power control mechanisms. We evaluate the proposed enhancements through system- and link-level simulations, and show a significant improvement in the coverage for cell-edge users. We also show that our proposed enhancements achieve close to two times the improvement in the network capacity when compared to the currently available 5G specifications.

The fifth generation (5G) of wireless networks features three core use cases, namely ultra-reliable and low latency communications (URLLC), massive machine type communications (mMTC), and enhanced mobile broadband (eMBB). These use cases co-exist in many practical scenarios and compete for the same set of time and frequency resources, resulting in a natural trade-off in their performance. In this paper, a network supporting both URLLC and eMBB modes of operation is studied. To guarantee the ultra low latency requirement of URLLC, a dynamic resource allocation scheme indicated by a two-dimensional bitmap is proposed. This approach is capable to achieve finer granularity as well as lower false cancellation rate compared to the state-of-the-art methods. A novel power control and indication method is also proposed to dynamically provide different power control parameters to the user equipment (UE), while guaranteeing the reliability requirement of URLLC and minimizing the impact to eMBB. In addition, we devise a dynamic selection mechanism (DSM) to accommodate diverse scenarios, which is empowered with load prediction to become more intelligent. Our extensive system-level simulation results for eMBB-URLLC co-existence scenarios showcase that the perceived throughput of eMBB UEs is increased by 45.3%, while about 13.3% more UEs are enjoying URLLC services with at most 84% transmit power savings compared to the state-of-the-art methods.

This article presents an output power regulation system for micro fuel cells to help enhance the stability of the fuel cell in a portable micro power system. The structure of an MCU-controlled DC-DC converter is proposed. Then, the output characteristics of a selected fuel cell stack and the DC-DC converter’s power control functions are estimated by a system-level model. Based on the simulation results, the model provides a power regulation system which is implemented, and the test shows that it fulfills its intended function and the output power is regulated to a fixed level of 5 W–40 W with good efficiency.

This work presents a novel solution for accelerating the dynamic optimal power flow using a distributed‐memory parallelization approach. Unlike other two‐stage relaxation‐based approaches (such as ADMM), the proposed approach constructs the entire dynamic optimal power flow problem in parallel and solves it using a parallel primal‐dual interior point method with an iterative Krylov subspace linear solver with a block‐Jacobi preconditioning scheme. The parallel primal‐dual interior point method has been implemented in the open‐source portable, extensible toolkit for scientific computation (PETSc) library. The formulation, implementation, and numerical results on multicore computers to demonstrate the performance of the proposed approach on medium‐ to large‐scale networks with varying time horizons are presented. The results show that a significant speedup is achieved by using a block‐Jacobi preconditioner with an iterative Krylov subspace method for solving the dynamic optimal power flow problems. [ABSTRACT FROM AUTHOR]

Numerous studies have been undertaken to evaluate wind energy systems' active and reactive power control, the energy produced, and their its link to distribution networks. This research makes a novel contribution to the discipline in this setting. The novelty of this work aims to design a new wind emulator and design a power control approach for a doubly fed induction generator (DFIG)-based wind system. A description of the system was provided first. Secondly, the control strategy was described in detail. Then, it was applied to both converters (machine and grid sides). Three stages were used to evaluate the control solution: (1) a MATLAB/Simulink simulation to validate the reference's persistence (for both real and step wind speeds) and the system's robustness, (2) implementation in real-time on a dSPACE-DS1104 board linked to an experimental laboratory bench, and (3) overlapped comparison experimental and simulated data to conduct a thorough quantitative and qualitative analysis using the root-mean-square error measures. The simulation and experimental findings demonstrate that the suggested model is valid and presents an excellent correlation between experimental and simulated results regarding wind speed variation. [ABSTRACT FROM AUTHOR]

