Wi-Fi Channel Selection Based on Urban Interference Measurement

Increasing availability and usability enhancement of Wi-Fi in public areas has become more active. However, due to the dense deployment of Wi-Fi access points (APs), there is a chaotic and disorderly environment in urban areas. In our previous work, we have designed a function that predicts the network performance at each Wi-Fi AP according to the measurement of IEEE802.11 MAC frames sensed in each Wi-Fi channel. However, it was not examined in such scenarios assuming urban environment. We should understand the situations of current Wi-Fi AP deployment and traffic conditions, and should confirm the effectiveness of channel migration in such realistic environment. In this study, we proposed urban Wi-Fi channel utilization model based on real urban Wi-Fi measurement. We show that our method can predict the best channels and APs can migrate to them in the urban scenario.