Energy Efficient Resource Allocation for Uplink LoRa Networks

In this paper, we investigate energy efficiency for uplink LoRa, which is one of the most promising and widely deployed low-power wide-area (LPWA) networks. In the considered networks, we explore user scheduling, spreading factor (SF) assignment, and power allocation jointly. A nonconvex optimization problem for maximizing the system energy efficiency is formulated, with targeted SNR requirement and power range as constraints for each LoRa user. To solve this problem, we first propose a low-complexity suboptimal algorithm, which includes energy-efficient user scheduling and heuristic SF assignment for scheduled users based on matching theory. Then a novel power allocation based on Charnes-Cooper transformation is proposed to transform the fractional objective into the convex form to maximize the system energy efficiency. Simulation results show that the proposed algorithms achieve near-optimal performance in terms of energy efficiency.