Spectrum sensing method based on quantum particle swarm optimization extreme learning machine
A quantum particle swarm and extreme learning machine technology, applied in the field of spectrum sensing algorithm, can solve the problems of low detection rate of main user signal, easy overfitting, poor network structure, etc., to improve detection accuracy and low false alarm probability , Overcome the effect of large classification accuracy error
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[0038] Specific implementation mode 1. Combination Figure 1 to Figure 6 Description of this embodiment, based on the spectrum sensing method of quantum particle swarm optimization extreme learning machine, the method is implemented by the following steps:
[0039] Step 1, extracting signal cycle spectrum features and energy features;
[0040] Spectrum sensing is an important technology in cognitive radio. It detects whether the primary user is using the frequency band and prevents the cognitive user from interfering with the use of the primary user. It is established as a model of a binary hypothesis testing problem, and the established model (1) is shown in the formula:
[0041]
[0042] In formula (1) H 0 Under the assumption that the receiver only receives noise, that is, the primary user signal does not exist at this time; H 1 It is assumed that the signal received by the receiver contains the main user signal and noise, that is, the main user signal exists at this ...
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