Wireless communication anti-eavesdrop interference power control algorithm based on Q learning
A technology of jamming power and wireless communication, which is applied in the field of machine learning and physical layer security, can solve problems such as fluctuations in transmission power, and achieve the effects of minimizing network energy loss, maximizing information security, and maximizing network energy loss
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[0043] Such as figure 1 As shown, a wireless communication anti-eavesdropping interference power control algorithm based on Q learning includes the following steps:
[0044] Step 1: Initialize the transmit power P s , safety evaluation coefficient ρ, interference power x i and the rank t of working hours s .
[0045] S101. Set the transmit power P s The average division is divided into n files, and the transmission power set is recorded as L, so that L=[P 1 ,P 2 ,···,P n ];
[0046] S102. Determine the safety assessment coefficient ρ made jointly by the legitimate sender and the receiver, ρ∈[0,1];
[0047] S103. Transmit power P from the legitimate sender s and the safety evaluation coefficient ρ are combined to obtain a state set, denoted as S, S=[P s , ρ];
[0048] S104. Divide the jamming power of friendly jammers into n levels on average, record the jamming power action set of friendly jammers as A, let A=[x 1 ,x 2 ,···,x n ];
[0049] S105. Set the working ...
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