Joint ABS Deployment and TBS Antenna Downtilt Optimization for Coverage Maximization

In this letter, we consider an air-and-ground cooperative network, where several aerial base stations (ABS) help terrestrial base stations (TBS) for coverage enhancement. In this network, we first quantify the space-time coverage ratio (STCR) by fully considering the antenna models and the dynamic of the ABS, and then formulate a joint ABS deployment and TBS antenna downtilt optimization problem with the objective to maximize the STCR of the concerned area. The objective function involves many control variables and judgement operations, which make the problem very complex. To solve the problem effectively, we first adopt the genetic algorithm (GA). Using the solutions of the GA as training samples, we propose a deep neural network architecture to further reduce the computational time. Simulation results indicate that the proposed GA significantly improves the coverage ratio and the deep neural network (DNN) architecture achieves orders of magnitude acceleration in computational time with acceptable performance.

Automated summary

This letter investigates an air-and-ground cooperative network, where aerial base stations assist terrestrial base stations for coverage enhancement. The space-time coverage ratio (STCR) is quantified by considering antenna models and the dynamic of the aerial base stations. The joint deployment problem and antenna downtilt optimization problem are formulated to maximize the STCR. A genetic algorithm (GA) is employed to effectively solve the problem, and a deep neural network architecture is proposed to reduce computational time.