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20 October 2020

SoftAtHome extends home WiFi reach within Telenor footprint

WiFi mesh specialist SoftAtHome is working with Kaon Media to deploy gateways that will help to future-proof Telenor’s broadband business in Denmark. The suppliers have delivered Telenor Denmark a new mesh-enabled home gateway, integrating the Connect’ON and WiFi’ON technologies from SoftAtHome onto Kaon hardware, and even supporting 5G connectivity alongside fiber.

There is, however, no sign of the SoftAtHome’s Eyes’ON software, which applies machine learning to WiFi optimization, gathering user data to send actionable insights back to the service provider for proactively improving customer quality of experience. Without Eyes’ON, there appears to be a missing analytics element, although Telenor may well have its own analytics dashboard.

Telenor operates triple play services across four Nordic countries – Norway, Sweden, Denmark and Finland – and the operator’s Norwegian unit deployed a WiFi Amplifier powered by SoftAtHome’s WiFi’ON technology in summer 2019. The WiFi’ON software automatically selects the best network frequency within the home gateway, applying the MQTT protocol for real-time data transfer to the operator for enabling faster software updates via Telenor’s Skynet service.

SoftAtHome has become a familiar name among Nordic operators. Danish telco TDC selected it last year, running software on home gateways that combine two bonded VDSL lines, high quality TV and uninterrupted communications with 4×4 WiFi. This preceded the major deal at Telenor in Norway, so it’s possible SoftAtHome could soon have a clean sweep of Telenor’s footprint.

Meanwhile, Telenor Sweden, together with Orange Labs, has funded Norwegian WiFi start-up Domos to train machine learning algorithms, with the goal of sniffing out hidden node issues in WiFi networks. The development will expand on the Broadband Forum’s work on the QED framework, with Orange and Telenor deploying probes on existing CPE, including SoftAtHome hardware, to achieve machine learning models capable of estimating network quality. Domos data suggests that hidden node issues are a major contributor to WiFi performance anomalies.