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

The impractical association of a dedicated fiber optic backhauling link with each basestation in future wireless area network (WAN) networks promoted self-backhaulingto become one of the most practical techniques for ultra-dense deployments. Selfbackhauling reduces the number of stations with fiber-optic links, while the remaining stations can communicate with the core network through wireless multi-hopingconnections. Nevertheless, routing through self-backhauling stations is an NP-hardproblem. In this study, we propose a routing scheme based on a semi-distributedself-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 linkfailures. The proposed solution offers changing propagation medium between freespace optical (FSO) and radio frequency (RF); this dynamic change between every twohops reduces power consumption, increases throughput, and minimizes latency. Basedon the performed simulation, our proposed algorithm measured better overall bit error rate (BER) compared to both RF-only and free-space optical FSO-only techniquesresulting in increased backhauling capacity and reduced overall route interference.