# A Transfer Learning Approach for Cache-Enabled Wireless Networks

arXiv: https://arxiv.org/abs/1503.05448 · HTML: https://mlsanity.com/paper/1503.05448/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Mar 2015.

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

- [Transfer Learning for Future Wireless Networks: A Comprehensive Survey](https://mlsanity.com/paper/2102.07572/) (2021)
- [A Joint Energy and Latency Framework for Transfer Learning over 5G Industrial Edge Networks](https://mlsanity.com/paper/2104.09382/) (2021)
- [Machine Learning for Security in Vehicular Networks: A Comprehensive Survey](https://mlsanity.com/paper/2105.15035/) (2021)
- [Robust, Deep, and Reinforcement Learning for Management of Communication and Power Networks](https://mlsanity.com/paper/2202.05395/) (2022)

## Abstract (arXiv)

Locally caching contents at the network edge constitutes one of the most disruptive approaches in 5G wireless networks. Reaping the benefits of edge caching hinges on solving a myriad of challenges such as how, what and when to strategically cache contents subject to storage constraints, traffic load, unknown spatio-temporal traffic demands and data sparsity. Motivated by this, we propose a novel transfer learning-based caching procedure carried out at each small cell base station. This is done by exploiting the rich contextual information (i.e., users' content viewing history, social ties, etc.) extracted from device-to-device (D2D) interactions, referred to as source domain. This prior information is incorporated in the so-called target domain where the goal is to optimally cache strategic contents at the small cells as a function of storage, estimated content popularity, traffic load and backhaul capacity. It is shown that the proposed approach overcomes the notorious data sparsity and cold-start problems, yielding significant gains in terms of users' quality-of-experience (QoE) and backhaul offloading, with gains reaching up to 22% in a setting consisting of four small cell base stations.