Channel Estimation for UAV-based mmWave Massive MIMO Communications with Beam Squint

Abstract

The incorporation of UAVs in 5G and envisioned 6G wireless communication systems is considered for many applications and use-cases, either as part of the infrastructure, providing coverage and connectivity (e.g., during unforeseen and rare events) or as an end-user, e.g., in remote sensing, real-time monitoring and surveillance, to name a few. From the perspective of the physical layer and the involved signal processing algorithms, the transmission environment between the UAVs and the ground communication devices, along with the utilisation of massive MIMO in the mmWave spectrum, require new channel estimation algorithms to support the required physical layer functionality. In this paper, the problem of channel estimation in a multi-user, UAV-based mmWave massive MIMO system is considered in view of the so-called beam squint effect as well as the time-varying nature of the involved channels due to mobility. The proposed approach takes advantage of the low-rank channel matrix and solves a minimisation problem via ADMM, leading to a low complexity, iterative algorithm. The performance of the proposed algorithm is evaluated via simulations and its efficacy is demonstrated over other algorithms from the relevant literature.