Improved Periodogram-Based spectrum sensing technique for FM wireless microphone signals

Spectrum sensing has been identified as a key enabling functionality to ensure that cognitive radios would not interfere with the primary users, by reliably detecting primary user signal. In this paper, the primary user signal is wireless microphone (WM) signal. The power of the WM signal is highly concentrated in the frequency domain. Due to this property, we focus on spectrum sensing in the frequency domain. The most common and simplest method is energy detection (ED), which suffers from large degradation in performance under low signal-to-noise ratio (SNR) environment. To overcome this problem, an Improved Periodogram-Based (IPB) technique is proposed. Averaging the power spectral density (PSD) of segmented overlapped samples with different window shapes is proposed in IPB. We also examine the optimum segmentation for a given sensing time and obtain the optimum number of segments in the region satisfying the probability of false alarm constraint.