In this paper,we develop a 6G wireless powered Internet of Things(IoT)system assisted by unmanned aerial vehicles(UAVs)to intelligently supply energy and collect data at the same time.In our dual-UAV scheme,UAV-E,with...In this paper,we develop a 6G wireless powered Internet of Things(IoT)system assisted by unmanned aerial vehicles(UAVs)to intelligently supply energy and collect data at the same time.In our dual-UAV scheme,UAV-E,with a constant power supply,transmits energy to charge the IoT devices on the ground,whereas UAV-B serves the IoT devices by data collection as a base station.In this framework,the system's energy efficiency is maximized,which we define as a ratio of the sum rate of IoT devices to the energy consumption of two UAVs during a fixed working duration.With the constraints of duration,transmit power,energy,and mobility,a difficult non-convex issue is presented by optimizing the trajectory,time duration allocation,and uplink transmit power of concurrently.To tackle the non-convex fractional optimization issue,we deconstruct it into three subproblems and we solve each of them iteratively using the descent method in conjunction with sequential convex approximation(SCA)approaches and the Dinkelbach algorithm.The simulation findings indicate that the suggested cooperative design has the potential to greatly increase the energy efficiency of the 6G intelligent UAV-assisted wireless powered IoT system when compared to previous benchmark systems.展开更多
Unmanned Aerial Vehicles(UAVs)integrated with Wireless Sensor Networks(WSNs)present a transformative approach to environmental monitoring by enabling real-time,low power,wide-area,and high-resolution data collection.T...Unmanned Aerial Vehicles(UAVs)integrated with Wireless Sensor Networks(WSNs)present a transformative approach to environmental monitoring by enabling real-time,low power,wide-area,and high-resolution data collection.This paper proposes a UAV-based WSN framework designed for efficient ecological data acquisition,including parameters such as temperature,humidity,various gases,detection of motion of a material,and safety features.The system leverages UAVs for dynamic deployment and data retrieval from distributed sensor nodes in remote or inaccessible areas,reducing the reliance on fixed infrastructure.Long Range Communication(LoRa)technology is also integrated with a WSN to enhance network coverage and adaptability issues.The proposed system covers vast areas through LoRa communication ensuring minimal energy consumption and cost-effective sensing capabilities.Field tests and simulation findings show how well the system captures spatiotemporal environmental fluctuations,making it an invaluable tool for monitoring climate change,ecological research,and disaster response.展开更多
This paper investigates a wireless powered and backscattering enabled sensor network based on the non-linear energy harvesting model, where the power beacon(PB) delivers energy signals to wireless sensors to enable th...This paper investigates a wireless powered and backscattering enabled sensor network based on the non-linear energy harvesting model, where the power beacon(PB) delivers energy signals to wireless sensors to enable their passive backscattering and active transmission to the access point(AP). We propose an efficient time scheduling scheme for network performance enhancement, based on which each sensor can always harvest energy from the PB over the entire block except its time slots allocated for passive and active information delivery. Considering the PB and wireless sensors are from two selfish service providers, we use the Stackelberg game to model the energy interaction among them. To address the non-convexity of the leader-level problem, we propose to decompose the original problem into two subproblems and solve them iteratively in an alternating manner. Specifically, the successive convex approximation, semi-definite relaxation(SDR) and variable substitution techniques are applied to find a nearoptimal solution. To evaluate the performance loss caused by the interaction between two providers, we further investigate the social welfare maximization problem. Numerical results demonstrate that compared to the benchmark schemes, the proposed scheme can achieve up to 35.4% and 38.7% utility gain for the leader and the follower, respectively.展开更多
In order to satisfy the ever-increasing energy appetite of the massive battery-powered and batteryless communication devices,radio frequency(RF)signals have been relied upon for transferring wireless power to them.The...In order to satisfy the ever-increasing energy appetite of the massive battery-powered and batteryless communication devices,radio frequency(RF)signals have been relied upon for transferring wireless power to them.The joint coordination of wireless power transfer(WPT)and wireless information transfer(WIT)yields simultaneous wireless information and power transfer(SWIPT)as well as data and energy integrated communication network(DEIN).However,as a promising technique,few efforts are invested in the hardware implementation of DEIN.In order to make DEIN a reality,this paper focuses on hardware implementation of a DEIN.It firstly provides a brief tutorial on SWIPT,while summarising the latest hardware design of WPT transceiver and the existing commercial solutions.Then,a prototype design in DEIN with full protocol stack is elaborated,followed by its performance evaluation.展开更多
