Channel Identification Based on Cumulants, Binary Measurements, and Kernels
| Autor: | Anouar Darif, Mathieu Pouliquen, Said Safi, Miloud Frikel, Rachid Fateh, Hicham Oualla |
|---|---|
| Přispěvatelé: | Laboratoire d'automatique de Caen (LAC), École Nationale Supérieure d'Ingénieurs de Caen (ENSICAEN), Normandie Université (NU)-Normandie Université (NU)-Université de Caen Normandie (UNICAEN), Normandie Université (NU), Université Sultan Moulay Slimane (USMS ) |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
0209 industrial biotechnology
Information Systems and Management Computer Networks and Communications Computer science higher-order cumulants Binary number 02 engineering and technology broadband radio access network (BRAN) [SPI.AUTO]Engineering Sciences [physics]/Automatic Systems engineering binary measurement TA168 020901 industrial engineering & automation channel identification Broadband 0202 electrical engineering electronic engineering information engineering T1-995 Cumulant Technology (General) Radio access network reproducing kernel 020206 networking & telecommunications Noise Identification (information) Control and Systems Engineering Modeling and Simulation Kernel (statistics) Computer Science::Programming Languages Algorithm Software Communication channel |
| Zdroj: | Systems Volume 9 Issue 2 Systems, Vol 9, Iss 46, p 46 (2021) Systems, MDPI, 2021, 9 (2), pp.46. ⟨10.3390/systems9020046⟩ |
| ISSN: | 2079-8954 |
| DOI: | 10.3390/systems9020046 |
| Popis: | 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 SNR 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 (SNR≥16 dB). |
| Databáze: | OpenAIRE |
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