# Individual Preference Aware Caching Policy Design in Wireless D2D Networks

## TL;DR

This paper explores how incorporating individual user preferences into caching policies in wireless D2D networks can significantly enhance performance metrics like throughput and energy efficiency, by optimizing caching strategies based on user-specific data.

## Contribution

It introduces a utility maximization framework that accounts for individual preferences, user distribution, and channel effects, providing a novel approach to cache policy design in D2D networks.

## Key findings

- Performance improves significantly with personalized caching policies.
- Tradeoffs exist between throughput, energy efficiency, and hit-rate.
- The proposed approach finds stationary points under mild assumptions.

## Abstract

Cache-aided wireless device-to-device (D2D) networks allow significant throughput increase, depending on the concentration of the popularity distribution of files. Many studies assume that all users have the same preference distribution; however, this may not be true in practice. This work investigates whether and how the information about individual preferences can benefit cache-aided D2D networks. We examine a clustered network and derive a network utility that considers both the user distribution and channel fading effects into the analysis. We also formulate a utility maximization problem for designing caching policies. This maximization problem can be applied to optimize several important quantities, including throughput, energy efficiency (EE), cost, and hit-rate, and to solve different tradeoff problems. We provide a general approach that can solve the proposed problem under the assumption that users coordinate, then prove that the proposed approach can obtain the stationary point under a mild assumption. Using simulations of practical setups, we show that performance can improve significantly with proper exploitation of individual preferences. We also show that different types of tradeoffs exist between different performance metrics and that they can be managed through caching policy and cooperation distance designs.