Contribution to the design and the implementation of a Cloud Radio Access Network

TL;DR

This paper presents a comprehensive design and implementation of a Cloud-RAN system addressing real-time signal processing and fronthaul capacity reduction, combining theoretical modeling with practical validation.

Contribution

It introduces a multi-threading model and an optimized functional split for Cloud-RAN, validated through stochastic modeling and a real-world testbed.

Findings

Latency reduction achieved through multi-threading

Optimized functional split improves fronthaul efficiency

Theoretical models accurately predict system performance

Abstract

This dissertation paper presents the main contributions to the design and the implementation of a Cloud-RAN solution. We concretely address the two main challenges of Cloud-RAN systems: real-time processing of radio signals and reduced fronthaul capacity. We propose a multi-threading model to achieve latency reduction of critical RAN functions as well as an adapted functional split for optimizing the transmission of radio signals. We model the performance of the proposed solution by means of stochastic service systems which reflect the behavior of high performance computing architectures based on parallel processing and yield dimensioning rules for the required computing capacity. Finally, we validate the accuracy of the theoretical proposals by a Cloud-RAN testbed implemented on the basis of open source solutions, namely Open Air Interface (OAI).