E. Mostafapour, Amin Hoseini, J. Nourinia, M. Amirani
{"title":"基于自适应增量策略的分布式传感器网络信道估计","authors":"E. Mostafapour, Amin Hoseini, J. Nourinia, M. Amirani","doi":"10.1109/KBEI.2015.7436147","DOIUrl":null,"url":null,"abstract":"In this paper we will consider channel estimation task with a wireless sensor network. We assume the fading channel coefficients are produced by a Rayleigh process and we construct the unknown weight vector using these coefficients. We used an incremental LMS algorithm over sensor network and analyzed the tracking performance of this algorithm in channel estimation task. Up until now such analysis was not possible because we did not have access to the theoretical closed form results for tracking EMSE and MSD of distributed networks. Computer experiments present a clear match between theoretical and simulation results.","PeriodicalId":168295,"journal":{"name":"2015 2nd International Conference on Knowledge-Based Engineering and Innovation (KBEI)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Channel estimation with adaptive incremental strategy over distributed sensor networks\",\"authors\":\"E. Mostafapour, Amin Hoseini, J. Nourinia, M. Amirani\",\"doi\":\"10.1109/KBEI.2015.7436147\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we will consider channel estimation task with a wireless sensor network. We assume the fading channel coefficients are produced by a Rayleigh process and we construct the unknown weight vector using these coefficients. We used an incremental LMS algorithm over sensor network and analyzed the tracking performance of this algorithm in channel estimation task. Up until now such analysis was not possible because we did not have access to the theoretical closed form results for tracking EMSE and MSD of distributed networks. Computer experiments present a clear match between theoretical and simulation results.\",\"PeriodicalId\":168295,\"journal\":{\"name\":\"2015 2nd International Conference on Knowledge-Based Engineering and Innovation (KBEI)\",\"volume\":\"40 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 2nd International Conference on Knowledge-Based Engineering and Innovation (KBEI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/KBEI.2015.7436147\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 2nd International Conference on Knowledge-Based Engineering and Innovation (KBEI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/KBEI.2015.7436147","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Channel estimation with adaptive incremental strategy over distributed sensor networks
In this paper we will consider channel estimation task with a wireless sensor network. We assume the fading channel coefficients are produced by a Rayleigh process and we construct the unknown weight vector using these coefficients. We used an incremental LMS algorithm over sensor network and analyzed the tracking performance of this algorithm in channel estimation task. Up until now such analysis was not possible because we did not have access to the theoretical closed form results for tracking EMSE and MSD of distributed networks. Computer experiments present a clear match between theoretical and simulation results.