Spreading Factor Allocation using the Standard Deviation Classification Method

This paper proposes the standard deviation (SD) classification method to improve the long range wide area network (LoRaWAN) resource allocation. The proposed method distributes spreading factors (SFs) by considering means and standard deviations of receive signal strength indicator (RSSI) values of the end devices. The simulation is performed for a rural environment whose signal propagation characteristics are governed by the Hata-Okumura propagation model. It is shown that the SD classification method distributes more SFs to the end devices and clearly offers higher data extraction rate (DER) than that of the original adaptive data rate (ADR) scheme.