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WBA: What do you consider to be today’s greatest Wi-Fi challenge?
Ting: Enterprise Wi-Fi networks are expanding exponentially, both in size and complexity. Now, with the introduction of 6 GHz, balancing Wi-Fi’s many channel planning, bandwidth planning, and transmit power configuration settings across very large, dynamic networks for optimum RF operation is pushing the limits of today’s wireless personnel.
WBA: What’s creating RF complexity and what are its ramifications for wireless operators?
Ting: Many digital transformation initiatives involve deploying wireless applications with high-availability, low-latency requirements that historically only wired networks could meet. IoT, robotics, and augmented reality are just a few examples. Configuring Wi-Fi unlicensed-band operations to support these performance levels, at scale, compounds operators’ challenges as they strive to maximize capacity and minimize interference network-wide. Moreover, current and forthcoming RF technologies, including 6 GHz Wi-Fi, automated frequency coordination (AFC), and Wi-Fi 7’s promise of concurrent transmissions across multiple RF bands, add still more channel, bandwidth aggregation, and transmit power options, driving complexity beyond what human operators alone can handle.
WBA: How can we simplify wireless operations while meeting the stricter performance requirements?
Ting: The wireless industry is now applying artificial intelligence (AI) and machine learning (ML) to Wi-Fi operations. Wireless AIOps platforms aggregate and process billions of network- and client-side telemetric data points about user and device experience levels, while ML algorithms applied to the data inform the platforms of the network and traffic behaviors of every connected device. Moreover, AI and ML enable enterprises to surface issues before they become service-affecting -- to address the most urgent issues first, fix them fast, compare network KPIs before and after any configuration change to analyze the impact of that change and, last-but-not least, automatically adjust configuration parameters to maximize service levels. Without AI and ML, wireless triage can take hours, days, or even weeks, putting service levels at risk.
WBA: Can you quantify the benefits of applying AI/ML to Wi-Fi?
Ting: Offloading network troubleshooting from IT staff while accelerating wireless operations saves time and money while boosting service levels. A large Wi-Fi managed service provider (MSP) using our RUCKUS Networks Wi-Fi AIOps platform, for example, has reported a 67% reduction in mean time to resolution (MTTR), 60% savings in professional IT time, and a 50% decrease in time required to train new IT hires. The MSP also said its improved Wi-Fi service levels helped reduce customer churn by 80% in the year following deployment.
WBA: What exactly are the new configuration considerations facing Wi-Fi operators?
Ting: In 2021, Wi-Fi 6E standards extended Wi-Fi beyond its traditional 2.4-GHz and 5-GHZ unlicensed channels into the 6-GHz unlicensed frequency band for an additional 1200-MHz of bandwidth. Having more channels and more opportunities to combine them for greater bandwidth enables operators to fine-tune their networks for better throughput and interference avoidance. However, there are also many more channels, bandwidth, and power variables to consider, each with capacity, interference, and throughput tradeoffs. As Wi-Fi networks grow larger and applications become more demanding, it will become increasingly difficult for human operators to maintain just the right configuration balance across all network access points. That’s why we feel that enterprises will soon require AI-powered systems to meet their dynamic RF growth, complexity, and service-level challenges.
Read how enterprises and operators are using RUCKUS® AI-driven analytics to better meet their SLAs and deliver a better customer and student experience: https://www.ruckusnetworks.com/products/network-analytics-assurance/
Wi-Fi, Wi-Fi 6E and Wi-Fi 7 are trademarks of the Wi-Fi Alliance.