Caching in Heterogeneous Networks with Per-File Rate Constraints

TL;DR

This paper investigates caching strategies in heterogeneous networks with interference and per-file rate constraints, demonstrating that cooperative approaches significantly improve power efficiency and resource utilization over non-cooperative methods.

Contribution

It introduces a novel cache optimization framework considering cooperation and interference, with a low-complexity algorithm that outperforms existing strategies.

Findings

Cooperative caching reduces power consumption significantly.

Full cooperation enhances resource sparing and efficiency.

Storing only popular files is not always optimal for power savings.

Abstract

We study the problem of caching optimization in heterogeneous networks with mutual interference and per-file rate constraints from an energy efficiency perspective. A setup is considered in which two cache-enabled transmitter nodes and a coordinator node serve two users. We analyse and compare two approaches: (i) a cooperative approach where each of the transmitters might serve either of the users and (ii) a non-cooperative approach in which each transmitter serves only the respective user. We formulate the cache allocation optimization problem so that the overall system power consumption is minimized while the use of the link from the master node to the end users is spared whenever possible. We also propose a low-complexity optimization algorithm and show that it outperforms the considered benchmark strategies. Our results indicate that significant gains both in terms of power saving and sparing of master node's resources can be obtained when full cooperation between the transmitters is in place. Interestingly, we show that in some cases storing the most popular files is not the best solution from a power efficiency perspective.