With the rapid development of emerging 5G and beyond(B5G),Unmanned Aerial Vehicles(UAVs)are increasingly important to improve the performance of dense cellular networks.As a conventional metric,coverage probability ha...With the rapid development of emerging 5G and beyond(B5G),Unmanned Aerial Vehicles(UAVs)are increasingly important to improve the performance of dense cellular networks.As a conventional metric,coverage probability has been widely studied in communication systems due to the increasing density of users and complexity of the heterogeneous environment.In recent years,stochastic geometry has attracted more attention as a mathematical tool for modeling mobile network systems.In this paper,an analytical approach to the coverage probability analysis of UAV-assisted cellular networks with imperfect beam alignment has been proposed.An assumption was considered that all users are distributed according to Poisson Cluster Process(PCP)around base stations,in particular,Thomas Cluster Process(TCP).Using thismodel,the impact of beam alignment errors on the coverage probabilitywas investigated.Initially,the ProbabilityDensity Function(PDF)of directional antenna gain between the user and its serving base station was obtained.Then,association probability with each tier was achieved.A tractable expression was derived for coverage probability in both Line-of-Sight(LoS)andNon-Line-of-Sight(NLoS)condition links.Numerical results demonstrated that at low UAVs altitude,beam alignment errors significantly degrade coverage performance.Moreover,for a small cluster size,alignment errors do not necessarily affect the coverage performance.展开更多
Despite the expanded efforts,the vehicular ad-hoc networks(VANETs)are still facing many challenges such as network performances,network scalability and context-awareness.Many solutions have been proposed to overcome t...Despite the expanded efforts,the vehicular ad-hoc networks(VANETs)are still facing many challenges such as network performances,network scalability and context-awareness.Many solutions have been proposed to overcome these obstacles,and the edge computing,an extension of the cloud computing,is one of them.With edge computing,communication,storage and computational capabilities are brought closer to end users.This could offer many benefits to the global vehicular network including,for example,lower latency,network off-loading and context-awareness(location,environment factors,etc.).Different approaches of edge computing have been developed:mobile edge computing(MEC),fog computing(FC)and cloudlet are the main ones.After introducing the vehicular environment background,this paper aims to study and compare these different technologies.For that purpose their main features are compared and the state-of-the-art applications in VANETs are analyzed.In addition,MEC,FC,and cloudlet are classified and their suitability level is debated for different types of vehicular applications.Finally,some challenges and future research directions in the fields of edge computing and VANETs are discussed.展开更多
基金supported by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2022R323)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia,and Taif University Researchers Supporting Project Number TURSP-2020/34,Taif,Saudi Arabia.
文摘With the rapid development of emerging 5G and beyond(B5G),Unmanned Aerial Vehicles(UAVs)are increasingly important to improve the performance of dense cellular networks.As a conventional metric,coverage probability has been widely studied in communication systems due to the increasing density of users and complexity of the heterogeneous environment.In recent years,stochastic geometry has attracted more attention as a mathematical tool for modeling mobile network systems.In this paper,an analytical approach to the coverage probability analysis of UAV-assisted cellular networks with imperfect beam alignment has been proposed.An assumption was considered that all users are distributed according to Poisson Cluster Process(PCP)around base stations,in particular,Thomas Cluster Process(TCP).Using thismodel,the impact of beam alignment errors on the coverage probabilitywas investigated.Initially,the ProbabilityDensity Function(PDF)of directional antenna gain between the user and its serving base station was obtained.Then,association probability with each tier was achieved.A tractable expression was derived for coverage probability in both Line-of-Sight(LoS)andNon-Line-of-Sight(NLoS)condition links.Numerical results demonstrated that at low UAVs altitude,beam alignment errors significantly degrade coverage performance.Moreover,for a small cluster size,alignment errors do not necessarily affect the coverage performance.
文摘Despite the expanded efforts,the vehicular ad-hoc networks(VANETs)are still facing many challenges such as network performances,network scalability and context-awareness.Many solutions have been proposed to overcome these obstacles,and the edge computing,an extension of the cloud computing,is one of them.With edge computing,communication,storage and computational capabilities are brought closer to end users.This could offer many benefits to the global vehicular network including,for example,lower latency,network off-loading and context-awareness(location,environment factors,etc.).Different approaches of edge computing have been developed:mobile edge computing(MEC),fog computing(FC)and cloudlet are the main ones.After introducing the vehicular environment background,this paper aims to study and compare these different technologies.For that purpose their main features are compared and the state-of-the-art applications in VANETs are analyzed.In addition,MEC,FC,and cloudlet are classified and their suitability level is debated for different types of vehicular applications.Finally,some challenges and future research directions in the fields of edge computing and VANETs are discussed.
