2D Versus 3D Geometric Modelling for Massive Access Networks in 5G-IoT Applications
| Autor: | Bisma Manzoor, Karina Gomez Chavez, Sithamparanathan Kandeepan, Akram Al-Hourani, Ming Ding |
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| Rok vydání: | 2018 |
| Předmět: |
Access network
Computer science Stochastic modelling Distributed computing 020206 networking & telecommunications 020207 software engineering 02 engineering and technology Solid modeling Geometric networks Base station Geometric design 0202 electrical engineering electronic engineering information engineering Stochastic geometry 5G |
| Zdroj: | ICSPCS |
| DOI: | 10.1109/icspcs.2018.8631746 |
| Popis: | With the advent of Internet of Things (IoT) more devices are connecting to the network. As such, a robust network is required to properly deal with this huge traffic. The Fifth Generation (5G) technology is anticipated to have capability of handling huge data generated by massive number of devices. In the literature, most of the geometric network models that have been proposed are in two dimensions (2D). This paper focuses on modelling networks that considers massive number of devices (IoT-devices) in three dimensions (3D) using the tools of stochastic modelling. The location of the devices and Base Stations (BS) in terms of third dimension is considered using the distribution of heights of buildings put forth by ITU - R. Additionally, 3D coverage probability of the dense network for Melbourne Central Business District (CBD) is analysed and compared with 2D simulations. Our results show that it is important to model IoT-based networks taking into account heights of nodes, as there is a significant shift in contact distances in 3D as compared to 2D. This sequentially proves to have a considerable effect on the cellular characteristics such as coverage probability. |
| Databáze: | OpenAIRE |
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