The next step in the evolution of smart grids
5G enables multiple and diverse new use cases, such as real-time streaming of VR streams from the metaverse, but also increasing complexity for CSPs. To prepare for the future, CSPs must simplify operations, increase sustainability, and improve user experience. To achieve this, we need the technology of tomorrow. In other words, networks must evolve. The good news is that we don’t have to wait until tomorrow, we are already creating the networks of the future and providing an evolutionary path to intelligent automated radio networks.
In my previous blog Who are intelligent agents in network operations and why do we need them? I presented the use of AI technology in network operations and how this technology can help achieve better results in network optimization and performance. In this blog, I’m going to build on that information and provide guidance – or should we say the foundation – on how CSPs can succeed in the journey – and build the networks of the future.
As mentioned, 5G radio access networks (RANs) will need to support a multiplicity of use cases. The challenge is to overcome this complexity and ensure an exceptional customer experience with efficient energy consumption for sustainability.
This will require an evaluation of multiple scenarios with different network configurations to predict the optimal configuration for network performance, power consumption, and radio resource efficiency. For this task, we must apply new technologies. We need artificial intelligence (AI) and deep reinforcement learning (DRL) techniques applied everywhere, both in products and services.
However, applying AI is not enough. We need AI everywhere but not just anywhere. In other words, we need to run it where it makes sense to unlock all the potential benefits of AI. Below, I share four pillars that will enable CSPs to succeed today and in the future based on this holistic approach.
1. Use AI to support CSP decision-making
Data is the most important factor in decision making – good decisions cannot be made without relevant and reliable data. However, there is a limit to the amount of data a person or team can manage, and that’s where AI comes in.
AI also helps automate the data processing process, sift through big data to distill it, and ultimately create actionable insights. By coupling AI, data and automation, a virtuous circle is created, with data enhancing the AI algorithm and further improving networks. AI data-driven algorithms enable networks to adapt to an ever-changing environment to meet ever-changing demands.
The power of an intelligent approach can be demonstrated by Ericsson’s Advanced Microwave Insights solution. This solution recognizes events in a live network such as weather events or temporary blocking events (blocking vehicles). It can detect different types of interference and could potentially be used to track weather in the future. With this information, CSPs can identify performance issues for faster resolution.
There are many more examples of this AI data-driven approach in the intelligent services and network scaling capabilities that are part of intelligent RAN automation solutions.
In short, CSPs benefit from these AI data-driven automation solutions in network planning, deployment, optimization, and repair. Some examples of these solutions available today are shown below.
2. RApps to boost efficiency and foster innovation
Have you heard of rApps? What are they and why are they needed? We mention them here because they are part of the next stage in the evolution of the smart grid. Imagine having the Network Evolution Almanac, which tells you what new services will be required and demanded by your customers. Well, you would also like to be ready for these new services as soon as possible to gain a competitive edge.
rApps provide the new technology needed to realize the core ambitions of CSPs: they help drive innovation with a short time to market, improve performance, and optimize CAPEX and OPEX investments.
rApps are a new software architecture paradigm that brings the following benefits to CSPs:
- Agility for new use cases implementation in an open ecosystem where customers and partners can be developers.
- Simplified automated network operations with true closed-loop automation with CSPs under control.
- Improve network efficiency with AI applied in the large-scale network to make the most of the radio network.
rApps are applications designed for automation and optimization. They are deployed and managed on the non-real-time Intelligent RAN Controller (RIC). If you’ve never heard of RIC before, don’t worry, it’s an industry term for the platform applications run on. We will talk more about this in the third pillar.
We can already provide examples of rApps improving energy efficiency and performance to create more sustainable networks with excellent user experience. They can reduce daily power consumption by 15% without impacting performance, reduce transmission power by 20%, and increase user data throughput by up to 30% in a congested network.
3. SMO and intelligent automation are essential for a future-proof architecture to ensure security and openness
Let’s talk in more depth about the evolution of the smart grid and the new architecture.
There is a demand to streamline the number of platforms and make them more open and secure. This is achieved in the industry-defined Service Management and Orchestration (SMO) platform. Ericsson Intelligent Automation Platform (EIAP) is Ericsson’s SMO with a strong AI foundation. to clarify, SMO is the industry standard and EIAP is the implementation of the SMO platform with added value and functionality.
Let’s see the relationship between rApps and the platform and why both are needed.
rApps are placed in the EIAP where there is automated support for rApps and AI capabilities. EIAP automates rApp lifecycle management and AI support components such as deployment, model monitoring, and recycling. This feature enables one-to-one development and deployment with automated orchestration and conflict management. In short, the rApps orchestrate the radio and the EIAP is the orchestrator of the rApps.
Ericsson is at the forefront of industry standards (O-RAN alliance) to ensure that the platform, its rApps and its interfaces will be secure. Moreover, based on the developed platform and rApps features, faster and deeper threat detection will improve RAN security.
4. Open ecosystem for innovation and monetization
The main focus of the platform’s open architecture and rApps is innovation and monetization. This goes beyond the standardization of interfaces; we need to enable CSPs to have collaboration with partners and faster development of new use cases.
When talking about Intelligent RAN Automation solutions and how they can enable service providers to reduce time to market for new use cases and services, the Software Development Kit (SDK) comes up. as a key catalyst. With EIAP, Ericsson SDK, frameworks and components enable and extend the ecosystem of developers around rApps.
In summary, this environment supports the ambitions of CSPs and third parties to deliver new functionality, covering network-wide automation use cases (i.e. for monetization).
AI applied to network automation together with the architecture presented with these four key pillars supports an open ecosystem of constant innovation and collaboration for all parties: service providers, suppliers and future development partners of the telecommunications industry.
AI technology will enable CSPs to win the 5G game by delivering a competitive advantage with data-driven AI algorithms, while also enabling them to reduce CAPEX and OPEX, simplify operations complexity, increase durability and improve user experience. At Ericsson, some of these features have already been tested with excellent results.
To meet the challenges of 5G and succeed in new opportunities, your “Back to the Future” almanac is here: the Intelligent RAN automation.
Read the Intelligent Automation Guide How Intelligent RAN Automation Creates Key Use Cases for Service Providers
Dive Deeper into Intelligent RAN Automation
Explore the Intelligent Automation Platform
Learn more about rApps
Learn more about Telecom SDKs
Learn more about AI in networks