# Joint Transmission Scheme and Coded Content Placement in Cluster-centric UAV-aided Cellular Networks

arXiv: https://arxiv.org/abs/2101.11787 · HTML: https://mlsanity.com/paper/2101.11787/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 Jan 2021.

## Built on by (most cited first, 4 of 4)

- [TEDGE-Caching: Transformer-based Edge Caching Towards 6G Networks](https://mlsanity.com/paper/2112.00633/) (2021)
- [Multi-Content Time-Series Popularity Prediction with Multiple-Model Transformers in MEC Networks](https://mlsanity.com/paper/2210.05874/) (2022)
- [ViT-CAT: Parallel Vision Transformers with Cross Attention Fusion for Popularity Prediction in MEC Networks](https://mlsanity.com/paper/2210.15125/) (2022)
- [CLSA: Contrastive Learning-based Survival Analysis for Popularity Prediction in MEC Networks](https://mlsanity.com/paper/2303.12097/) (2023)

## Abstract (arXiv)

Recently, as a consequence of the COVID-19 pandemic, dependence on telecommunication for remote working and telemedicine has significantly increased. In cellular networks, incorporation of Unmanned Aerial Vehicles (UAVs) can result in enhanced connectivity for outdoor users due to the high probability of establishing Line of Sight (LoS) links. The UAV's limited battery life and its signal attenuation in indoor areas, however, make it inefficient to manage users' requests in indoor environments. Referred to as the Cluster centric and Coded UAV-aided Femtocaching (CCUF) framework, the network's coverage in both indoor and outdoor environments increases via a two-phase clustering for FAPs' formation and UAVs' deployment. First objective is to increase the content diversity. In this context, we propose a coded content placement in a cluster-centric cellular network, which is integrated with the Coordinated Multi-Point (CoMP) to mitigate the inter-cell interference in edge areas. Then, we compute, experimentally, the number of coded contents to be stored in each caching node 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. Capitalizing on clustering, our second objective is to assign the best caching node to indoor/outdoor users for managing their requests. In this regard, we define the movement speed of ground users as the decision metric of the transmission scheme for serving outdoor users' requests to avoid frequent handovers between FAPs and increase the battery life of UAVs. Simulation results illustrate that the proposed CCUF implementation increases the cache hit-ratio, SINR, and cache diversity and decrease the users' access delay, cache redundancy and UAVs' energy consumption.