Since power of a wireless sensor node is limited, low power communication technology has been required. M-ary frequency shift keying (MFSK) modulation with orthogonal signals is one of the methods to decrease the powe...Since power of a wireless sensor node is limited, low power communication technology has been required. M-ary frequency shift keying (MFSK) modulation with orthogonal signals is one of the methods to decrease the power. However, if the amount of transmitted data including such as an identification number (ID) of a node and measured data is small, a ratio of the data length to the total packet length, which means transmission efficiency, becomes quite low. Because a preamble and error check codes are generally added to a packet for synchronization between a transmitter and a receiver and for decrease in reception errors, respectively. In this research, we have developed a method with digital filters which eliminates the other signals from time series frequency spectra not to use a preamble and error check codes. Although estimated synchronization loss of the method was less than 1.6 dB, it was found that the loss of the method on error packet rate was almost 0 dB at more than 0.001 of packet error rate by a simulation made by BASIC. These results indicate a possibility to realize that a packet which consists of only two symbols can be received with no error if the transmitted data is less than 14 bits using 128-FSK.展开更多
This paper investigates a wireless powered communication network(WPCN)facilitated by an unmanned aerial vehicle(UAV)in Internet of Things(IoT)networks,where multiple IoT devices(IoTDs)gather energy from a terrestrial ...This paper investigates a wireless powered communication network(WPCN)facilitated by an unmanned aerial vehicle(UAV)in Internet of Things(IoT)networks,where multiple IoT devices(IoTDs)gather energy from a terrestrial energy station(ES)during the wireless energy transfer(WET)stage,followed by the UAV collecting data from these powered IoTDs with the time division multiple access(TDMA)protocol in the wireless information transfer(WIT)stage.To overcome the challenges of radio propagation caused by obstructions,we incorporate a reconfigurable intelligent surface(RIS)to enhance the link quality of the ES-IoTDs and IoTDs-UAV.The primary objective is to maximize the average sum rate of all IoTDs by jointly optimizing UAV trajectory,ES transmit power,and RIS phase shifts,along with the time allocation for WET and WIT.To this end,we reformulate the optimization problem as a markov decision process(MDP)and introduce a deep reinforcement learning(DRL)approach for addressing the formulated problem,called the proximal policy optimization(PPO)based energy harvesting with trajectory design and phase shift optimization(PPO-EHTDPS)algorithm.By continuously exploring within the environment,the PPO algorithm refines its policy to optimize the UAV trajectory,the energy phase shifts,ES transmit power,and WET/WIT time allocation.Additionally,a continuous phase shift optimization algorithm is employed to determine the information phase shifts for each IoTD to maximize average sum rate.Finally,numerical results demonstrate that the proposed PPOEHTDPS algorithm can significantly achieve higher average sum rate and show better convergence performance over the benchmark algorithms.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
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 propose an active reconfigurable intelligent surface(RIS)enabled hybrid relaying scheme for a multi-antenna wireless powered communication network(WPCN),where the active RIS is employed to assist both...In this paper,we propose an active reconfigurable intelligent surface(RIS)enabled hybrid relaying scheme for a multi-antenna wireless powered communication network(WPCN),where the active RIS is employed to assist both wireless energy transfer(WET)from the power station(PS)to energyconstrained users and wireless information transmission(WIT)from users to the receiving station(RS).For further performance enhancement,we propose to employ both transmit beamforming at the PS and receive beamforming at the RS.We formulate a sumrate maximization problem by jointly optimizing the RIS phase shifts and amplitude reflection coefficients for both the WET and the WIT,transmit and receive beamforming vectors,and network resource allocation.To solve this non-convex problem,we propose an efficient alternating optimization algorithm with the linear minimum mean squared error criterion,semidefinite relaxation(SDR)and successive convex approximation techniques.Specifically,the tightness of applying the SDR is proved.Simulation results demonstrate that our proposed scheme with 10 reflecting elements(REs)and 4 antennas can achieve 17.78%and 415.48%performance gains compared to the single-antenna scheme with 10 REs and passive RIS scheme with 100 REs,respectively.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
无线供电通信网络(Wireless-powered Communication Network,WPCN)不仅可以实现远程无线充电而且能够提供无线通信服务,因此受到了学术界和工业界的广泛关注。然而,低效率的能量收集和信息传输会限制WPCN的性能,并且在WPCN中的双重远近...无线供电通信网络(Wireless-powered Communication Network,WPCN)不仅可以实现远程无线充电而且能够提供无线通信服务,因此受到了学术界和工业界的广泛关注。然而,低效率的能量收集和信息传输会限制WPCN的性能,并且在WPCN中的双重远近效应会导致物联网设备收集的能量与消耗的能量之间的不平衡。为了解决这些问题,提出基于能量回收的主动智能反射面(Intelligent Reflecting Surface,IRS)辅助WPCN波束成形算法,其中物联网设备既能从功率站端收集能量,还能从其他物联网设备的上行信息传输中回收能量。考虑能量收集、吞吐量、时间分配,以及功率站和主动IRS的最大功率等约束,基于能量回收机制,建立了系统总吞吐量最大化的资源分配模型;然后,提出一种基于内层近似和双线性变换的交替优化算法进行求解。仿真结果表明,在相应的参数配置下,能量回收机制的应用能够提升约8.13%的吞吐量,而主动IRS的应用能够提升约61.1%的吞吐量。展开更多
基金supported by the Natural Science Foundation of Beijing Municipality under Grant L192034。
文摘In this paper,we develop a 6G wireless powered Internet of Things(IoT)system assisted by unmanned aerial vehicles(UAVs)to intelligently supply energy and collect data at the same time.In our dual-UAV scheme,UAV-E,with a constant power supply,transmits energy to charge the IoT devices on the ground,whereas UAV-B serves the IoT devices by data collection as a base station.In this framework,the system's energy efficiency is maximized,which we define as a ratio of the sum rate of IoT devices to the energy consumption of two UAVs during a fixed working duration.With the constraints of duration,transmit power,energy,and mobility,a difficult non-convex issue is presented by optimizing the trajectory,time duration allocation,and uplink transmit power of concurrently.To tackle the non-convex fractional optimization issue,we deconstruct it into three subproblems and we solve each of them iteratively using the descent method in conjunction with sequential convex approximation(SCA)approaches and the Dinkelbach algorithm.The simulation findings indicate that the suggested cooperative design has the potential to greatly increase the energy efficiency of the 6G intelligent UAV-assisted wireless powered IoT system when compared to previous benchmark systems.