With the growing interest in owning electric vehicles due to increased environmental awareness and uncertain energy security together with the development of Li-ion batteries, quietness, and trouble-free operation, it is urgent to develop charging stations that are fast enough to supply the vehicles with energy conveniently, as in case of conventional petrol stations. The main reason that hinders the spread of fast charging stations is the installation cost, comprising the infrastructure and converter costs. In this article, a multiport DC-DC converter with differential power processing stages is proposed for Electric Vehicle (EV) fast charging stations, which results in a considerable reduction in the cost of using converters while achieving high efficiency. The proposed topology consists of two paths for the power flow (outer and inner loops) for EV battery charging with main and auxiliary DC-DC converters in the outer loop; all the ports are connected in series with the main supply, where the bulk power is being transferred. The main DC-DC converter injects a series voltage to control the power in the outer loop. The auxiliary DC-DC converters are rated at a fractional power that controls the partial power supplied to each port through the inner loops. Thanks to the fractional power processed by the auxiliary converter with the remaining power fed to the battery through the main converter, the proposed architecture enables simultaneous charging of multiple electric vehicles with better efficiency, lower cost, and the capability of providing a fault tolerance feature. A PWM control scheme for the converters to achieve bi-directional power flow in the partially rated DC-DC converters is discussed for the proposed system. Moreover, a practical down-scaled hardware prototype is designed to validate the functionality, control scheme, and effectiveness of the proposed topology in different case studies being investigated. The efficiency of the proposed converter is compared to the conventional configuration. [ABSTRACT FROM AUTHOR]

Distributed power generation plays a critical role in the stability and reliability of modern power systems. Due to the rapid growth of renewable energy generation, the requirements of the transmission and distribution system operators are becoming more stringent. Among these requirements, one of the most important is the Low-Voltage Ride-Through (LVRT) capability, which demands that the inverters remain connected to the grid and provide support during voltage sags. For this purpose, flexible current control algorithms stand out because they can manage unbalanced voltages and simultaneously achieve other control objectives. With the aim of presenting a concrete document focused on describing fundamental principles and discussing common design guidelines, this paper presents an overview of flexible current control strategies applied to LVRT capability. The operation features and design aspects of experiences reported in the literature are reviewed. Moreover, the paper proposes a general methodology to design LVRT flexible current control algorithms. Finally, current and future trends are discussed. [ABSTRACT FROM AUTHOR]

In this paper, an emergency ad‐hoc network based on cognitive radio is considered. It is assumed that secondary users (SUs) are moving agents in which some fixed agents namely distributed relays (DRs), forward the data gathered by SUs to destination. The main goal is to maximize the capacity of data gathering in destination with respect to the maximum interference tolerable by primary users (PU), and SU's and DR's power constraints. A mixed‐integer nonlinear model (MINLP) for joint relay assignment and power allocation is shown. Given that MINLP problems are NP‐Hard, a two interdependent solutions are proposed to achieve the relay assignment and power control. A social‐aware dynamic relay assignment algorithm (SADRA) based on many‐to‐one matching is proposed. In this matching, the preference list of DRs is the result of mean opinion scores ranking that two roulette wheel selection and random walk selection techniques are applied to eliminate the same priorities. In the second phase, a greedy adaptive algorithm for non‐convex power allocation problem that converges to the component‐wise minimal power is proposed. It is shown that the SADRA algorithm converges to a two‐sided exchange stable matching. The superior performance of the proposed SADRA algorithm is verified by the simulation results. [ABSTRACT FROM AUTHOR]

Induction heating appliance operation is constrained by the nonlinear pot material behavior under the generated magnetic field. The equivalent load seen by the inverter varies with the intensity of the field, meaning that this variation is dependent on the mains voltage. In flexible-surface induction cooktops, this fact is combined with a high coil number and different pots to be powered simultaneously, increasing the complexity to control the transmitted power while maintaining proper mains current consumption. In this article, two noncomplementary asymmetrical modulations with in-cycle parameter variation are proposed for improved power factor correction while avoiding the need for switching frequency variation and intermodulation noise in multiload systems. The proposed strategies are analyzed and experimentally tested using a 3.6 kW multi-inverter prototype featuring five induction coils. [ABSTRACT FROM AUTHOR]

Non-orthogonal multiple access (NOMA) has recently gained much research attention as a possible multiple access solution for fifth-generation (5G) wireless communication. The NOMA can further enhance spectral performance compared with orthogonal multiple access (OMA). This paper focuses on the joint optimization problem of power control and user grouping by considering the uplink NOMA system. The power control issues are solved using a linear programming approach and three alternative algorithms solve user grouping: Randomly, 2-Opt, and the Hybrid. The numerical results show that the proposed solution for power control and user-grouping achieves significant spectral performance compared to OMA and existing schemes reported in the literature with lower system complexity for uplink NOMA systems. [ABSTRACT FROM AUTHOR]

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