With the introduction of 5G and cloud-based applications like virtualisation, network deployment is becoming more complex and in need of revision. Ericsson Intelligent Deployment uses technologies like artificial intelligence (AI) and machine learning (ML) to reduce 5G rollout complexity and offer communications service providers innovative ways to make more intelligent investment decisions.

Widespread adoption of cloud-based services and virtualisation, network deployments, upgrades and expansion are making network deployment and evolution more complex. These include increased levels of the following:

• Spectrum complexity and an increasing volume of parameters to be monitored;
• Small-cell densification, making logistics and integration more challenging
• Hardware volumes, driving an increase in number of network elements to put in place;
• Multi-vendor deployment models, with the arrival of cloud radio access network (CRAN) and edge;
• Critical use-case performance, requiring more accuracy and agility.

Communications service providers (CSPs) need to take into account these newly emerging considerations and revise their approach to network deployment – leveraging the latest available technologies.

A new reality for network deployment

Network rollout has traditionally been viewed as a series of sequential phases based on design, engineering, installation and acceptance. Many of these phases have been, to a large extent, manual and labour intensive processes.

Today, CSPs require more from network deployments, with more stringent performance requirements from 5G than they did from 4G. 5G offers exciting new opportunities with fixed wireless access (FWA) in suburban areas, private network solutions in industrial areas with multiple connected factories and warehouses, and also high-performing consumer services in dense, urban environments.

With all the complexity that comes with 5G, it becomes more and more important to continuously optimise network upgrades, evolution and maintenance. It is no longer enough to just put a network in place. It is vital that CSPs get a fully digitised view of the network that has been deployed and to know exactly what can be done on a particular site in the future without having to physically visit that site.

AI and ML are now commonly used in many different industry sectors. Their use cases include everything from consumer services through to agriculture and farming, security and surveillance, manufacturing and production. Advanced algorithms employed in AI and ML offer us a way to escape labour intensive mundane business tasks by automating them and performing data analysis at speeds of which we could only dream.

Digitised network deployment is here

Network deployment that is digitised from design to acceptance, considering the performance required for each use case as well as topology, current and future traffic demands, is no pipe dream. It’s here and now.

Ericsson has combined tools that leverage international data standards with proprietary data and processes to provide CSPs with unified, digitised experiences during deployment, expansion, upgrades, and maintenance of their networks.

Ericsson Intelligent Deployment offers CSPs quick return on investments with fast and efficient rollout and fast site activation. It delivers standardisation and digitalisation of the full network life cycle using a modular suite of capabilities that focuses specifically on network deployment. Ericsson Intelligent Deployment offers:

• Fast time to market by standardising data in a single user interface
• Lower OPEX through better control of the network lifecycle
• Transparency through access to data from the end-to-end deployment process
• Cost efficiency, sending drones instead of engineers for the site surveys
• Accuracy through capturing more data and adding granularity
• Flexibility in planning OPEX and CAPEX availability and change management.