Node positioning is a fundamental problem in applications of wireless sensor networks (WSNs). In this paper, a new range-free algorithm, called spring swarm localization algorithm (SSLA), is proposed for positioning W...Node positioning is a fundamental problem in applications of wireless sensor networks (WSNs). In this paper, a new range-free algorithm, called spring swarm localization algorithm (SSLA), is proposed for positioning WSNs. To determine the locations of sensor nodes, the proposed algorithm uses network topology information and a small fraction of sensor nodes which know their locations. Numerical simulations show that high positioning accuracy can be obtained by using the algorithm. Some examples are given to illustrate the effectiveness of the algorithm.展开更多
中国某海上气田新建的无人驻守井口平台与中心平台之间无海底光缆敷设,平台之间需传输DCS生产数据和关断、语音、视频等信号。为建立安全、可靠的通信链路,采用4 G TD-LTE无线传输技术进行组网。4 G TD-LTE技术目前已广泛应用于陆地油...中国某海上气田新建的无人驻守井口平台与中心平台之间无海底光缆敷设,平台之间需传输DCS生产数据和关断、语音、视频等信号。为建立安全、可靠的通信链路,采用4 G TD-LTE无线传输技术进行组网。4 G TD-LTE技术目前已广泛应用于陆地油田组网系统,技术和设备相对成熟,但在国内海上油气田尚未推广使用。通过比对单独敷设光缆和数字微波技术组网,4 G TD-LTE技术具有较好的价格优势与组网灵活性。经该海域某已建油田内部4G组网链路测试,得出4 G TD-LTE技术能够在海上建立稳定可靠的传输链路,满足油气田生产需要。展开更多
Link asymmetry in wireless mesh access networks(WMAN)of Mobile ad-hoc Networks(MANETs)is due mesh routers’transmission range.It is depicted as significant research challenges that pose during the design of network pro...Link asymmetry in wireless mesh access networks(WMAN)of Mobile ad-hoc Networks(MANETs)is due mesh routers’transmission range.It is depicted as significant research challenges that pose during the design of network protocol in wireless networks.Based on the extensive review,it is noted that the substantial link percentage is symmetric,i.e.,many links are unidirectional.It is identified that the synchronous acknowledgement reliability is higher than the asynchronous message.Therefore,the process of establishing bidirectional link quality through asynchronous beacons underrates the link reliability of asym-metric links.It paves the way to exploit an investigation on asymmetric links to enhance network functions through link estimation.Here,a novel Learning-based Dynamic Tree routing(LDTR)model is proposed to improve network performance and delay.For the evaluation of delay measures,asymmetric link,interference,probability of transmission failure is evaluated.The proportion of energy consumed is used for monitoring energy conditions based on the total energy capacity.This learning model is a productive way for resolving the routing issues over the network model during uncertainty.The asymmetric path is chosen to achieve exploitation and exploration iteratively.The learning-based Dynamic Tree routing model is utilized to resolve the multi-objective routing problem.Here,the simulation is done with MATLAB 2020a simulation environment and path with energy-efficiency and lesser E2E delay is evaluated and compared with existing approaches like the Dyna-Q-network model(DQN),asymmetric MAC model(AMAC),and cooperative asymmetric MAC model(CAMAC)model.The simulation outcomes demonstrate that the anticipated LDTR model attains superior network performance compared to others.The average energy consump-tion is 250 J,packet energy consumption is 6.5 J,PRR is 50 bits/sec,95%PDR,average delay percentage is 20%.展开更多
It is of great importance to control flexibly wireless links in the modern society,especially with the advent of the Internet of Things(IoT),fifth-generation communication(5G),and beyond.Recently,we have witnessed tha...It is of great importance to control flexibly wireless links in the modern society,especially with the advent of the Internet of Things(IoT),fifth-generation communication(5G),and beyond.Recently,we have witnessed that programmable metasurface(PM)or reconfigurable intelligent surface(RIS)has become a key enabling technology for manipulating flexibly the wireless link;however,one fundamental but challenging issue is to online design the PM's control sequence in a complicated wireless environment,such as the real-world indoor environment.Here,we propose a reinforcement learning(RL)approach to online control of the PM and thus in-situ improve the quality of the underline wireless link.We designed an inexpensive one-bit PM working at around 2.442 GHz and developed associated RL algorithms,and demonstrated experimentally that it is capable of enhancing the quality of commodity wireless link by a factor of about 10 dB and beyond in multiple scenarios,even if the wireless transmitter is in the glancing angle of the PM in the realworld indoor environment.Moreover,we also prove that our RL algorithm can be extended to improve the wireless signals of receivers in dual-receiver scenario.We faithfully expect that the presented technique could hold important potentials in future wireless communication,smart homes,and many other fields.展开更多
基金supported by the National Natural Science Foundation of China (Grant Nos. 10832006 and 60872093)
文摘Node positioning is a fundamental problem in applications of wireless sensor networks (WSNs). In this paper, a new range-free algorithm, called spring swarm localization algorithm (SSLA), is proposed for positioning WSNs. To determine the locations of sensor nodes, the proposed algorithm uses network topology information and a small fraction of sensor nodes which know their locations. Numerical simulations show that high positioning accuracy can be obtained by using the algorithm. Some examples are given to illustrate the effectiveness of the algorithm.
