In power communication networks, it is a challenge to decrease the risk of different services efficiently to improve operation reliability. One of the important factor in reflecting communication risk is service route...In power communication networks, it is a challenge to decrease the risk of different services efficiently to improve operation reliability. One of the important factor in reflecting communication risk is service route distribution. However, existing routing algorithms do not take into account the degree of importance of services, thereby leading to load unbalancing and increasing the risks of services and networks. A routing optimization mechanism based on load balancing for power communication networks is proposed to address the abovementioned problems. First, the mechanism constructs an evaluation model to evaluate the service and network risk degree using combination of devices, service load, and service characteristics. Second, service weights are determined with modified relative entropy TOPSIS method, and a balanced service routing determination algorithm is proposed. Results of simulations on practical network topology show that the mechanism can optimize the network risk degree and load balancing degree efficiently.展开更多
The power communication network can be abstracted as a graph based on its topology. In this paper, we propose an approach to conduct simulations of power communication network based on its graph representation. In par...The power communication network can be abstracted as a graph based on its topology. In this paper, we propose an approach to conduct simulations of power communication network based on its graph representation. In particular, the nodes and edges in the graph refer to the ports and channels in the grid topology. Different applications on the grid can be transformed into queries over the graph. Hence, in this paper, we build our grid simulation model based on the Neo4 j graph database. We also propose a fault extension algorithm based on predicate calculus. Our experiment evaluations show that the proposed approach can effectively improve the efficiency of the power grid.展开更多
The main function of the power communication business is to monitor,control and manage the power communication network to ensure normal and stable operation of the power communication network.Commu-nication services r...The main function of the power communication business is to monitor,control and manage the power communication network to ensure normal and stable operation of the power communication network.Commu-nication services related to dispatching data networks and the transmission of fault information or feeder automation have high requirements for delay.If processing time is prolonged,a power business cascade reaction may be triggered.In order to solve the above problems,this paper establishes an edge object-linked agent business deployment model for power communication network to unify the management of data collection,resource allocation and task scheduling within the system,realizes the virtualization of object-linked agent computing resources through Docker container technology,designs the target model of network latency and energy consumption,and introduces A3C algorithm in deep reinforcement learning,improves it according to scene characteristics,and sets corresponding optimization strategies.Mini-mize network delay and energy consumption;At the same time,to ensure that sensitive power business is handled in time,this paper designs the business dispatch model and task migration model,and solves the problem of server failure.Finally,the corresponding simulation program is designed to verify the feasibility and validity of this method,and to compare it with other existing mechanisms.展开更多
A wireless powered communication network(WPCN)assisted by intelligent reflecting surface(IRS)is proposed in this paper,which can transfer information by non-orthogonal multiple access(NOMA)technology.In the system,in ...A wireless powered communication network(WPCN)assisted by intelligent reflecting surface(IRS)is proposed in this paper,which can transfer information by non-orthogonal multiple access(NOMA)technology.In the system,in order to ensure that the hybrid access point(H-AP)can correctly decode user information via successive interference cancellation(SIC)technology,the information transmit power of user needs to satisfy a certain threshold,so as to meet the corresponding SIC constraints.Therefore,when the number of users who transfer information simultaneously increases,the system performance will be greatly restricted.To minimize the influence of SIC constraints on system performance,users are firstly clustered,and then each cluster collects energy from H-AP and finally,users transfer information based on NOMA with the assistance of IRS.Specifically,this paper aims to maximize the sum throughput of the system by jointly optimizing the beamforming of IRS and resource allocation of the system.The semi-definite relaxation(SDR)algorithm is employed to alternately optimize the beamforming of IRS in each time slot,and the joint optimization problem about user’s transmit power and time is transformed into two optimal time allocation sub-problems.The numerical results show that the proposed optimization scheme can effectively improve the sum throughput of the system.In addition,the results in the paper further reveals the positive impact of IRS on improving the sum throughput of the system.展开更多
In this paper,we investigate the effective deployment of millimeter wave(mmWave)in unmanned aerial vehicle(UAV)-enabled wireless powered communication network(WPCN).In particular,a novel framework for optimizing the p...In this paper,we investigate the effective deployment of millimeter wave(mmWave)in unmanned aerial vehicle(UAV)-enabled wireless powered communication network(WPCN).In particular,a novel framework for optimizing the performance of such UAV-enabled WPCN in terms of system throughput is proposed.In the considered model,multiple UAVs monitor in the air along the scheduled flight trajectory and transmit monitoring data to micro base stations(mBSs)with the harvested energy via mmWave.In this case,we propose an algorithm for jointly optimizing transmit power and energy transfer time.To solve the non-convex optimization problem with tightly coupled variables,we decouple the problem into more tractable subproblems.By leveraging successive convex approximation(SCA)and block coordinate descent techniques,the optimal solution is obtained by designing a two-stage joint iteration optimization algorithm.Simulation results show that the proposed algorithm with joint transmit power and energy transfer time optimization achieves significant performance gains over Q-learning method and other benchmark schemes.展开更多
