Optimization of Spreading Factor Distribution in High Density LoRa Networks

Abstract

LoRa is a promising wireless technology for various sensing and positioning applications in Smart Cities. LoRa uses Chirp Spread Spectrum (CSS) with different Spreading Factors (SF) to handle varying intensities of multipath reflections and interference. However, the standard LoRaWAN uses the pure ALOHA algorithm that suffers from both Intra-SF collisions and Inter-SF collisions which limit it to mostly low density environment. In this work, we optimize the transmission parameters of a LoRaWAN system in high density Smart City traffic environment using golden section search and parabolic interpolation. Our approach of optimum distribution of spreading factors not only significantly improves the success rate, but also enable more nodes to use lower spreading which results in lower delay.