Policy Optimization for Content Push via Energy Harvesting Small Cells in Heterogeneous Networks

TL;DR

This paper develops energy-efficient push policies for small-cell base stations powered by renewable energy, aiming to reduce user request blocking and improve content delivery in heterogeneous networks.

Contribution

It introduces threshold-based policies for energy harvesting SBSs, derives closed-form blocking probabilities, and demonstrates their effectiveness over traditional methods.

Findings

Threshold policies outperform non-push policies under certain conditions.

Proposed policies achieve near-optimal performance with low energy arrival rates.

Closed-form blocking probabilities are derived for infinite battery capacity.

Abstract

Motivated by the rapid development of energy harvesting technology and content-aware communication in access networks, this paper considers the push mechanism design in small-cell base stations (SBSs) powered by renewable energy. A user request can be satisfied by either push or unicast from the SBS. If the SBS cannot handle the request, the user is blocked by the SBS and is served by the macro-cell BS (MBS) instead, which typically consumes more energy. We aim to minimize the ratio of user requests blocked by the SBS. With finite battery capacity, Markov decision process based problem is formulated, and the optimal policy is found by dynamic programming (DP). Two threshold-based policies are proposed: the push-only threshold-based (POTB) policy and the energy-efficient threshold-based (EETB) policy, and the closed-form blocking probabilities with infinite battery capacity are derived. Numerical results show that the proposed policies outperform the conventional non-push policy if the content popularity changes slowly or the content request generating rate is high, and can achieve the performance of the greedy optimal threshold-based (GOTB) policy. In addition, the performance gap between the threshold-based policies and the DP optimal policy is small when the energy arrival rate is low or the request generating rate is high.