Dynamic Channel Selection in cognitive radio WiFi networks: An experimental evaluation

Increased wireless network intelligence and interference awareness enabled by cognitive radio can lead to improved spectrum utilization and network performance. Using a cognitive radio platform developed by Communication Research Centre Canada (CRC), in this work we propose and implement a novel Dynamic Channel Selection (DCS) algorithm for a network of sectorized WiFi cells. The proposed algorithm leverages the ability of underlying cognitive radio platform to continuously monitor and identify WiFi interference sources and relieves the network operator of having to manually configure and update the channels across the network. The algorithm's performance is evaluated using field experiments in both rural and urban environments which demonstrate significant improvement in terms of spectrum efficiency as well as robustness to variations in the interference. The main contributions of this work include the proposed DCS algorithm as well as offering a prime example of cognitive radio's potential in practical deployments. In addition, an overview of the CORAL platform summarizing its major components and capabilities is provided.