New energy power generation equipment has the characteristics of diurnal, perturbative, seasonal, and periodic power generation, which makes new power optical communication network(POCN) more dynamic and changeable. T...New energy power generation equipment has the characteristics of diurnal, perturbative, seasonal, and periodic power generation, which makes new power optical communication network(POCN) more dynamic and changeable. This is directly reflected in the dynamics of the link risk and service importance of the POCN. In this paper, aiming at the problem of the dynamic importance of service in POCN, and the resulting power optical communication network reliability decline problem, a new energy POCN dynamic routing intelligence algorithm based on service importance prediction is proposed. Based on the short-term power generation of new energy power station, the importance of each service and the risk degree of each link are predicted. Link weights are dynamically adjusted, and k-shortest path(KSP) algorithm is used to calculate route results. When network resources are insufficient, low-importance services can give way to prevent a large number of high-importance services from being blocked. Simulation results show that compared with the traditional KSP algorithm, the prediction-based dynamic routing intelligent(P-DRI) algorithm can reduce the service blocking probability by 55.59%, and reduce the average importance of blocking services by 44.77% at the cost of about 6.17% of the calculation delay.展开更多
The recent aggrandizement of radio frequency(RF)signals in wireless power transmission combined with energy harvesting methods have led to the replacement of traditional battery-powered wireless networks since the blo...The recent aggrandizement of radio frequency(RF)signals in wireless power transmission combined with energy harvesting methods have led to the replacement of traditional battery-powered wireless networks since the blooming RF technology provides energy renewal of wireless devices with the quality of service(QoS).In addition,it does not require any unnecessary alterations on the transmission hardware side.A hybridized global optimization technique uniting Global best and Local best(GL)based particle swarm optimization(PSO)and ant colony optimization(ACO)is proposed in this paper to optimally allocate resources in wireless powered communication networks(WPCN)through coordinated operation of communication groups,in which the wireless energy transfer and information sharing take place concomitantly by the aid of a cooperative relay positioned in between the communicating groups.The designed algorithm assists in minimizing power consumption and maximizes the weighted sum rate at the end-user side.Thus the principal target of the system is coordinated optimization of energy beamforming along with time and energy allocation to reduce the total energy consumed combined with assured information rates of the communication groups.Numerical outputs are presented to manifest the proposed system’s performance to verify the analytical results via simulations.展开更多
This paper considers a wireless powered communication network(WPC network, WPCN) based on non-orthogonal multiple access(NOMA) technology aided by intelligent reflective surfaces(IRS). WPCN mainly focuses on downlink ...This paper considers a wireless powered communication network(WPC network, WPCN) based on non-orthogonal multiple access(NOMA) technology aided by intelligent reflective surfaces(IRS). WPCN mainly focuses on downlink energy transfer(ET) and uplink information transmission(IT). At the ET phase, a dedicated multi-antenna power station(PS) is equipped to supply power to users with the assistance of IRS, and at the IT phase, the IRS adjusts the phase to assist the user in applying NOMA technology to transmit information to the base station(BS), thus minimizing the impact of dynamic IRS on the system. Based on the above settings, the maximization of sum-throughput of the system under this working mode is studied. Due to the non-convexity of maximization problem of the sum-throughput of this system, block coordinate descent(BCD) technology is applied for alternative optimization of each system block by semidefinite relaxation(SDR) and particle swarm optimization(PSO) respectively. The numerical results show that compared with baseline scheme, the proposed optimization scheme can provide greater sum-throughput of the system.展开更多
基金supported by the State Grid project which names the simulation and service quality evaluation technology research of power communication network(No.XX71-14-046)
文摘In power communication networks, it is a challenge to decrease the risk of different services efficiently to improve operation reliability. One of the important factor in reflecting communication risk is service route distribution. However, existing routing algorithms do not take into account the degree of importance of services, thereby leading to load unbalancing and increasing the risks of services and networks. A routing optimization mechanism based on load balancing for power communication networks is proposed to address the abovementioned problems. First, the mechanism constructs an evaluation model to evaluate the service and network risk degree using combination of devices, service load, and service characteristics. Second, service weights are determined with modified relative entropy TOPSIS method, and a balanced service routing determination algorithm is proposed. Results of simulations on practical network topology show that the mechanism can optimize the network risk degree and load balancing degree efficiently.
