An Adaptive Enhancement Algorithm for Weak Signals in Communication Networks Based on Wavelet Transform

Abstract

In order to improve the accuracy of network weak signal prediction, combined with the changing characteristics of network signals, and considering the limitations of the current network signal prediction model, a wavelet transform-based communication network weak signal enhancement adaptive algorithm is proposed. Compressing and decompressing signal data from weak signals in communication networks is essential for the real-time distribution and synchronization of network communications. It is used to evaluate the modulation mode of a weak network signal. This is the content of joint research on weak signal processing and pattern recognition in communication networks. This paper takes wavelet transform as the theoretical basis of the research, uses the adaptive enhancement algorithm as the main research algorithm, and integrates its important contents to analyze and research the optimization of the adaptive enhancement algorithm. This paper takes the classic adaptive enhancement algorithm as the research object, and optimizes and improves the weak signal of the communication network respectively. The adaptive enhancement algorithm in wavelet transform can be regarded as a kind of node sorting algorithm, so it can be used to construct weak signal strategy of communication network. The experimental results show that this research has a better effect on using wavelet transform and adaptive enhancement algorithm parameters to estimate the weak signal prediction value of the communication network and calculate the prediction error. From the prediction error of the adaptive enhancement algorithm, check whether the observed signal contains a weak signal.