Analysis and performance optimization of LoRa network using the CE & SC hybrid approach

Abstract

In this research, we assess the impact of collisions produced by simultaneous transmission using the same Spreading Factor (SF) and over the same channel in LoRa networks, demonstrating that such collisions significantly impair LoRa network performance. We quantify the network performance advantages by combining the primary characteristics of the Capture Effect (CE) and Signature Code (SC) approaches. The system is analyzed using a Markov chain model, which allows us to construct the mathematical formulation for the performance measures. Our numerical findings reveal that the proposed approach surpasses the standard LoRa in terms of network throughput and transmitted packet latency.