SINR Prediction in Presence of Correlated Shadowing in Cellular Networks

Abstract

Signal-to-interference-plus-noise ratio (SINR) evaluates the quality of the link between the base station (BS) and the user equipment (UE), taking into account the interference coming from neighboring cells and the thermal noise. Predicting the SINR with good accuracy ensures proper planning and optimization of radio coverage and good estimation of end-user throughput. In this paper, SINR is predicted at any user location based on UE geo-located measurements, using the Kriging technique and assuming that the received signals from serving and interfering cells undergo shadowing fading. Unlike previous works where only the prediction of the received powers is studied, the current functionality also considers the prediction error on the received signals. We consider both spatial correlation of shadowing signals for each cell and also inter-cell correlation and we propose a new model to generate multiple links shadowing signals for the downlink of cellular networks. For validation, we perform Monte-Carlo network simulations in which the shadowing samples are generated based on the proposed model. Results show a good prediction accuracy of the SINR at a new location resulting in a good estimation of the end-user perceived average data rate.