Energy Detection and Noise performance analysis of Empirical mode decomposition for cognitive radio networks

An approach useful for processing sequences of non-stationary and non-linear signals in adaptive time-space analysis is empirical mode decomposition. Using intrinsic mode functions, EMD divides a series into two modes (IMFs). These modes give details about the numerous signals that are present in the data. This approach is particularly appropriate for non-stationary, non-linear natural signal analysis. One of the most significant problems with spectrum sensing is the noise uncertainty of the channel. Energy detectors based on EMD can help with the noise analysis of the communication network without the need for prior knowledge of the received signal. In this paper, we discuss the noise performance analysis, misdetection and sensing capabilities of the EMD-based wireless regional area communication network. WRAN is simulated in MATLAB and results for sensing capabilities and noise performance is obtained. From the results it is seen that probability of sensing in WRAN can be increased with sampling rate greater than twice the maximum frequency.