基金supported by the Science and Technology Project of State Grid Corporation of China(Grant No.5211XT17001N)
文摘The power communication network can be abstracted as a graph based on its topology. In this paper, we propose an approach to conduct simulations of power communication network based on its graph representation. In particular, the nodes and edges in the graph refer to the ports and channels in the grid topology. Different applications on the grid can be transformed into queries over the graph. Hence, in this paper, we build our grid simulation model based on the Neo4 j graph database. We also propose a fault extension algorithm based on predicate calculus. Our experiment evaluations show that the proposed approach can effectively improve the efficiency of the power grid.
基金funded by the“Research on Digitization and Intelligent Application of Low-Voltage Power Distribution Equipment”[SGSDDK00PDJS2000375]。
文摘The main function of the power communication business is to monitor,control and manage the power communication network to ensure normal and stable operation of the power communication network.Commu-nication services related to dispatching data networks and the transmission of fault information or feeder automation have high requirements for delay.If processing time is prolonged,a power business cascade reaction may be triggered.In order to solve the above problems,this paper establishes an edge object-linked agent business deployment model for power communication network to unify the management of data collection,resource allocation and task scheduling within the system,realizes the virtualization of object-linked agent computing resources through Docker container technology,designs the target model of network latency and energy consumption,and introduces A3C algorithm in deep reinforcement learning,improves it according to scene characteristics,and sets corresponding optimization strategies.Mini-mize network delay and energy consumption;At the same time,to ensure that sensitive power business is handled in time,this paper designs the business dispatch model and task migration model,and solves the problem of server failure.Finally,the corresponding simulation program is designed to verify the feasibility and validity of this method,and to compare it with other existing mechanisms.
基金supported by the Key Scientific and Technological Projects in Henan Province(202102310560)。
文摘A wireless powered communication network(WPCN)assisted by intelligent reflecting surface(IRS)is proposed in this paper,which can transfer information by non-orthogonal multiple access(NOMA)technology.In the system,in order to ensure that the hybrid access point(H-AP)can correctly decode user information via successive interference cancellation(SIC)technology,the information transmit power of user needs to satisfy a certain threshold,so as to meet the corresponding SIC constraints.Therefore,when the number of users who transfer information simultaneously increases,the system performance will be greatly restricted.To minimize the influence of SIC constraints on system performance,users are firstly clustered,and then each cluster collects energy from H-AP and finally,users transfer information based on NOMA with the assistance of IRS.Specifically,this paper aims to maximize the sum throughput of the system by jointly optimizing the beamforming of IRS and resource allocation of the system.The semi-definite relaxation(SDR)algorithm is employed to alternately optimize the beamforming of IRS in each time slot,and the joint optimization problem about user’s transmit power and time is transformed into two optimal time allocation sub-problems.The numerical results show that the proposed optimization scheme can effectively improve the sum throughput of the system.In addition,the results in the paper further reveals the positive impact of IRS on improving the sum throughput of the system.
