Individual Preference Aware Caching Policy Design for Energy-Efficient Wireless D2D Communications

Abstract

Cache-aided wireless device-to-device (D2D) networks allow significant throughput increase, depending on the concentration of the popularity distribution of files. While many previous investigations assumed that all users have the same preference, this may not be true in practice. This work investigates whether and how the information about individual preferences can benefit such cache-aided D2D networks. Considering a clustered network, we derive a network utility that considers both the user distribution and channel fading effects, and formulate a utility optimization problem. This formulation can be used to optimize several important quantities, including throughput, energy efficiency (EE), and hit-rate, and solve different tradeoff problems. We provide designs of caching policies that solve the utility maximization problem with and without coordination between the devices, and prove that the coordinated design can obtain the stationary point under a mild assumption. Using simulations of practical setups, we show that by properly exploiting the diversity entailed by the individual preferences, performance can be improved significantly. Besides, different types of tradeoffs exist between different performance metrics, and they can be managed by means of proper caching policy and cooperation distance design.

A Markovian model for satellite integrated cognitive and D2D HetNets

“…In contrast to our study, theirs does not support cognitive capabilities in devices and has no satellite extension. In [26], caching strategies for improving EE are proposed in a cellular and D2D hybrid network taking user request preferences into account. They assume that different users can have distinct preferences for same content.…”

Video Transmission Using Device-to-Device Communications: A Survey

“…The probability of requesting a file by a user is modeled as a probability that a user requests a certain genre, then a conditional probability that a file within a genre is requested. Also, a caching policy with the aim of minimizing energy consumption using users' preferences is also proposed in [46]. The authors considered two scenarios; when the users do not collaborate, i.e., a user has no knowledge about other users' preferences and when users collaborate.…”

Decentralized Video Streaming in Multi-Hop Wireless Networks: Incentive Mechanism and Energy Efficiency

“…Despite a variety of works on QoE-based network optimization, the consideration of the individual user preferences has been largely ignored. Researchers have recently started taking this point into account, e.g., in video caching [12] or content offloading [4]. The most relevant work to our present work is [4] where the authors consider the willingness of the users in helping each other for data offloading.…”