Problem Statement
The successful operation of cognitive radios depends largely on the results of spectrum sensing. Energy detection being the simplest to implement in terms of computational complexity has attracted a great deal of attention from researchers in order to improve on it, as its performance is weak when the SNR is low. Researches had proposed ways of performing energy detection and the use of time-frequency analysis show a great potential. However, the distribution techniques used so far suffers from cross-terms which affects the readability of the resulting distribution, leading to no improvement on the sensing threshold. Therefore, there is the need to employ a different distribution technique that can improve on the weakness of the techniques present in literature so as to improve on the sensing threshold, especially at low signal to noise ratio.
1.3 Aim and Objectives
The aim of this work is to determine an improved spectrum sensing threshold for energy detection through the use of time-frequency analysis by employing smoothed pseudo WignerVille distribution to analyze the energy spectral content of the primary user signal. The research work had the following objectives:
1. To simulate signals of an orthogonal frequency division multiple access (OFDMA) user with varying signal-to-noise ratios.
2. To apply the smoothed pseudo Wigner-Ville distribution technique on the generated signals to determine the energy spectral content and determining a better sensing threshold.
3. To compare the result obtained with the work of Monfared et al., (2013) in order to establish the validity and improvement made of the technique used in this work.
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