Self-adaptive Machine Learning Approach for Real-time Tuning of IEEE 802.11 PHY and MAC layers

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https://www.fed4fire.eu/demo-stories/oc8/smart/

The worldwide demand for wireless access networks providing very high throughputs has been increasing exponentially, namely due to bandwidth-hungry applications such as high definition video streaming and augmented reality. In order to fulfil these requirements, the Wi-Fi standard was enriched and new parameters have been proposed for both physical (PHY) and media access control (MAC) layers, including channel bonding, a short guard interval (SGI), and advanced modulation and coding schemes (MCS). However, the high variability of the signal strength in the wireless radio channel, allied to the channel asymmetry, turns the selection of optimal configurations for these parameters a challenge.
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