{"title":"Impulsive noise mitigation using an adaptive WMA-MVDR estimator for array based wireless communications","authors":"Xing Guang John Yang, W. Ser, S. G. Razul, C. See","doi":"10.1109/ICICS.2013.6782865","DOIUrl":null,"url":null,"abstract":"In this paper, we propose an adaptive WMA-MVDR estimator for mitigating impulsive noise in a multiple-access interference (MAI) environment. A time-domain Bernoulli-Gaussian process is used to model the impulsive noise. The estimator comprises two stages of processing: an adaptive window-mean amplitude (WMA) filter and a modified MVDR (Minimum Variance Distortionless Response) estimator. Numerical results show that the bit error rate (BER) performance of the proposed algorithm outperforms some existing estimators under the impulsive noise environment.","PeriodicalId":184544,"journal":{"name":"2013 9th International Conference on Information, Communications & Signal Processing","volume":"39 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 9th International Conference on Information, Communications & Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICICS.2013.6782865","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, we propose an adaptive WMA-MVDR estimator for mitigating impulsive noise in a multiple-access interference (MAI) environment. A time-domain Bernoulli-Gaussian process is used to model the impulsive noise. The estimator comprises two stages of processing: an adaptive window-mean amplitude (WMA) filter and a modified MVDR (Minimum Variance Distortionless Response) estimator. Numerical results show that the bit error rate (BER) performance of the proposed algorithm outperforms some existing estimators under the impulsive noise environment.