# Energy-Efficient Wireless Content Delivery with Proactive Caching

## TL;DR

This paper introduces an energy-efficient proactive caching scheme for wireless content delivery in social networks, optimizing cache management based on channel conditions to significantly reduce energy use.

## Contribution

It proposes a novel proactive caching policy with a threshold structure and a simplified scheme optimized via policy search, improving energy efficiency in wireless content delivery.

## Key findings

- Proactive caching reduces energy consumption compared to reactive methods.
- The optimal policy has a threshold structure based on channel quality.
- The simplified scheme performs close to the optimal policy in simulations.

## Abstract

We propose an intelligent proactive content caching scheme to reduce the energy consumption in wireless downlink. We consider an online social network (OSN) setting where new contents are generated over time, and remain \textit{relevant} to the user for a random lifetime. Contents are downloaded to the user equipment (UE) through a time-varying wireless channel at an energy cost that depends on the channel state and the number of contents downloaded. The user accesses the OSN at random time instants, and consumes all the relevant contents. To reduce the energy consumption, we propose \textit{proactive caching} of contents under favorable channel conditions to a finite capacity cache memory. Assuming that the channel quality (or equivalently, the cost of downloading data) is memoryless over time slots, we show that the optimal caching policy, which may replace contents in the cache with shorter remaining lifetime with contents at the server that remain relevant longer, has certain threshold structure with respect to the channel quality. Since the optimal policy is computationally demanding in practice, we introduce a simplified caching scheme and optimize its parameters using policy search. We also present two lower bounds on the energy consumption. We demonstrate through numerical simulations that the proposed caching scheme significantly reduces the energy consumption compared to traditional reactive caching tools, and achieves close-to-optimal performance for a wide variety of system parameters.