Broadband anti-interference system based on deep reinforcement learning and anti-interference method

Abstract

The invention discloses a broadband anti-interference system based on deep reinforcement learning and an anti-interference method. A group of transmitter and receiver pairs are considered as a communication user; when a user performs communication, a plurality of jammers perform malicious interference on the user, the user intelligently selects a communication frequency from a wide frequency bandby utilizing spectrum sensing information, the user decision process is modeled into a Markov decision process, and a user frequency decision is optimized to maximize the throughput of the user. According to the anti-interference method, a layered deep reinforcement learning algorithm is designed, then a two-dimensional window is controlled according to a frequency band decision, a frequency spectrum waterfall plot of a corresponding frequency band is selected, and a frequency selection network is designed for learning to obtain an optimal frequency decision. The broadband anti-interference system is complete in model and reasonable and effective in design algorithm, and compared with a traditional deep reinforcement learning anti-interference algorithm, iteration time and calculation complexity are effectively reduced while an excellent anti-interference effect is guaranteed.

Description

technical field [0001] The present invention relates to the field of wireless communication technology, in particular to a broadband anti-interference system and anti-interference method based on deep reinforcement learning, and in particular to a broadband anti-interference model and an anti-interference algorithm based on layered deep reinforcement learning. Background technique [0002] In the field of communication, a signal is a physical quantity that represents a message. For example, an electrical signal can represent different messages through changes in amplitude, frequency, and phase. Interference is the impairment of reception of a desired signal. With the rapid development of wireless communication technology, interference, especially intelligent interference, is posing a huge threat to the security of our country's information and related fields. In the field of military communications, with the deep integration of artificial intelligence and communication coun...

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Problems solved by technology

[0004] In order to solve the above problems, the present invention provides a broadband anti-jamming system and anti-jamming method based on deep reinforcement learning, which can well describe the broadband anti-jamming scene based on deep reinforcement learning algorithm, and effectively avoid most of the existing technologies. Anti-jamming research based on deep reinforcement learning considers less decision-making, is only suitable for narrowband channel selection, and cannot be applied to wideband channel selection.

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