Short-Term and Long-Term Cell Outage Compensation Using UAVs in 5G Networks

Abstract

The use of Unmanned Aerial Vehicles (UAVs) has gained interest in wireless networks for its many uses and advantages such as rapid deployment and multi-purpose functionality. This is why wide deployment of UAVs has the potential to be integrated in the upcoming 5G standard. They can be used as flying base-stations, which can be deployed in case of ground Base-Stations (GBSs) failures. Such failures can be short-term or longterm. Based on the type and duration of the failure, we propose a framework that uses drones or helikites to mitigate GBS failures. Our proposed short-term and long-term cell outage compensation framework aims to mitigate the effect of the failure of any GBS in 5G networks. Within our framework, outage compensation is done with the assistance of sky BSs (UAVs). An optimization problem is formulated to jointly minimize communication power of the UAVs and maximize the minimum rates of the Users' Equipment (UEs) affected by the failure. Also, the optimal placement of the UAVs is determined. Simulation results show that the proposed framework guarantees the minimum quality of service for each UE in addition to minimizing the UAVs' consumed energy.

Towards enabling unmanned aerial vehicles as a service for heterogeneous applications

“…By increasing the number of used DBSs/UAVs, the consumed power increases. As the maximum power increases, the rate increases but levels off when the power reaches 1W [40]. Owing to the fact that the objective function of the optimization problem is maximizing the minimum achievable rate and at the same time minimizing the downlink power, there is a trade-off between increasing the achievable rate and decreasing the downlink power.…”

D3S: A Framework for Enabling Unmanned Aerial Vehicles as a Service

“…For the short-term failure scenario, we apply the D 3 S framework as follows (the results area mainly based on the optimization formulations in reference [5] by the authors):…”

“…Based on the given scenario, three DBSs are used to heal the failed GBS. The deployment location is decided based on solving the optimization problem in [5].…”

“…Phase 3: D (Deployment) In this phase, the deployment depends mainly on the initial locations of the DBSs and the trajectory is determined optimally [5]. In the deployed scenario, the initial locations of the DBSs are set such that each GBS is hosting a standby DBS.…”

“…Phase 4: S (Service) In this phase, we guarantee a minimum achievable rate to the users under the failed GBS. This is always achieved using a rate constraint in the optimization problem [5].…”