Innovative unmanned aerial vehicle self-backhauling hybrid solution using RF/FSO system for 5G networks

Abstract

The impractical association of a dedicated fiber optic backhauling link with each base station in future wireless area network (WAN) networks promoted self-backhauling to become one of the most practical techniques for ultra-dense deployments. Self-backhauling reduces the number of stations with fiber-optic links, while the remaining stations can communicate with the core network through wireless multi-hoping connections. Nevertheless, routing through self-backhauling stations is an NP-hard problem. In this study, we propose a routing scheme based on a semi-distributed self-learning algorithm to reduce the end-to-end latency which achieve better stability against the dynamic nature of the mobile network, such as load variations and link failures. The proposed solution offers changing propagation medium between free-space optical (FSO) and radio frequency (RF); this dynamic change between every two hops reduces power consumption, increases throughput, and minimizes latency. Based on the performed simulation, our proposed algorithm measured better overall bit error rate (BER) compared to both RF-only and free-space optical FSO-only techniques resulting in increased backhauling capacity and reduced overall route interference.