MmWave Vehicle-to-Infrastructure Communication :Analysis of Urban Microcellular Networks

2017PDFTech ReportD-STOP/2017/123DTRT13-G-UTC58Vehicle to roadside communicationsMobile communication systemsMillimeter wave communication systemsMillimeter wave devicesVehicle-to-infrastructure, V2I, millimeterwavemmWavebase stationpathlossTexasUnited StatesUniversity of Texas at Austin. Data-Supported Transportation Operations & Planning Center (D-STOP)Wang, YuyangUniversity of Texas at Austin. Data-Supported Transportation Operations & Planning Center (D-STOP)University Transportation Centers Program (U.S.)Heath, Robert W.US Transportation CollectionVehicle-to-infrastructure (V2I) communication may provide high data rates to vehicles via millimeterwave (mmWave) microcellular networks. This report 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 report, we use a pathloss model inspired by measurements, which uses a Manhattan distance model and accounts for differences in pathloss exponents and losses when turning corners. In our model, streets and base stations (BSs) are randomly located on a network formed by a two-dimensional Poisson line process. Our model is well suited for urban microcellular networks where the base stations 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. Second, there is an ultra-dense regime where deploying (active) BSs does not enhance coverage