小波域在无线局域网络信号增强中的应用

Application of Wavelet Domain in Signal Enhancement of Wireless Local Area Network

为提升无线局域网络信号增强中的去噪效果,应用小波域思想,设计一种无线局域网络信号增强算法.针对无线局域网络,收集无线局域网络原始功率谱数据,通过功率谱拟合因子提取信号特征,识别网络信号.对于识别的无线局域网络信号,通过过零率和短时功率提取该信号.基于小波域对无线局域网络信号实施去噪处理,分为二维小波变换、二进剖分、信号重构三个步骤.通过贝叶斯方法,在实施稀疏字典训练的同时,实现无线局域网络信号的增强处理,在训练中结合K-SVD算法,将信号增强过程和稀疏字典学习过程进行迭代和融合.将MATLAB R2019a作为测试设计算法的实验平台,利用计算机开展算法性能测试.测试结果表明:设计算法的无线局域网络信号增强性能良好,同时信号去噪性能较强,说明算法满足设计需求,在完善细节后可以投入实际应用.

To improve the denoising effect in signal enhancement of wireless local area network,a signal enhancement algorithm of wireless local area network is designed by using the wavelet domain idea.The study plans to collect raw power spectrum data for wireless local area networks,extract signal features through power spectrum fitting factors,and identify network signals.The identified wireless local area network signal is extracted through zero crossing rate and short-term power.Implementing denoising processing for wireless local area network signals is based on wavelet domain.The signal processing is divided into three steps.The first step is two-dimensional wavelet transform,the second step is binary subdivision,and the third step is signal reconstruction.By using the Bayesian method,while implementing sparse dictionary training,the enhancement processing of wireless local area network signals is achieved.In the training,the K-SVD algorithm is combined to iterate and fuse the signal enhancement process and sparse dictionary learning process.The study uses MATLAB R2019a as the experimental platform for testing and designing algorithms,and conducts algorithm performance testing using a computer.The performance test results show that the signal enhancement of wireless local area network performance of the designed algorithm is good,and the signal denoising performance is strong,indicating that the algo-rithm meets the design requirements and can be put into practical application after improving the details.