Stochastic Content-Centric Multicast Scheduling for Cache-Enabled Heterogeneous Cellular Networks

TL;DR

This paper develops a stochastic multicast scheduling framework for cache-enabled heterogeneous cellular networks, optimizing content delivery to reduce delay and power costs while considering wireless multicast capabilities.

Contribution

It formulates the problem as an MDP, characterizes the optimal policy structure, and proposes both optimal and low-complexity suboptimal algorithms.

Findings

Optimal multicast scheduling policy is of threshold type.

Proposed algorithms effectively minimize network delay and power costs.

Structural properties enable efficient policy computation.

Abstract

Caching at small base stations (SBSs) has demonstrated significant benefits in alleviating the backhaul requirement in heterogeneous cellular networks (HetNets). While many existing works focus on what contents to cache at each SBS, an equally important problem is what contents to deliver so as to satisfy dynamic user demands given the cache status. In this paper, we study optimal content delivery in cache-enabled HetNets by taking into account the inherent multicast capability of wireless medium. We consider stochastic content multicast scheduling to jointly minimize the average network delay and power costs under a multiple access constraint. We establish a content-centric request queue model and formulate this stochastic optimization problem as an infinite horizon average cost Markov decision process (MDP). By using \emph{relative value iteration} and special properties of the request queue dynamics, we characterize some properties of the value function of the MDP. Based on these properties, we show that the optimal multicast scheduling policy is of threshold type. Then, we propose a structure-aware optimal algorithm to obtain the optimal policy. We also propose a low-complexity suboptimal policy, which possesses similar structural properties to the optimal policy, and develop a low-complexity algorithm to obtain this policy.