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In this paper, we propose to deploy multiple unmanned aerial vehicle (UAV)mounted base stations to serve ground users in outdoor environments withobstacles. In particular, the geographic information is employed to capture theblockage effects for air-to-ground (A2G) links caused by buildings, and arealistic blockage-aware A2G channel model is proposed to characterize thecontinuous variation of the channels at different locations. Based on theproposed channel model, we formulate the joint optimization problem of UAVthree-dimensional (3-D) positioning and resource allocation, by powerallocation, user association, and subcarrier allocation, to maximize theminimum achievable rate among users. To solve this non-convex combinatorialprogramming problem, we introduce a penalty term to relax it and develop asuboptimal solution via a penalty-based double-loop iterative optimizationframework. The inner loop solves the penalized problem by employing the blocksuccessive convex approximation (BSCA) technique, where the UAV positioning andresource allocation are alternately optimized in each iteration. The outer loopaims to obtain proper penalty multipliers to ensure the solution of thepenalized problem converges to that of the original problem. Simulation resultsdemonstrate the superiority of the proposed algorithm over other benchmarkschemes in terms of the minimum achievable rate.

3-D Positioning and Resource Allocation for Multi-UAV Base Stations Under Blockage-Aware Channel Model