文摘中国某海上气田新建的无人驻守井口平台与中心平台之间无海底光缆敷设,平台之间需传输DCS生产数据和关断、语音、视频等信号。为建立安全、可靠的通信链路,采用4 G TD-LTE无线传输技术进行组网。4 G TD-LTE技术目前已广泛应用于陆地油田组网系统,技术和设备相对成熟,但在国内海上油气田尚未推广使用。通过比对单独敷设光缆和数字微波技术组网,4 G TD-LTE技术具有较好的价格优势与组网灵活性。经该海域某已建油田内部4G组网链路测试,得出4 G TD-LTE技术能够在海上建立稳定可靠的传输链路,满足油气田生产需要。
基金中国博士后科学基金资助项目(20110490389)东南大学移动通信国家重点实验室开放研究基金资助项目(2010D01)+5 种基金西安电子科技大学综合业务网理论及关键技术国家重点实验室开放研究基金资助项目(ISN12-11)区域光纤通信网与新型光通信系统国家重点实验室开放基金资助项目(2008SH06)Fundation of Graduate Innovation Center in NUAA(kfjj20110129)航空科学基金资助项目(2008195201420085552021)南京航空航天大学基本科研业务费专项基金资助项目(NS10097)
文摘Link asymmetry in wireless mesh access networks(WMAN)of Mobile ad-hoc Networks(MANETs)is due mesh routers’transmission range.It is depicted as significant research challenges that pose during the design of network protocol in wireless networks.Based on the extensive review,it is noted that the substantial link percentage is symmetric,i.e.,many links are unidirectional.It is identified that the synchronous acknowledgement reliability is higher than the asynchronous message.Therefore,the process of establishing bidirectional link quality through asynchronous beacons underrates the link reliability of asym-metric links.It paves the way to exploit an investigation on asymmetric links to enhance network functions through link estimation.Here,a novel Learning-based Dynamic Tree routing(LDTR)model is proposed to improve network performance and delay.For the evaluation of delay measures,asymmetric link,interference,probability of transmission failure is evaluated.The proportion of energy consumed is used for monitoring energy conditions based on the total energy capacity.This learning model is a productive way for resolving the routing issues over the network model during uncertainty.The asymmetric path is chosen to achieve exploitation and exploration iteratively.The learning-based Dynamic Tree routing model is utilized to resolve the multi-objective routing problem.Here,the simulation is done with MATLAB 2020a simulation environment and path with energy-efficiency and lesser E2E delay is evaluated and compared with existing approaches like the Dyna-Q-network model(DQN),asymmetric MAC model(AMAC),and cooperative asymmetric MAC model(CAMAC)model.The simulation outcomes demonstrate that the anticipated LDTR model attains superior network performance compared to others.The average energy consump-tion is 250 J,packet energy consumption is 6.5 J,PRR is 50 bits/sec,95%PDR,average delay percentage is 20%.
基金supported by the National Key Research and Development Program of China(2021YFA1401002,2017YFA0700201,2017YFA0700202 and 2017YFA0700203).
文摘It is of great importance to control flexibly wireless links in the modern society,especially with the advent of the Internet of Things(IoT),fifth-generation communication(5G),and beyond.Recently,we have witnessed that programmable metasurface(PM)or reconfigurable intelligent surface(RIS)has become a key enabling technology for manipulating flexibly the wireless link;however,one fundamental but challenging issue is to online design the PM's control sequence in a complicated wireless environment,such as the real-world indoor environment.Here,we propose a reinforcement learning(RL)approach to online control of the PM and thus in-situ improve the quality of the underline wireless link.We designed an inexpensive one-bit PM working at around 2.442 GHz and developed associated RL algorithms,and demonstrated experimentally that it is capable of enhancing the quality of commodity wireless link by a factor of about 10 dB and beyond in multiple scenarios,even if the wireless transmitter is in the glancing angle of the PM in the realworld indoor environment.Moreover,we also prove that our RL algorithm can be extended to improve the wireless signals of receivers in dual-receiver scenario.We faithfully expect that the presented technique could hold important potentials in future wireless communication,smart homes,and many other fields.
