On the Implementation of a Secure and Energetically Efficient NOC for Mobile Networks

Abstract

Over the past decade, the technological evolution of mobile networks has contributed to the global success and democratization of internet connectivity, notably relying on 4G and 5G deployments. Digital services have grown exponentially, resulting in high traffic volumes and continuous requirements to expand the network footprint. The problem is that, despite the investment in network expansion and upgrade, the revenues of the major Mobile Network Operators (MNOs) have presented anaemic growth, whilst other factor costs have risen, notably the energy prices. This challenging outlook raises concerns over the sector’s long-term sustainability and calls MNOs to adopt smart operative strategies in network management, aiming at ensuring sustainable energy consumption levels. This new paradigm essentially leverages artificial intelligence capabilities to evolve the current reactive approach of Network Operations Centres (NOCs) towards proactive and preventive models relying on network data. In particular, energy consumption data can be used to detect abnormal network behaviours, either caused by unintentional disruptions or by a cyber/physical attack. This paper contributes with a novel multi-domain NOC that combines performance, efficiency and security as an integral part of network optimization. Additionally, as a concrete use case example using live data from a 4G mobile network, a new methodology is proposed to optimize the trade-off between spectral and energy efficiency. The preliminary results show that up to 13% of improvement in energy consumption could be achieved using the proposed methodology to detect the worse performing sites and their root cause factors.