SPARSE CHANNEL ESTIMATION FOR AERONAUTICAL TELEMETRY
| dc.contributor.advisor | Rice, Michael | en |
| dc.contributor.author | Hogstrom, Christopher | |
| dc.date.accessioned | 2017-06-20T15:57:04Z | |
| dc.date.available | 2017-06-20T15:57:04Z | |
| dc.date.issued | 2016-11 | |
| dc.identifier.issn | 0884-5123 | |
| dc.identifier.issn | 0074-9079 | |
| dc.identifier.uri | http://hdl.handle.net/10150/624251 | |
| dc.description.abstract | This paper applies a compressed sensing (CS) algorithm to SOQPSK-TG waveform samples to reconstruct a sparse channel. The mean squared error (MSE) is computed between the estimated channel and the true channel. The estimated channel is then used in an equalized system and a bit error rate (BER) curve is calculated. The results are then compared to a Maximum Likelihood (ML) estimator. The CS estimate does not produce significant gains but it doesn’t break anything either. | |
| dc.description.sponsorship | International Foundation for Telemetering | en |
| dc.language.iso | en_US | en |
| dc.publisher | International Foundation for Telemetering | en |
| dc.relation.url | http://www.telemetry.org/ | en |
| dc.rights | Copyright © held by the author; distribution rights International Foundation for Telemetering | en |
| dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | |
| dc.title | SPARSE CHANNEL ESTIMATION FOR AERONAUTICAL TELEMETRY | en_US |
| dc.type | text | en |
| dc.type | Proceedings | en |
| dc.contributor.department | Brigham Young University | en |
| dc.identifier.journal | International Telemetering Conference Proceedings | en |
| dc.description.collectioninformation | Proceedings from the International Telemetering Conference are made available by the International Foundation for Telemetering and the University of Arizona Libraries. Visit http://www.telemetry.org/index.php/contact-us if you have questions about items in this collection. | en |
| refterms.dateFOA | 2018-09-11T20:15:29Z | |
| html.description.abstract | This paper applies a compressed sensing (CS) algorithm to SOQPSK-TG waveform samples to reconstruct a sparse channel. The mean squared error (MSE) is computed between the estimated channel and the true channel. The estimated channel is then used in an equalized system and a bit error rate (BER) curve is calculated. The results are then compared to a Maximum Likelihood (ML) estimator. The CS estimate does not produce significant gains but it doesn’t break anything either. |