文摘In this paper,we investigate the effective deployment of millimeter wave(mmWave)in unmanned aerial vehicle(UAV)-enabled wireless powered communication network(WPCN).In particular,a novel framework for optimizing the performance of such UAV-enabled WPCN in terms of system throughput is proposed.In the considered model,multiple UAVs monitor in the air along the scheduled flight trajectory and transmit monitoring data to micro base stations(mBSs)with the harvested energy via mmWave.In this case,we propose an algorithm for jointly optimizing transmit power and energy transfer time.To solve the non-convex optimization problem with tightly coupled variables,we decouple the problem into more tractable subproblems.By leveraging successive convex approximation(SCA)and block coordinate descent techniques,the optimal solution is obtained by designing a two-stage joint iteration optimization algorithm.Simulation results show that the proposed algorithm with joint transmit power and energy transfer time optimization achieves significant performance gains over Q-learning method and other benchmark schemes.
基金supported by the National Natural Science Foundation of China(62021005).
文摘New energy power generation equipment has the characteristics of diurnal, perturbative, seasonal, and periodic power generation, which makes new power optical communication network(POCN) more dynamic and changeable. This is directly reflected in the dynamics of the link risk and service importance of the POCN. In this paper, aiming at the problem of the dynamic importance of service in POCN, and the resulting power optical communication network reliability decline problem, a new energy POCN dynamic routing intelligence algorithm based on service importance prediction is proposed. Based on the short-term power generation of new energy power station, the importance of each service and the risk degree of each link are predicted. Link weights are dynamically adjusted, and k-shortest path(KSP) algorithm is used to calculate route results. When network resources are insufficient, low-importance services can give way to prevent a large number of high-importance services from being blocked. Simulation results show that compared with the traditional KSP algorithm, the prediction-based dynamic routing intelligent(P-DRI) algorithm can reduce the service blocking probability by 55.59%, and reduce the average importance of blocking services by 44.77% at the cost of about 6.17% of the calculation delay.
文摘The recent aggrandizement of radio frequency(RF)signals in wireless power transmission combined with energy harvesting methods have led to the replacement of traditional battery-powered wireless networks since the blooming RF technology provides energy renewal of wireless devices with the quality of service(QoS).In addition,it does not require any unnecessary alterations on the transmission hardware side.A hybridized global optimization technique uniting Global best and Local best(GL)based particle swarm optimization(PSO)and ant colony optimization(ACO)is proposed in this paper to optimally allocate resources in wireless powered communication networks(WPCN)through coordinated operation of communication groups,in which the wireless energy transfer and information sharing take place concomitantly by the aid of a cooperative relay positioned in between the communicating groups.The designed algorithm assists in minimizing power consumption and maximizes the weighted sum rate at the end-user side.Thus the principal target of the system is coordinated optimization of energy beamforming along with time and energy allocation to reduce the total energy consumed combined with assured information rates of the communication groups.Numerical outputs are presented to manifest the proposed system’s performance to verify the analytical results via simulations.
基金supported by the Key Scientific and Technological Projects in Henan Province (202102310560)the Basic Scientific Research Operating Expenses of Henan Polytechnic University (NSFRF180309)。
文摘This paper considers a wireless powered communication network(WPC network, WPCN) based on non-orthogonal multiple access(NOMA) technology aided by intelligent reflective surfaces(IRS). WPCN mainly focuses on downlink energy transfer(ET) and uplink information transmission(IT). At the ET phase, a dedicated multi-antenna power station(PS) is equipped to supply power to users with the assistance of IRS, and at the IT phase, the IRS adjusts the phase to assist the user in applying NOMA technology to transmit information to the base station(BS), thus minimizing the impact of dynamic IRS on the system. Based on the above settings, the maximization of sum-throughput of the system under this working mode is studied. Due to the non-convexity of maximization problem of the sum-throughput of this system, block coordinate descent(BCD) technology is applied for alternative optimization of each system block by semidefinite relaxation(SDR) and particle swarm optimization(PSO) respectively. The numerical results show that compared with baseline scheme, the proposed optimization scheme can provide greater sum-throughput of the system.
