Reinforcement Learning for Wi-Fi: Channel Planning in MDUs
In dense multi-dwelling units (MDUs), Wi-Fi interference and suboptimal performance are constant challenges. Traditional static channel planning falls short in these dynamic environments. This blog explores how reinforcement learning (RL)—a branch of AI—can intelligently and autonomously optimize channel assignments across multiple access points (APs). By continuously analyzing real-time network conditions and adapting to changes, RL enables smarter, faster, and more efficient Wi-Fi management. Discover how this cutting-edge approach can reduce interference, enhance performance, and offer ISPs a scalable, vendor-neutral solution for modern Wi-Fi networks.
Compare OpenWrt + OpenWiFi with Plume, Calix & Eero: Which One Wins for ISPs?
As Internet Service Providers (ISPs) seek to deliver high-performance, cost-effective, and flexible Wi-Fi solutions to their customers, the choice between open-source and proprietary platforms becomes more critical than ever. In this blog, we’ll explore how the OpenWrt + OpenWiFi stack compares against popular proprietary home WiFi platforms—focusing on cost, flexibility, innovation, and operational control. Why […]