Channel Clustering and Probabilistic Channel Visiting Techniques for WLAN Interference Mitigation in Bluetooth Devices

Abstract

Since Bluetooth and wireless local area network (WLAN) technologies both operate at the 2.4-GHz industrial, scientific, and medical (ISM) band, the two types of devices may suffer from mutual interference and performance degradations. In this paper, we propose two new techniques, channel clustering and probabilistic channel visiting, to effectively improve the existing coexistence and interference mitigation mechanisms. The channel clustering technique employs statistical pattern recognition to classify the status of Bluetooth channels more accurately. The probabilistic channel visiting is used to more equitably allocate the channel resources between Bluetooth and WLAN devices. The effectiveness of these techniques is quantified by simulations. Results show that both techniques are beneficial in improving the performance of the existing mechanisms.