Secure Cooperative Transmission With Imperfect Channel State Information Based on BPNN

In this paper, we study a secure cooperative transmission system in which a transmitter (Alice) intends to send a secret message to an authorized receiver (Bob), with the aid of a friendly private cooperative jammer (Oscar), in the presence of a malicious eavesdropper (Eve). Specifically, artificial noise (AN) assisted secrecy beamforming is utilized for secure transmission. Under the imperfect channel state information (CSI) of legitimate channels and the statistic CSI of illegitimate channels, the optimal power allocation ratio between the information-bearing signal and the AN signal for maximizing secrecy rate is derived. Through mathematical analysis, we notice that the high channel estimation error is greatly detrimental to the realization of the positive secrecy rate in secure system. For overcoming this drawback, back propagation neural network (BPNN) is employed for a high accuracy channel estimation to simulate a realistic security communication scenario. The numerical results show that the channel estimation errors result in a decrease in secrecy rate, but the BPNN channel estimator still can guarantee secure transmission that verifies the feasibility of the application of physical layer security. Analytical derivations and numerical simulations are presented to validate the correctness of obtained expressions and our analysis.