Discrete Particle Swarm Optimization Based Antenna Selection for MIMO LoRa IoT Systems

In recent years, as one of the most efficient low power wide area network (LPWAN) techniques, long range (LoRa) has been widely employed in the internet of things (IoT) applications due to its wide coverage and high interference resistance. In this paper, a multiple-input multiple-output (MIMO) LoRa system is proposed for further enhancing the performance of LoRa based IoT systems, where correlated channel environment is considered between the LoRa gateway and the node. More explicitly, the multi-antenna gateway employs LoRa modulation and the signals are precoded by space-time block coding for long-range and reliable data transmission in LPWAN. Moreover, since power consumption is a key point to consider in LPWAN, we further propose a discrete particle swarm optimization based antenna selection (DPSOBAS) algorithm for the MIMO LoRa system to reduce the hardware costs and power consumption, while retaining the MIMO advantages. The corresponding simulation results show that the proposed DPSOBAS is capable of substantially improving the performance of the proposed MIMO LoRa IoT system in correlated channel environment, and approaching the performance of ergodic search based optimal AS scheme with significantly lower computational complexity.