Joint position and trajectory optimization of flying base station in 5G cellular networks, based on users' current and predicted location

TL;DR

This paper proposes a method for optimizing the placement and number of drone-based base stations in 5G networks by considering current and predicted user locations to enhance coverage and network reliability.

Contribution

It introduces a novel approach to jointly optimize drone base station positions and quantities based on user location predictions, improving network coverage during temporary events.

Findings

The method achieves acceptable network coverage in simulations.

Optimized drone placement adapts to user movement and predicted locations.

The approach reduces coverage gaps during network disruptions.

Abstract

Nowadays, Unmanned Aerial Vehicles (UAVs) have been significantly improved, and one of their most important applications is to provide temporary coverage for cellular users. Static Base Station cannot service all users due to temporary crashes because of temporary events such as ground BS breakdowns, bad weather conditions, natural disasters, transmission errors, etc., drones equipped with small cellular BS. The Drone Base Station is immediately sent to the target location and establishes the necessary communication links without requiring any predetermined infrastructure and covers that area. Finding the optimal location and the appropriate number (DBS) of drone-BS in this area is a challenge. Therefore, in this paper, the optimal location and optimal number of DBSs are distributed in the current state of the users and the subsequent user states determined by the prediction. Finally, the DBS transition is optimized from the current state to the predicted future locations. The simulation results show that the proposed method can provide acceptable coverage on the network.