Evaluation method of wireless network communication anti-jamming performance based on rough set
Rui Wang · 2022
The transmission signal of large-scale multi-input multi-output wireless network facing medium and high frequency de-cellular is interfered by the intersymbol fluctuation of spectrum disturbance noise, which leads to the distortion of the output error code in the far-field and near-field areas of antenna array, so it is necessary to carry out anti-interference filtering processing of wireless network communication. This paper proposes a filtering technology of communication interference signal in medium and high frequency de-cellular large-scale multi-input multi-output wireless network based on rough set spectrum parameter estimation. Extract that characteristic quantity of the output signal of the medium-high frequency cellular large-scale MIMO wireless network, using sparse Bayesian learn and rough set estimation method of channel parameters to enhance the line spectrum of the communication signal of the medium-high frequency cellular large-scale MIMO wireless network, and extracting the rough vector characteristic matching set of the communication transmission signal of the medium-high frequency cellular large-scale MIMO wireless network by combine the array antenna correlation matching method, Block sparse Bayesian learning is used to decompose the spectrum of the signal, and the posterior probability estimation method of the channel vector is used to decompose the feature and separate the blind source of the extracted interference signal, so as to realize the effective filtering and immunity evaluation of the interference signal in the large-scale multi-input multi-output wireless network with medium and high frequency de-cellular. The simulation results show that the filtering performance of communication interference signals in large-scale multi-input multi-output wireless network with medium and high frequency de-cellular is good, the signal-to-noise ratio of output signals is high, and the signal fidelity and anti-interference evaluation ability of large-scale multi-input multi-output wireless network transmission are improved.