Channel Identification Based on Cumulants, Binary Measurements, and Kernels
In this paper, we discuss the problem of channel identification by using eight algorithms. The first three algorithms are based on higher-order cumulants, the next three algorithms are based on binary output measurement, and the last two algorithms are based on reproducing kernels. The principal obj...
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doaj-0db88a809eaa4145951de1b99624214d2021-07-01T00:30:05ZengMDPI AGSystems2079-89542021-06-019464610.3390/systems9020046Channel Identification Based on Cumulants, Binary Measurements, and KernelsHicham Oualla0Rachid Fateh1Anouar Darif2Said Safi3Mathieu Pouliquen4Miloud Frikel5Department of Mathematics and Informatics, Sultan Moulay Slimane University, Po. Box 592, 23000 Beni Mellal, MoroccoDepartment of Mathematics and Informatics, Sultan Moulay Slimane University, Po. Box 592, 23000 Beni Mellal, MoroccoDepartment of Mathematics and Informatics, Sultan Moulay Slimane University, Po. Box 592, 23000 Beni Mellal, MoroccoDepartment of Mathematics and Informatics, Sultan Moulay Slimane University, Po. Box 592, 23000 Beni Mellal, MoroccoLaboratoire d’Automatique de Caen, UNICAEN, ENSICAEN, Normandie University, 6, B. Marchal Juin, 14050 Caen, FranceLaboratoire d’Automatique de Caen, UNICAEN, ENSICAEN, Normandie University, 6, B. Marchal Juin, 14050 Caen, FranceIn this paper, we discuss the problem of channel identification by using eight algorithms. The first three algorithms are based on higher-order cumulants, the next three algorithms are based on binary output measurement, and the last two algorithms are based on reproducing kernels. The principal objective of this paper is to study the performance of the presented algorithms in different situations, such as with different sizes of the data input or different signal-to-noise ratios. The presented algorithms are applied to the estimation of the channel parameters of the broadband radio access network (BRAN). The simulation results confirm that the presented algorithms are able to estimate the channel parameters with different accuracies, and each algorithm has its advantages and disadvantages for a given situation, such as for a given <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>S</mi><mi>N</mi><mi>R</mi></mrow></semantics></math></inline-formula> and data input. Finally, this study provides an idea of which algorithms can be selected in a given situation. The study presented in this paper demonstrates that the cumulant-based algorithms are more adequate if the data inputs are not available (blind identification), but the kernel- and binary-measurement-based methods are more adequate if the noise is not important (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>S</mi><mi>N</mi><mi>R</mi><mo>≥</mo><mn>16</mn></mrow></semantics></math></inline-formula> dB).https://www.mdpi.com/2079-8954/9/2/46channel identificationbinary measurementhigher-order cumulantsreproducing kernelbroadband radio access network (BRAN) |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Hicham Oualla Rachid Fateh Anouar Darif Said Safi Mathieu Pouliquen Miloud Frikel |
spellingShingle |
Hicham Oualla Rachid Fateh Anouar Darif Said Safi Mathieu Pouliquen Miloud Frikel Channel Identification Based on Cumulants, Binary Measurements, and Kernels Systems channel identification binary measurement higher-order cumulants reproducing kernel broadband radio access network (BRAN) |
author_facet |
Hicham Oualla Rachid Fateh Anouar Darif Said Safi Mathieu Pouliquen Miloud Frikel |
author_sort |
Hicham Oualla |
title |
Channel Identification Based on Cumulants, Binary Measurements, and Kernels |
title_short |
Channel Identification Based on Cumulants, Binary Measurements, and Kernels |
title_full |
Channel Identification Based on Cumulants, Binary Measurements, and Kernels |
title_fullStr |
Channel Identification Based on Cumulants, Binary Measurements, and Kernels |
title_full_unstemmed |
Channel Identification Based on Cumulants, Binary Measurements, and Kernels |
title_sort |
channel identification based on cumulants, binary measurements, and kernels |
publisher |
MDPI AG |
series |
Systems |
issn |
2079-8954 |
publishDate |
2021-06-01 |
description |
In this paper, we discuss the problem of channel identification by using eight algorithms. The first three algorithms are based on higher-order cumulants, the next three algorithms are based on binary output measurement, and the last two algorithms are based on reproducing kernels. The principal objective of this paper is to study the performance of the presented algorithms in different situations, such as with different sizes of the data input or different signal-to-noise ratios. The presented algorithms are applied to the estimation of the channel parameters of the broadband radio access network (BRAN). The simulation results confirm that the presented algorithms are able to estimate the channel parameters with different accuracies, and each algorithm has its advantages and disadvantages for a given situation, such as for a given <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>S</mi><mi>N</mi><mi>R</mi></mrow></semantics></math></inline-formula> and data input. Finally, this study provides an idea of which algorithms can be selected in a given situation. The study presented in this paper demonstrates that the cumulant-based algorithms are more adequate if the data inputs are not available (blind identification), but the kernel- and binary-measurement-based methods are more adequate if the noise is not important (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>S</mi><mi>N</mi><mi>R</mi><mo>≥</mo><mn>16</mn></mrow></semantics></math></inline-formula> dB). |
topic |
channel identification binary measurement higher-order cumulants reproducing kernel broadband radio access network (BRAN) |
url |
https://www.mdpi.com/2079-8954/9/2/46 |
work_keys_str_mv |
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