Optimization of Multi-UAV-BS Aided Millimeter-Wave Massive MIMO Networks

• Published in: IEEE Global Communications Conference (Online) pp. 1 - 6
• Main Authors: Zhu, Lipeng, Zhang, Jun, Xiao, Zhenyu, Schober, Robert
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.12.2020
• Subjects: Analog-digital conversion; Array signal processing; Autonomous aerial vehicles; Benchmark testing; hybrid beamforming; Massive MIMO; Millimeter wave communication; millimeter-wave; Optimization; positioning; Simulation; Transmission line matrix methods; UAV communication; Upper bound; user assignment
• ISSN: 2576-6813
• DOI: 10.1109/GLOBECOM42002.2020.9348170

In this paper, we investigate millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) networks with multiple unmanned aerial vehicle (UAV) mounted base stations (BSs). Uniform planar arrays are equipped at the UAV-BSs to perform hybrid analog-digital beamforming (BF) for compensation of the high path loss of mmWave channels and for mitigation of intra-cell and/or inter-cell interference. We jointly optimize the UAV-BS positioning, user assignment, and hybrid BF for maximization of the achievable sum rate (ASR) of the users, subject to a minimum rate constraint for each user. A sub-optimal solution for the resulting high-dimensional and non-convex problem is developed by exploiting alternating optimization, successive convex optimization, and combinatorial optimization. Our simulation results verify the convergence of the proposed algorithm and demonstrate significant performance gains compared to two benchmark schemes in terms of the ASR.