{"title":"Non-Pilot-Aided Phase Estimator for 2-Source BPSK NOMA Channel with Closed-Form Solver","authors":"J. Sýkora","doi":"10.1109/WPMC48795.2019.9096099","DOIUrl":null,"url":null,"abstract":"In this paper, we focus on developing the non-pilot-aided phase CSE (Channel State Estimator) for 2-source BPSK generic NOMA (Non-Orthogonal Multiple Access) scenario. Apart of the exact CSE form, we develop also the low-SNR approximation which allows us to find a closed-form ML (Maximum Likelihood) solver. Both, exact and low-SNR (Signal to Noise Ratio) forms will be analyzed in terms of their fundamental mean-square error performance limits. We will use classical and mismatched model Cramer-Rao Lower Bound (CRLB) analysis. The numerical analysis shows that the mismatched low-SNR model CRLB nicely pairs the true estimator performance for low and medium SNRs.","PeriodicalId":298927,"journal":{"name":"2019 22nd International Symposium on Wireless Personal Multimedia Communications (WPMC)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 22nd International Symposium on Wireless Personal Multimedia Communications (WPMC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WPMC48795.2019.9096099","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 focus on developing the non-pilot-aided phase CSE (Channel State Estimator) for 2-source BPSK generic NOMA (Non-Orthogonal Multiple Access) scenario. Apart of the exact CSE form, we develop also the low-SNR approximation which allows us to find a closed-form ML (Maximum Likelihood) solver. Both, exact and low-SNR (Signal to Noise Ratio) forms will be analyzed in terms of their fundamental mean-square error performance limits. We will use classical and mismatched model Cramer-Rao Lower Bound (CRLB) analysis. The numerical analysis shows that the mismatched low-SNR model CRLB nicely pairs the true estimator performance for low and medium SNRs.