文摘Unmanned Aerial Vehicles(UAVs)integrated with Wireless Sensor Networks(WSNs)present a transformative approach to environmental monitoring by enabling real-time,low power,wide-area,and high-resolution data collection.This paper proposes a UAV-based WSN framework designed for efficient ecological data acquisition,including parameters such as temperature,humidity,various gases,detection of motion of a material,and safety features.The system leverages UAVs for dynamic deployment and data retrieval from distributed sensor nodes in remote or inaccessible areas,reducing the reliance on fixed infrastructure.Long Range Communication(LoRa)technology is also integrated with a WSN to enhance network coverage and adaptability issues.The proposed system covers vast areas through LoRa communication ensuring minimal energy consumption and cost-effective sensing capabilities.Field tests and simulation findings show how well the system captures spatiotemporal environmental fluctuations,making it an invaluable tool for monitoring climate change,ecological research,and disaster response.
基金supported by National Natural Science Foundation of China(No.61901229 and No.62071242)the Project of Jiangsu Engineering Research Center of Novel Optical Fiber Technology and Communication Network(No.SDGC2234)+1 种基金the Open Research Project of Jiangsu Provincial Key Laboratory of Photonic and Electronic Materials Sciences and Technology(No.NJUZDS2022-008)the Post-Doctoral Research Supporting Program of Jiangsu Province(No.SBH20).
文摘This paper investigates a wireless powered and backscattering enabled sensor network based on the non-linear energy harvesting model, where the power beacon(PB) delivers energy signals to wireless sensors to enable their passive backscattering and active transmission to the access point(AP). We propose an efficient time scheduling scheme for network performance enhancement, based on which each sensor can always harvest energy from the PB over the entire block except its time slots allocated for passive and active information delivery. Considering the PB and wireless sensors are from two selfish service providers, we use the Stackelberg game to model the energy interaction among them. To address the non-convexity of the leader-level problem, we propose to decompose the original problem into two subproblems and solve them iteratively in an alternating manner. Specifically, the successive convex approximation, semi-definite relaxation(SDR) and variable substitution techniques are applied to find a nearoptimal solution. To evaluate the performance loss caused by the interaction between two providers, we further investigate the social welfare maximization problem. Numerical results demonstrate that compared to the benchmark schemes, the proposed scheme can achieve up to 35.4% and 38.7% utility gain for the leader and the follower, respectively.
基金financial support of National Natural Science Foundation of China(NSFC),No.U1705263 and 61971102GF Innovative Research Programthe Sichuan Science and Technology Program,No.2019YJ0194。
文摘In order to satisfy the ever-increasing energy appetite of the massive battery-powered and batteryless communication devices,radio frequency(RF)signals have been relied upon for transferring wireless power to them.The joint coordination of wireless power transfer(WPT)and wireless information transfer(WIT)yields simultaneous wireless information and power transfer(SWIPT)as well as data and energy integrated communication network(DEIN).However,as a promising technique,few efforts are invested in the hardware implementation of DEIN.In order to make DEIN a reality,this paper focuses on hardware implementation of a DEIN.It firstly provides a brief tutorial on SWIPT,while summarising the latest hardware design of WPT transceiver and the existing commercial solutions.Then,a prototype design in DEIN with full protocol stack is elaborated,followed by its performance evaluation.
