Spectrum sensing assisted by windowing for fast time-varying channel
Résumé
In this paper, we introduce new totally blind spectrum sensing (SS) algorithms, for fast time-varying channel, based on eigenvalue decomposition (EVD) of the covariance matrix of the received signal. The new scheme is based on the sliding window whose the size depends on the coherence time of the channel. First, we evaluate the impact of the mobility on the detection performance. Then, by applying EVD in each window, we focus our study on the maximal estimated largest eigenvalue (MELE). We provide simulation results in order to validate the proposed theoretical expression of the probability density function of the MELE. Finally, simulation results illustrate the performance of the contributions and are compared to other SS methods.
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