Resource Management in Energy Harvesting Powered LoRa Wireless Networks

Abstract

Long Range (LoRa) wireless networks, which is made up of low-powered connected devices, is a key technology for next generation wireless networks that support internet of things applications. Specifically, LoRa devices (LDs) may be powered by energy harvesting sources for greening wireless communications systems. Furthermore, LoRa modulation is based on the chirp spreading modulation (CSM) which consists of assigning various orthogonal spreading factors (SFs) among the LDs in the network. Hence, this paper investigates energy-efficient resource allocation in LoRa wireless networks, where the LDs are powered by independent energy harvesting sources. First, the problem of maximizing the number of scheduled LDs under quality of service constraints and making use of the available harvested energy, is formulated. Next, the relationship between the assigned SF, the instantaneous channel coefficients and the available energy at the batteries is analytically established. Hence, the optimal energy management, device scheduling, and SF assignment algorithm is proposed. Simulations results shows that the proposed resource allocation approaches offer efficient use of renewable energy which allows to enhance the rate of successful transmissions.