Novel modified energy detection spectrum sensing technique for FM wireless microphone signals

Spectrum Sensing is an important functionality of Cognitive Radio (CR). Accuracy and speed of estimation are the key indicators to select the appropriate spectrum sensing technique. In this paper, we focus on spectrum sensing of narrowband wireless microphone (WM) signals using the modified periodogram and Welch method for different window types. It is well-known that the power of the WM signal is highly concentrated in the frequency domain, particularly under silence. Due to this property, spectrum sensing can be performed by what we call modified energy detection (MED) which applies of two techniques. First, a proposed window is used to reduce the height of the side-lobes or spectral leakage, which is called modified periodogram method. This increases the difference between the signal PSD peak and the noise level resulting in better detection. Second, Welch's method is used, which takes the average of the modified periodograms using overlapped windows that decreases the noise variance compared to single periodogram estimation. The performance of the proposed spectrum sensing technique is demonstrated by computer simulations.