Design of an Efficient Heuristic Algorithm for Dense Heterogeneous Networks with Multi-Hop Backhauling

Abstract

5G networking is considered a promising technology which offers a variety of advantages over the previous networks generations such as higher peak data rate, higher density of connections (ultra-dense networks) and latency. Using of ultra-dense networks as an advantage of 5G networks helps improving the capacity of the network. However, at the same time, it implies challenges on the backhauling between small cells (SC) of the network. Using terrestrial wired hubs is not practical any more as the communication between large number of SCs requires the availability of many locations within line of sight (LOS). Furthermore, this method is costly. An alternative way for achieving high level of backhauling between SCs is using Unmanned aerial vehicle (UAV) for establishing wireless backhauling between SCs. One model for maximizing the throughput of a backhauling network is studied. The model was formulated by (Almohamad et al., 2019) and it has been identified to be NP-hard. As the formulated model is NP-hard, it takes longer periods to solve dense networks with large number of small cells. In this thesis, novel heuristic approaches are designed for providing fast and accurate solutions for dense networks with large number of small cells.