When the network is subject to intrusion and attack, the node output channel equalization will be affected, resulting in bit error and distortion in the output of network transmission symbols. In order to improve the anti-attack ability and equalization of network node, a network intrusion feature map node equalization algorithm based on modified variable step-size constant modulus blind equalization algorithm (MISO-VSS-MCMA) is proposed. In this algorithm, the node transmission channel model after network intrusion is constructed, and sequential processing is performed to intruded nodes with the variable structure feedback link control method. With diversity spread spectrum technology, the channel loss after network intrusion is compensated and the network intrusion map feature is extracted. According to the extracted feature amount, channel equalization processing is performed for the cost function with the MISO-VSS-MCMA method to reduce the damage of network intrusion to the channel. Simulation results show that in node transmission channel equalization after network intrusion, this algorithm can reduce the error bit rate of signal transmission in network, and provide a good ability of correcting phase deflection in the output constellation, thus avoiding the error bit distortion and channel damage caused by network intrusion to the signal with a good equalization effect. This algorithm provides stronger convergence and map concentration, which demonstrates that its anti-interference and signal recovery capabilities are better, so it improves the anti-attack ability of the network.
A Novel Implementation of Variable Step Size Constant Modulus Algorithm with LMS update
