AI meets mobile networks with the Qualcomm Edgewise Suite
Mobile network operators can look forward to more powerful, scalable and cost-effective radio access networks with artificial intelligence-powered RAN management.
The potential of AI with Radio Access Networks (RAN) is immense. For example, consider intent-based autonomous networks that get to work when triggered by a simple query. “Dear AI tool, please optimize the 5G network’s energy efficiency without compromising more than 10% of download speed for the least served subscribers.” It’s not difficult to imagine why a mobile network operator (MNO) would be excited about that sort of capability to improve operating efficiency and reduce operating expenses (OPEX) for their networks.
And who better to help MNOs apply leading AI tech to cellular networks than Qualcomm Technologies — a leader in edge AI and in cellular communications.
Let’s discuss what mobile operators can expect as Qualcomm Technologies continues to embed AI into RAN Automation and Management within the Qualcomm Edgewise Suite.
Introducing a powerful AI toolkit for the Qualcomm Edgewise Suite
AI has become a household term but it’s multi-faceted, and means many different things for different people and industries. For example, to maximize the potential of AI in RAN Management, traditional AI, generative AI and machine learning (ML) must work together to bring about desired outcomes. By applying the distinct capabilities of each of these technologies to our Qualcomm Edgewise Suite, network operators can access a higher level of network automation and intelligence, driving significant improvements in performance, reliability, efficiency and user experience.
By introducing sophisticated AI technology within the Qualcomm Edgewise Suite, we are addressing critical MNO challenges spanning several real-world use cases — here are a few:
The AI-powered Qualcomm Edgewise Suite makes it easy to conduct root cause analysis with the use of natural language prompts.
Enabling powerful intent-based autonomous networks
With generative AI technology, the Qualcomm Edgewise Suite can automatically manage and optimize network performance by following intent-driven prompts that are provided by network engineers. For example, the network engineer tells the AI tool what business objective it intends to accomplish and allows the Qualcomm Edgewise Suite RAN management layer to autonomously achieve the objective without the need to dive into specific parameters (i.e. focus on “what” needs to be achieved instead of “how” to achieve it). Furthermore, the generative AI tool can have a conversation (of sorts) with the engineer, exposing the different alternatives to reach a set of objectives, empowering the engineer to “talk business” instead of technology.
Going back to the example earlier in this blog, if an operator’s chief technology officer has assigned the RAN team to make sure that the lowest 10% of the subscriber base will have a minimum download speed of 20MB, the engineer can send this directive down to the Qualcomm Edgewise Suite, enabling the network to achieve the KPIs autonomously, while showing the engineer various alternatives to reach this goal, along with the pros and cons of each option (e.g., “Do I achieve this objective by impacting the top two highest deciles of subscribers by 20%? Or do I achieve this objective by impacting all the other deciles of subscribers by 5%?”).
Automating complex and repetitive tasks
Say goodbye to the tedious process of querying multiple databases and conducting root cause analysis to identify sleeping cells. Radio Frequency (RF) engineers can simply use natural language prompts to ask the AI-powered Qualcomm Edgewise Suite to pinpoint sleeping cells in a specific market. It will then compare the configurations of these cells with others, highlight the differences and generate the necessary configuration changes for the engineer to apply directly to the network.
Automating rApps development
Let’s say a MNO’s engineering team has an idea for a new network application (rApp) that runs on the RAN Intelligent Controller (RIC). For example, one that would better handle traffic surges at a certain train station during rush hour. Today, this translates into approaching the network vendor and asking them to build a specific set of logic or configuration, which costs lots of time and money.
AI tools, embedded into the Qualcomm Edgewise Suite, help free engineers from rApp, API and KPI development — tasks which they often lack the skill set or time to do themselves. The Qualcomm Edgewise Suite AI toolkit reduces the time and technology expertise needed for rApp development by automating the design process using natural language, then coding, testing and launching rApps in a run-time environment.
Multi-vendor, multi-tech heritage
The depth of AI expertise and innovation is critical, and Qualcomm is not only a force in the AI arena, but also in multi-vendor and multi-technology enablement. Afterall, MNOs want to modernize, but do not want to forfeit legacy infrastructure investments from older tech or, morph into single vendor systems.
As an extension to the existing Qualcomm Edgewise Suite, these new AI tools can be applied across more networks and vendors, increasing their applicability footprint.
– Apply to a mix of traditional RAN (TRAN), virtualized RAN (vRAN) and Open RAN (O-RAN)
– Apply to a mix of legacy equipment from vendor A, and new equipment from vendor B
A new paradigm for network automation and management
With the Qualcomm Edgewise Suite AI toolkit, Mobile Network Operators can look forward to lower operational costs, enhanced network performance and more scalable network capacity. They can optimize resource use and CAPEX with AI tools that automate time-consuming and error-prone tasks such as configuration management, performance monitoring and troubleshooting. By analyzing network data and traffic patterns, MNOs can forecast future capacity needs and recommend proactive measures to prevent network issues. These advancements empower mobile network operators to efficiently manage increasingly complex networks with data-driven insights and automated solutions, setting a new standard in the industry.
The AI toolkit for the Qualcomm Edgewise Suite is currently under evaluation with lead customers.
Come and see us at Network X in Paris (Stand A13) for more information and to see a demo.
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