# Base-Station Assisted Device-to-Device Communications for High-Throughput Wireless Video Networks

arXiv: https://arxiv.org/abs/1304.7429 · HTML: https://mlsanity.com/paper/1304.7429/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 Apr 2013.

## Built on by (most cited first, 3 of 3)

- [Learning in Repeated Multi-Unit Pay-As-Bid Auctions](https://mlsanity.com/paper/2307.15193/) (2023)
- [Large Language Model as a Catalyst: A Paradigm Shift in Base Station Siting Optimization](https://mlsanity.com/paper/2408.03631/) (2024)
- [Spatio-Temporal Split Learning for Autonomous Aerial Surveillance using Urban Air Mobility (UAM) Networks](https://mlsanity.com/paper/2111.11856/) (2021)

## Abstract (arXiv)

We propose a new scheme for increasing the throughput of video files in cellular communications systems. This scheme exploits (i) the redundancy of user requests as well as (ii) the considerable storage capacity of smartphones and tablets. Users cache popular video files and - after receiving requests from other users - serve these requests via device-to-device localized transmissions. The file placement is optimal when a central control knows a priori the locations of wireless devices when file requests occur. However, even a purely random caching scheme shows only a minor performance loss compared to such a genie-aided scheme. We then analyze the optimal collaboration distance, trading off frequency reuse with the probability of finding a requested file within the collaboration distance. We show that an improvement of spectral efficiency of one to two orders of magnitude is possible, even if there is not very high redundancy in video requests.