3-D UAV Small Cell Base Station Positioning and Resource Allocation in Cellular Network: A Stochastic Optimization Approach

Integrating unmanned aerial vehicles (UAVs) into wireless communication as aerial platforms to mount small cell base stations has grown rapidly in recent years. One of the main objectives of UAV integration into wireless networks is to optimize UAV deployment while meeting user expectations with the fewest UAVs. To ensure that users receive the requested data rate, management of UAV placement and user association is necessary due to the limited capacity of aerial base stations. Besides the user-base station distance, environmental conditions and propagation mode affect the data rate received by the users. When accounting for uncertain conditions, network management decisions become more realistic and productive. This article considers a random propagation mode for each link depending on the environmental conditions of the desired area. We exploit the stochastic programming framework to reflect propagation mode uncertainty in the optimization problem, which impacts the received data rate and path loss. The suggested mathematical formulation determines the minimum number of required UAVs, their 3-D positions, and the best user association strategy. The proposed model also includes interference-aware constraints for optimal radio resource allocation to base stations. The nonlinear path loss and line-of-sight (LoS) probability distribution functions in terms of the base station positions lead to a nonlinear formulation. We obtain a mixed-binary linear formulation by replacing nonlinear functions with their piecewise linear approximations and solve the model accurately using the CPLEX solver. The implementation results show that stochastic approaches provide more accurate diagnoses of the environment, as well as superior performance to deterministic optimization.