{"title":"改进的小蜂窝网络稀疏度感知协同频谱估计","authors":"B. K. Das, Arpan Mukherjee","doi":"10.1109/CALCON49167.2020.9106549","DOIUrl":null,"url":null,"abstract":"In this paper, we propose some new adaptive approach for collaborative spectrum estimation in small scale Wireless Sensor Networks (WSN). The newly proposed regularized proportionate normalized least mean square (RPNLMS) diffusion adapt-then-combine (ATC) algorithm exploits the sparsity in the basis extension model for power spectral density (PSD) estimation. The proposed algorithm outperforms the existing sparsity aware ATC diffusion approach for the real-time collaborative spectrum estimation (CSE) in a WSN.","PeriodicalId":318478,"journal":{"name":"2020 IEEE Calcutta Conference (CALCON)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Improved Sparsity Aware Collaborative Spectrum Estimation for Small Cell Networks\",\"authors\":\"B. K. Das, Arpan Mukherjee\",\"doi\":\"10.1109/CALCON49167.2020.9106549\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose some new adaptive approach for collaborative spectrum estimation in small scale Wireless Sensor Networks (WSN). The newly proposed regularized proportionate normalized least mean square (RPNLMS) diffusion adapt-then-combine (ATC) algorithm exploits the sparsity in the basis extension model for power spectral density (PSD) estimation. The proposed algorithm outperforms the existing sparsity aware ATC diffusion approach for the real-time collaborative spectrum estimation (CSE) in a WSN.\",\"PeriodicalId\":318478,\"journal\":{\"name\":\"2020 IEEE Calcutta Conference (CALCON)\",\"volume\":\"21 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE Calcutta Conference (CALCON)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CALCON49167.2020.9106549\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE Calcutta Conference (CALCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CALCON49167.2020.9106549","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Improved Sparsity Aware Collaborative Spectrum Estimation for Small Cell Networks
In this paper, we propose some new adaptive approach for collaborative spectrum estimation in small scale Wireless Sensor Networks (WSN). The newly proposed regularized proportionate normalized least mean square (RPNLMS) diffusion adapt-then-combine (ATC) algorithm exploits the sparsity in the basis extension model for power spectral density (PSD) estimation. The proposed algorithm outperforms the existing sparsity aware ATC diffusion approach for the real-time collaborative spectrum estimation (CSE) in a WSN.