{"title":"Ionosphere characterization using received HF communications","authors":"S. Lynch, E. Bertot, K. Bales","doi":"10.1109/APWC.2016.7738177","DOIUrl":null,"url":null,"abstract":"In HF communications, both intra-and inter-symbol fading and losses can vary significantly between two nodes. While these channel effects may be problematic for maintaining a link, they may provide information about the structure of the ionosphere. We utilize our previously developed communications simulator which simulates a received RF data stream for a given channel response. Using channel responses estimated from the output from a ray-based propagation model, as well as modified modules within a Software Defined Radio framework, we map propagation channel variations to the received signal demodulator's corrective filters. By minimizing a cost function that compares predicted channel reponses to the true channel response, we devise an algorithm that enables estimating ionosphere features from the received signals.","PeriodicalId":143796,"journal":{"name":"2016 IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications (APWC)","volume":"116 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications (APWC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APWC.2016.7738177","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In HF communications, both intra-and inter-symbol fading and losses can vary significantly between two nodes. While these channel effects may be problematic for maintaining a link, they may provide information about the structure of the ionosphere. We utilize our previously developed communications simulator which simulates a received RF data stream for a given channel response. Using channel responses estimated from the output from a ray-based propagation model, as well as modified modules within a Software Defined Radio framework, we map propagation channel variations to the received signal demodulator's corrective filters. By minimizing a cost function that compares predicted channel reponses to the true channel response, we devise an algorithm that enables estimating ionosphere features from the received signals.