  Recently, as a consequence of the COVID-19 pandemic, dependence on
telecommunication for remote learning/working and telemedicine has
significantly increased. In this context, preserving high Quality of Service
(QoS) and maintaining low latency communication are of paramount importance.
Development of an Unmanned Aerial Vehicles (UAV)-aided heterogeneous cellular
network is a promising solution to satisfy the aforementioned requirements.
There are, however, key challenges ahead, on the one hand, it is challenging to
optimally increase content diversity in caching nodes to mitigate the network's
traffic over the backhaul. On the other hand is the challenge of attenuated
UAVs' signal in indoor environments, which increases users' access delay and
UAVs' energy consumption. To address these challenges, we incorporate UAVs, as
mobile caching nodes, together with Femto Access points (FAPs) to increase the
network's coverage in both indoor and outdoor environments. Referred to as the
Cluster-centric and Coded UAV-aided Femtocaching (CCUF) framework, a two-phase
clustering framework is proposed for optimal FAPs' formation and UAVs'
deployment. The proposed CCUF leads to an increase in the cache diversity, a
reduction in the users' access delay, and significant reduction in UAVs' energy
consumption. To mitigate the inter-cell interference in edge areas, the
Coordinated Multi-Point (CoMP) approach is integrated within the CCUF
framework. In contrary to existing works, we analytically compute the optimal
number of FAPs in each cluster to increase the cache-hit probability of coded
content placement. Furthermore, the optimal number of coded contents to be
stored in each caching node is computed to increase the cache-hit-ratio,
Signal-to-Interference-plus-Noise Ratio (SINR), and cache diversity and
decrease the users' access delay and cache redundancy for different content
popularity profiles.
