Performance evaluation and optimization of long range IoT network using whale optimization algorithm

Apart from supporting the essential requirements of low power consumption in the IoT networks, Long Range (LoRa) technology provides wide-area coverage, and massive scalability at a low cost. The conventional LoRa network follows a single-hop approach, which may lead to greater path loss and rapid battery depletion thereby rendering low coverage and connectivity. In this work, a dual-hop LoRa technology incorporating cooperative communication is presented and a mathematical framework has been formulated in terms of received power and signal-to-noise ratio (SNR). Further, outage probability, spectral efficiency and throughput are computed under the Rayleigh fading channel to explore the proposed LoRa network performance. A critical comparative analysis of the dual-hop LoRa network with the conventional single-hop LoRa network has been done. Evaluation reveals 75%, 62% and 70% improvement in the outage probability, spectral efficiency and throughput respectively by incorporating a cooperative scenario in the LoRa network. In addition, to enhance the performance of the LoRa nodes in both cooperative as well as non-cooperative scenarios, a metaheuristic optimization approach known as the whale optimization algorithm (WOA) is utilized. Based on the mathematical model, an optimization problem is defined whose solution gives the optimal transmission parameters to maximize the received power. The performance metrics evaluated utilizing the optimized solution discovered using WOA demonstrate the improved performance of the LoRa nodes in both the cooperative as well as non-cooperative scenarios.