Network Planning and Coverage Optimization for Mobile Campus Networks

Abstract

The campus networks specified in 5G offer use-case tailored wireless communications that fulfills the demanding requirements of Industry 4.0 applications. Also agriculture and construction sites are fields of application that can benefit from the deployment of such networks. However, permanently installed campus networks do not match their requirements, as the network is needed only for certain time intervals and furthermore needs to be easily adaptable due to the time-varying nature of construction sites. Mobile campus networks (MCNs) solve this problem, as they can be deployed by a trailer in a short time and can be adjusted flexibly. Such MCNs require a very short and as much as possible automated planning and deployment procedure. Thus, conventional radio network planning (RNP) as it is applied for macro cells is too costly and time consuming, as it requires lots of manual effort and is not easily scalable. This paper presents an automated RNP framework for MCN based on MATLAB and WinProp, which optimizes the downlink coverage with one base station for several receiver heights that are relevant in an agricultural scenario. The proposed procedure also includes field measurements, which are intended to be executed by a drone. This allows a high flexibility in the selection of the measurement positions. An algorithm is developed that automates the environment-specific selection of measurement points and thus allows an efficient tuning of the propagation model. Subsequently, based on the measurements the propagation model is tuned and then used to recheck the results of the initial RNP. By applying another propagation model, real-world data are mimicked and the proposed algorithm is evaluated.