Blind spectrum sensing for cognitive radio based on complexity measurement

In this paper, we propose a new method of spectrum sensing based on complexity measures. Since the proposed method is applied in time domain, resulting in an overall reduction on the system complexity. Two complexity measures called Lempel-Ziv Complexity and Higuchi fractal dimension are investigated. Lempel-Ziv Complexity measure is a reliable and promising measure of complexity that can be calculated in a straight forward manner. On the other hand, Higuchi fractal dimension is a low complexity method that is frequently used to measure the time series complexity. Our proposed method is blind in the sense that it requires no prior knowledge of the channel, primary users signal, and noise variance. In simulation section, it is shown that for sufficiently large data lengths, the proposed method has better performance in contrast with other complexity based detectors such as Shannon entropy and spectral entropy based detectors.

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