Energy Efficiency of Cloud Processors for Small Cell Networks

Abstract

A cloud-based networks offered as new wireless architecture, where optimization of radio resources at the base station (BS) is moved to a cloud data center for optimization. In this paper, we propose to minimize the energy consumption at the data center where multiple cloud processors are used for the optimization. As the cell size and networks become respectively smaller and denser, the number of BS to be optimized grows exponentially, resulting in high computational complexity and latency at cloud processors. The computation for the schemes is distributed across multiple processors and done in parallel using belief propagation (BP) method, leading to very low latency with increasing number of BS. Simulation results show that the network energy efficiency performances at the cloud are close to an exhaustive search solution in finding the best configuration.