Location information plays an important role in most of the applications in Wireless Sensor Network(WSN).Recently,many localization techniques have been proposed,while most of these deals with two Dimensional applicat...Location information plays an important role in most of the applications in Wireless Sensor Network(WSN).Recently,many localization techniques have been proposed,while most of these deals with two Dimensional applications.Whereas,in Three Dimensional applications the task is complex and there are large variations in the altitude levels.In these 3D environments,the sensors are placed in mountains for tracking and deployed in air for monitoring pollution level.For such applications,2D localization models are not reliable.Due to this,the design of 3D localization systems in WSNs faces new challenges.In this paper,in order to find unknown nodes in Three-Dimensional environment,only single anchor node is used.In the simulation-based environment,the nodes with unknown locations are moving at middle&lower layers whereas the top layer is equipped with single anchor node.A novel soft computing technique namely Adaptive Plant Propagation Algorithm(APPA)is introduced to obtain the optimized locations of these mobile nodes.Thesemobile target nodes are heterogeneous and deployed in an anisotropic environment having an Irregularity(Degree of Irregularity(DOI))value set to 0.01.The simulation results present that proposed APPAalgorithm outperforms as tested among other meta-heuristic optimization techniques in terms of localization error,computational time,and the located sensor nodes.展开更多
Many extensive UAV communication networks have used UAV cooperative control.Wireless networking services can be offered using unmanned aerial vehicles(UAVs)as aerial base stations.Not only is coverage maximization,but...Many extensive UAV communication networks have used UAV cooperative control.Wireless networking services can be offered using unmanned aerial vehicles(UAVs)as aerial base stations.Not only is coverage maximization,but also better connectivity,a fundamental design challenge that must be solved.The number of applications for unmanned aerial vehicles(UAVs)operating in unlicensed bands is fast expanding as the Internet of Things(IoT)develops.Those bands,however,have become overcrowded as the number of systems that use them grows.Cognitive Radio(CR)and spectrum allocation approaches have emerged as a potential approach for resolving spectrum scarcity in wireless networks,and hence as technological solutions for future generations,from this perspective.As a result,combining CR with UAVs has the potential to give significant benefits for large-scale UAV deployment.The paper examines existing research on the subject of UAV covering and proposes a multi-UAV cognitive-based error-free model for energy-efficient communication.Coverage maximization,power control,and enhanced connection quality are the three steps of the proposed model.To satisfy the desired signal-to-noise ratio,the covering zone efficacy is investigated as a function of the distance among UAVs stationed in a specific geographic region depending on multiple deployment configurations like as rural,suburban,and urban macro deployment scenarios of the ITU-R M.2135 standard(SNR).展开更多
基金This research was supported by X-mind Corps program of National Research Foundation of Korea(NRF)funded by the Ministry of Science,ICT(No.2019H1D8A1105622)and the Soonchunhyang University Research Fund.
文摘Location information plays an important role in most of the applications in Wireless Sensor Network(WSN).Recently,many localization techniques have been proposed,while most of these deals with two Dimensional applications.Whereas,in Three Dimensional applications the task is complex and there are large variations in the altitude levels.In these 3D environments,the sensors are placed in mountains for tracking and deployed in air for monitoring pollution level.For such applications,2D localization models are not reliable.Due to this,the design of 3D localization systems in WSNs faces new challenges.In this paper,in order to find unknown nodes in Three-Dimensional environment,only single anchor node is used.In the simulation-based environment,the nodes with unknown locations are moving at middle&lower layers whereas the top layer is equipped with single anchor node.A novel soft computing technique namely Adaptive Plant Propagation Algorithm(APPA)is introduced to obtain the optimized locations of these mobile nodes.Thesemobile target nodes are heterogeneous and deployed in an anisotropic environment having an Irregularity(Degree of Irregularity(DOI))value set to 0.01.The simulation results present that proposed APPAalgorithm outperforms as tested among other meta-heuristic optimization techniques in terms of localization error,computational time,and the located sensor nodes.
基金Ahmed Alhussen would like to thank the Deanship of Scientific Research at Majmaah University for supporting this work under Project No.R-2022-193.
文摘Many extensive UAV communication networks have used UAV cooperative control.Wireless networking services can be offered using unmanned aerial vehicles(UAVs)as aerial base stations.Not only is coverage maximization,but also better connectivity,a fundamental design challenge that must be solved.The number of applications for unmanned aerial vehicles(UAVs)operating in unlicensed bands is fast expanding as the Internet of Things(IoT)develops.Those bands,however,have become overcrowded as the number of systems that use them grows.Cognitive Radio(CR)and spectrum allocation approaches have emerged as a potential approach for resolving spectrum scarcity in wireless networks,and hence as technological solutions for future generations,from this perspective.As a result,combining CR with UAVs has the potential to give significant benefits for large-scale UAV deployment.The paper examines existing research on the subject of UAV covering and proposes a multi-UAV cognitive-based error-free model for energy-efficient communication.Coverage maximization,power control,and enhanced connection quality are the three steps of the proposed model.To satisfy the desired signal-to-noise ratio,the covering zone efficacy is investigated as a function of the distance among UAVs stationed in a specific geographic region depending on multiple deployment configurations like as rural,suburban,and urban macro deployment scenarios of the ITU-R M.2135 standard(SNR).