文摘Since power of a wireless sensor node is limited, low power communication technology has been required. M-ary frequency shift keying (MFSK) modulation with orthogonal signals is one of the methods to decrease the power. However, if the amount of transmitted data including such as an identification number (ID) of a node and measured data is small, a ratio of the data length to the total packet length, which means transmission efficiency, becomes quite low. Because a preamble and error check codes are generally added to a packet for synchronization between a transmitter and a receiver and for decrease in reception errors, respectively. In this research, we have developed a method with digital filters which eliminates the other signals from time series frequency spectra not to use a preamble and error check codes. Although estimated synchronization loss of the method was less than 1.6 dB, it was found that the loss of the method on error packet rate was almost 0 dB at more than 0.001 of packet error rate by a simulation made by BASIC. These results indicate a possibility to realize that a packet which consists of only two symbols can be received with no error if the transmitted data is less than 14 bits using 128-FSK.
文摘This paper investigates a wireless powered communication network(WPCN)facilitated by an unmanned aerial vehicle(UAV)in Internet of Things(IoT)networks,where multiple IoT devices(IoTDs)gather energy from a terrestrial energy station(ES)during the wireless energy transfer(WET)stage,followed by the UAV collecting data from these powered IoTDs with the time division multiple access(TDMA)protocol in the wireless information transfer(WIT)stage.To overcome the challenges of radio propagation caused by obstructions,we incorporate a reconfigurable intelligent surface(RIS)to enhance the link quality of the ES-IoTDs and IoTDs-UAV.The primary objective is to maximize the average sum rate of all IoTDs by jointly optimizing UAV trajectory,ES transmit power,and RIS phase shifts,along with the time allocation for WET and WIT.To this end,we reformulate the optimization problem as a markov decision process(MDP)and introduce a deep reinforcement learning(DRL)approach for addressing the formulated problem,called the proximal policy optimization(PPO)based energy harvesting with trajectory design and phase shift optimization(PPO-EHTDPS)algorithm.By continuously exploring within the environment,the PPO algorithm refines its policy to optimize the UAV trajectory,the energy phase shifts,ES transmit power,and WET/WIT time allocation.Additionally,a continuous phase shift optimization algorithm is employed to determine the information phase shifts for each IoTD to maximize average sum rate.Finally,numerical results demonstrate that the proposed PPOEHTDPS algorithm can significantly achieve higher average sum rate and show better convergence performance over the benchmark algorithms.
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 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.
基金supported in part by the National Natural Science Foundation of China (No.62071242 and No.61901229)in part by the Postgraduate Research&Practice Innovation Program of Jiangsu Province(No.KYCX22 0967)in part by the Open Research Project of Jiangsu Provincial Key Laboratory of Photonic and Electronic Materials Sciences and Technology (No.NJUZDS2022-008)
文摘In this paper,we propose an active reconfigurable intelligent surface(RIS)enabled hybrid relaying scheme for a multi-antenna wireless powered communication network(WPCN),where the active RIS is employed to assist both wireless energy transfer(WET)from the power station(PS)to energyconstrained users and wireless information transmission(WIT)from users to the receiving station(RS).For further performance enhancement,we propose to employ both transmit beamforming at the PS and receive beamforming at the RS.We formulate a sumrate maximization problem by jointly optimizing the RIS phase shifts and amplitude reflection coefficients for both the WET and the WIT,transmit and receive beamforming vectors,and network resource allocation.To solve this non-convex problem,we propose an efficient alternating optimization algorithm with the linear minimum mean squared error criterion,semidefinite relaxation(SDR)and successive convex approximation techniques.Specifically,the tightness of applying the SDR is proved.Simulation results demonstrate that our proposed scheme with 10 reflecting elements(REs)and 4 antennas can achieve 17.78%and 415.48%performance gains compared to the single-antenna scheme with 10 REs and passive RIS scheme with 100 REs,respectively.
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.
文摘无线供电通信网络(Wireless-powered Communication Network,WPCN)不仅可以实现远程无线充电而且能够提供无线通信服务,因此受到了学术界和工业界的广泛关注。然而,低效率的能量收集和信息传输会限制WPCN的性能,并且在WPCN中的双重远近效应会导致物联网设备收集的能量与消耗的能量之间的不平衡。为了解决这些问题,提出基于能量回收的主动智能反射面(Intelligent Reflecting Surface,IRS)辅助WPCN波束成形算法,其中物联网设备既能从功率站端收集能量,还能从其他物联网设备的上行信息传输中回收能量。考虑能量收集、吞吐量、时间分配,以及功率站和主动IRS的最大功率等约束,基于能量回收机制,建立了系统总吞吐量最大化的资源分配模型;然后,提出一种基于内层近似和双线性变换的交替优化算法进行求解。仿真结果表明,在相应的参数配置下,能量回收机制的应用能够提升约8.13%的吞吐量,而主动IRS的应用能够提升约61.1%的吞吐量。
