Map-assisted Internet of Vehicles anti-interference communication method based on reinforcement learning
A communication method and reinforcement learning technology, applied in the fields of wireless communication, Internet of Vehicles and information security, can solve the problems of blocking the wireless communication of vehicle communication equipment and passenger mobile equipment, reducing the quality of service for communication users, and increasing the energy consumption of equipment communication. The effect of reducing communication energy consumption, improving message transmission reliability, reducing transmission power and bit error rate
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[0030] In order to make the objectives, technical solutions and advantages of the present invention clearer, the following embodiments will further illustrate the present invention with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are only used to explain the present invention, but not to limit the present invention.
[0031] The embodiment of the present invention includes the following steps:
[0032] Step 1: The available transmission power and the number of channels of the wireless communication device of the Internet of Vehicles are N=5 and C=4, respectively, and the transmission power is recorded. optional channel X={[20, 0], [20, 1]...[100, 4]}.
[0033] Step 2: Construct neural network A and network B, respectively composed of 4 fully connected layers, and their initial network parameters ω 1 =ω 2 =0. The first fully connected layer consists of 6 neurons, the second and third fully connected layer...
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