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See all (5) →High-performance, reliable connectivity delivering the best end-user experience
Today’s enterprise networks are increasingly difficult to manage. A major challenge, the radio environment is highly dynamic, complex and continuously changing. More client devices are mobile and roaming throughout buildings and venues, while technologies such as the internet of things (IoT) introduce new challenges to the wireless environment.
Additionally, with the introduction of the 6 GHz spectrum, Wi-Fi® networks have many choices with multiple frequency bands, channels, and channel widths. The 6 GHz spectrum alone has 59 distinct channels, whereas 5 GHz only offers up to 25.
While it may seem counterintuitive, this abundance of choice results in burdensome Wi-Fi spectrum management and an increased likelihood of higher RF interference, resulting in poorer-performing networks. RF interference is arguably the single biggest performance issue with modern Wi-Fi networks.
AI RRM operates in the cloud and utilizes proprietary techniques to monitor the network and identify wireless performance issues. Every day, it runs in the background, assessing the current state of the network. AI RRM constantly monitors the network for any radio interference that may have developed due to changing network conditions.
Once per day, AI RRM assesses the latest wireless data analysis and suggests modifications to access point (AP) configurations to reduce the RF interference as low as possible. It utilizes three primary Wi-Fi radio characteristics to control the performance of the AP: transmit (Tx) power, operating channel, and/or channel bandwidth.
As part of IntentAI, AI RMM provides network administrators with the option to either configure for the highest throughput or maximum client density. For highest throughput, it adjusts the operating channel to minimize co-channel interference. For maximizing client density, it may adjust Tx power, operating channel, and channel bandwidth. By managing the network’s RF environment using AI RRM, IT staff can automate the complexities of channel planning, allowing them to focus on other, more proactive strategies.
With RUCKUS AI-driven RRM, managing the vast number of RF channels available to a network becomes a breeze. AI RRM takes care of constantly monitoring the entire network for RF interference—and generating mitigation plans when it does occur. With a simple click of a button, IT staff can immediately remediate any co-channel interference on the network.
Various RF interference is one of the biggest factors in reduced network performance. The reduced network performance ultimately impacts the end-user experience. Latency-sensitive applications may behave erratically, with applications experiencing significant delays—or perhaps users notice throughput dropping that translates into longer wait times for web pages to load. Whatever the case may be, AI RRM reduces RF interference dramatically and constantly monitors for new anomalies. This ensures most interference is reduced in such a way as not to impact network performance.
RRM helps reduce operational expenses by delivering a more resilient network. RF interference issues manifest themselves through poor user experiences, which can be difficult to troubleshoot. User complaints about poor application experience or low throughput can consume a lot of IT resources and create unnecessary downtime. With AI RRM, IT has one less problem to worry about because the network is always being monitored and immediately remedied for RF interference.
In an education setting, reliable and agile connectivity is at the core of digital learning trends in modern classrooms. With AI RRM, students and teachers can spend more time on learning and less on slow downloads and unreliable connections. Areas with additional bandwidth needs are identified and preserved, while areas that need stability are also preserved.
With reliable and fast internet speeds, AI RRM can improve guests’ connectivity experiences, which helps improve their overall satisfaction and reduces complaints and poor reviews—and makes them more likely to return.
In managed Wi-Fi environments such as multi-dwelling units, delivering consistent and reliable Wi-Fi experience can make a huge difference in tenant experience and, therefore, plays a critical role in keeping occupancy rates as high as possible. RRM helps ensure the service provider delivers the best Wi-Fi experience possible across the property to all the tenants.
Discover how RUCKUS AI delivers robust service assurance for IT and business intelligence to line-of-business stakeholders to help you get the most from your enterprise network.
Our AI-enabled converged network management-as-a-service platform simplifies deployment, monitoring and management of your single-site or geographically distributed multi-site wired and wireless network.
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RUCKUS AI radio resource management (RRM) leverages AI and cloud technology to optimize wireless networks by analyzing data to adjust channel and power settings. This reduces interference and boosts performance. The dynamic system ensures efficient resource utilization, scalability, and enhanced user experience through continuous monitoring and actionable insights.
AI RRM is essential for optimizing wireless networks by dynamically adjusting channel and power settings. It minimizes interference, boosts performance, and ensures efficient resource utilization. This technology offers scalability, resilience, and enhanced user experience through continuous monitoring and proactive issue resolution, making networks more reliable and cost-effective.
RUCKUS AI RRM boosts network performance by dynamically optimizing channel and power settings to reduce interference. It automates complex tasks, allowing IT resources to focus on strategic initiatives. This technology ensures scalability, resilience, and improved user experience while lowering operational costs—making networks more efficient, reliable, and cost-effective.
For an in-depth look at RUCKUS AI RRM’s features and optimization, explore its full and partial optimization options, zone health insights, and interference reduction strategies. AI-driven RRM monitors network conditions, providing data-driven channel and bandwidth optimizations, easily applied with a click, enhancing network performance and efficiency.
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