UAV-Enabled Hardware-Impaired Spatially Correlated Cell-Free Massive MIMO Systems: Analysis and Energy Efficiency Optimization

We consider a cell-free (CF) massive multi-input multi-output (mMIMO) system, where multi-antenna access points (APs) serve single-antenna unmanned aerial vehicles (UAVs) and ground users (GUEs). We assume, unlike the existing CF mMIMO literature, hardware-impaired UAVs and GUEs, which observe a mixture of spatially-correlated Rician- and Rayleigh-faded channels while communicating with hardware-impaired APs. We derive a closed-form downlink spectral efficiency (SE) expression by using practical models for the channel mixture, and by considering channel estimation errors. We propose a novel block quadratic transformation (block-QT) technique to optimize non-convex network-centric global energy efficiency (GEE) by appropriately modeling circuit, UAV propulsion and fronthaul powers. The novel block-QT approach combines block optimization and quadratic transformation technique to decompose GEE optimization into simpler convex sub-problems. We numerically show that i) it is better to operate a UAV at a larger height when it has severe hardware impairments; and ii) when UAVs operate at a lower height, they do not significantly affect the SE of GUEs.