Optimized FFT and filter bank based spectrum sensing for Bluetooth signal

Wireless Local Area Networks (WLAN) and Wireless Personal Area Networks (WPAN) such as the Bluetooth are designed to operate in 2.4 GHz ISM band. Since both IEEE 802.15 based Bluetooth and IEEE 802.11 WLAN devices, among various others, use the same frequency band, interference may lead to significant performance degradation. Hence, Cognitive Radio (CR) technology has been considered for coordinating better the spectrum use in this band. Spectrum sensing is one of the most important functions in a CR. In this study, energy detector based spectrum sensing techniques are optimized for detecting Bluetooth signals, considering both the effect of non-flat power spectrum and frequency hopping characteristics. To reduce complexity and required number of samples for effective spectrum sensing, optimum weighting process is proposed for subband based spectrum sensing. Bluetooth sensing is analyzed also in the presence of WLANs at nearby frequencies.