Fairness Scheduling for Coded Caching in Multi-AP Wireless Local Area Networks

Abstract

Coded caching (CC) exploits cumulative cache memory at user devices and coding to transform unicast traffic into multicast transmissions. While information theoretic results show significant gains over uncoded caching for various network topologies, its practical benefits remain unclear. In this work, we investigate CC for on-demand video streaming over large wireless local area networks, where multiple users are served simultaneously by spatially distributed access points. Users asynchronously request video chunks from a content library. We propose a decentralized, asynchronous, and location-independent cache placement scheme combined with an "over IP" delivery mechanism operating at higher network layers, leaving the physical and MAC layers unchanged. For this scheme, we characterize the achievable goodput region, where goodput is defined as the number of video chunks per unit time delivered to users' playback buffers, and formulate the corresponding fairness problem as a convex maximization. We develop a dynamic scheduling algorithm that provably achieves the optimal fairness point under stationary conditions with reduced complexity, and introduce a heuristic to further lower complexity. Numerical results demonstrate significant gains over baseline schemes, including conventional prefix caching, orthogonal sub-channel allocation with spatial reuse, and a CSMA-inspired distributed coordination approach, showing that CC can be implemented as a scalable and compatible over IP solution for existing WLANs.