Adaptive Coded Caching for Fair Delivery over Fading Channels

TL;DR

This paper introduces an adaptive coded caching scheme that improves fairness and efficiency over fading channels by combining decentralized caching, joint scheduling, and power control, outperforming traditional methods.

Contribution

It proposes a novel online delivery scheme that maximizes alpha-fair utility by integrating caching, scheduling, and congestion control for fading channels.

Findings

Outperforms baseline schemes in simulations.

Achieves fairness and efficiency by adaptive user subset selection.

Maximizes alpha-fair utility among decentralized caching schemes.

Abstract

The performance of existing coded caching schemes is sensitive to the worst channel quality, a problem which is exacerbated when communicating over fading channels. In this paper, we address this limitation in the following manner: in short-term, we allow transmissions to subsets of users with good channel quality, avoiding users with fades, while in long-term we ensure fairness among users. Our online scheme combines (i) the classical decentralized coded caching scheme \cite{maddah2013decentralized} with (ii) joint scheduling and power control for the fading broadcast channel, as well as (iii) congestion control for ensuring the optimal long-term average performance. We prove that our online delivery scheme maximizes the alpha-fair utility among all schemes restricted to decentralized placement. By tuning the value of alpha, the proposed scheme can achieve different operating points on the average delivery rate region and tune performance according to an operator's choice. We demonstrate via simulations that our scheme outperforms two baseline schemes: (a) standard coded caching with multicast transmission, limited by the worst channel user yet exploiting the global caching gain; (b) opportunistic scheduling with unicast transmissions exploiting the fading diversity but limited to local caching gain.