Multi-UAV Aided Millimeter-Wave Networks: Positioning, Clustering, and Beamforming

In this paper, we propose to employ multiple unmanned aerial vehicle (UAV) base stations to serve ground users in the millimeter-wave (mmWave) frequency bands. To improve the spectrum efficiency, uniform planar arrays are equipped at the UAVs and users for compensation of the high path loss and for mitigation of interference. We formulate a problem to jointly optimize the UAV positioning, user clustering, and hybrid analog-digital beamforming (BF) for the maximization of user achievable sum rate (ASR), subject to a minimum rate constraint for each user. Since the problem is highly non-convex and involves high-dimensional variable matrices and combinatorial programming variables, we develop a suboptimal solution via alternating optimization, successive convex optimization, and combinatorial optimization. First, we design the UAV positioning and user clustering under the assumption of ideal beam patterns, which significantly decouples the UAV positioning and directional BF. Then, the transmit and receive BF variables are successively optimized to approach the ideal beam patterns. Our simulation results verify the convergence and superiority of the proposed algorithm. Significant performance gains can be obtained compared to some benchmark schemes in terms of the ASR, and the proposed hybrid BF solution closely approaches a performance bound given by fully-digital BF.

Automated summary

This paper proposes the use of multiple unmanned aerial vehicle (UAV) base stations to serve ground users in the millimeter-wave frequency bands. It formulates a problem to optimize UAV positioning, user clustering, and hybrid analog-digital beamforming for maximizing user achievable sum rate. A suboptimal solution is developed using alternating optimization, successive convex optimization, and combinatorial optimization. The proposed algorithm outperforms benchmark schemes and closely approaches the performance bound of fully-digital beamforming.