IEEE Transactions on Vehicular Technology · 2018 · 116 citations · 29 references
EngineeringElectrical EngineeringPropagationStochastic ModelingWireless CommunicationsFree-space PropagationPropagation ModelingSimulation MethodsStochastic NetworksWireless Channel ModelingWireless NetworksNon-line-of-sight CommunicationPoisson Point ProcessesPropagation CharacterizationSignal Propagation ModelingStatistical Propagation ModelsUrban Propagation ModelingVehicle-to-infrastructure CommunicationWireless Network Models
Vehicle-to-infrastructure (V2I) communication may provide high data rates to vehicles via millimeter-wave (mmWave) microcellular networks. This paper uses stochastic geometry to analyze the coverage of urban mmWave microcellular networks. Prior work used a pathloss model with a line-of-sight probability function based on randomly oriented buildings, to determine whether a link was line-of-sight or non-line-of-sight. In this paper, we use a pathloss model inspired by measurements, which uses a Manhattan distance pathloss model and accounts for differences in pathloss exponents and losses when turning corners. In our model, streets are randomly located as a Manhattan poisson line process and the base stations (BSs) are distributed according to a Poisson point process. Our model is well suited for urban microcellular networks where the BSs are deployed at street level. Based on this new approach, we derive the coverage probability under certain BS association rules to obtain closed-form solutions without much complexity. In addition, we draw two main conclusions from our work. First, non-line-of-sight BSs are not a major benefit for association or source of interference most of the time. Second, there is an ultra-dense regime where deploying active BSs does not enhance coverage.
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