Modeling and analysis of UAV-Assisted sparse ground networks
TL;DR
Simulation resulsts indicate that there is an optimal bias setting to maximize the overall coverage performance of the AGCN, which provides valuable guidance for the future network design.
Abstract
With the continuous improvement of communication requirements, it is difficult for traditional ground cellular networks to achieve seamless wide-area coverage, particularly in remote regions. To solve the insufficient coverage problem of sparse ground cellular network, we propose the Air-and-Ground Cooperative Network (AGCN) architecture to enhance the network coverage performance. Besides, and Cell Range Expansion (CRE) technology is combined to achieve load balancing between aerial Base Stations (BSs) and ground BSs. By setting user connection bias, communication users can access different BSs to coordinate the coverage performance of each layer in the AGCN. Based on stochastic geometry theory, we analyze the user access probability and distance distribution, and then derive the analytical formulas of network throughput and traversal rate. Furthermore, we analyze the influence of user connection bias on network performance in CRE technology. Simulation resulsts verify the correctness of the theoretial analysis and the efficiency of the AGCN in coverage enhancement. It indicates that there is an optimal bias setting to maximize the overall coverage performance of the AGCN, which provides valuable guidance for the future network design.