Intelligent spectrum cooperative sensing method based on reinforcement learning
A reinforcement learning and collaborative sensing technology, applied in the field of spectrum sensing, can solve the problem that the detection ability of nodes is vulnerable to weakening and shadow effects, and achieve the effect of reducing scanning overhead and improving detection probability
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[0037] In order to facilitate those of ordinary skill in the art to understand the present invention, at first the technical terms are defined as follows:
[0038] Primary user: The user who has the priority to use the spectrum and is authorized to use the spectrum.
[0039] Secondary user: A user who can share spectrum resources with the primary user without posing a threat to the normal communication of the primary user.
[0040]Cooperative secondary user: a secondary user that helps other secondary users to perform spectrum sensing.
[0041] Q-Learning: A reinforcement learning algorithm, the agent perceives the environment by performing actions in the environment to obtain a certain reward, so as to learn the mapping strategy from state to action to maximize the reward value.
[0042] Bandit gambling machine: A reinforcement learning algorithm with n arms, each of which generates a reward with a certain unknown probability. The purpose of the algorithm is to obtain the ma...
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