Iterative Hard Thresholding with Combined Variable Step Size & Momentum-Based Estimator for Wireless Communication Systems with Dynamic Sparse Channels
The channel of the broadband wireless communications system can be modeled as a dynamic sparse channel. Such a channel is difficult to reconstruct by using linear channel estimators that are normally employed for dense channels’ estimation because of their lack of capacity to use the inherent channe...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-04-01
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| Series: | Electronics |
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| Online Access: | https://www.mdpi.com/2079-9292/10/7/842 |
| _version_ | 1797539162205716480 |
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| author | Olutayo Oyeyemi Oyerinde Adam Flizikowski Tomasz Marciniak |
| author_facet | Olutayo Oyeyemi Oyerinde Adam Flizikowski Tomasz Marciniak |
| author_sort | Olutayo Oyeyemi Oyerinde |
| collection | DOAJ |
| description | The channel of the broadband wireless communications system can be modeled as a dynamic sparse channel. Such a channel is difficult to reconstruct by using linear channel estimators that are normally employed for dense channels’ estimation because of their lack of capacity to use the inherent channel’s sparsity. This paper focuses on reconstructing this type of time-varying sparse channel by extending a recently proposed dynamic channel estimator. Specifically, variable step size’s mechanism and variable momentum parameter are incorporated into traditional Iterative Hard Thresholding-based channel estimator to develop the proposed Iterative Hard Thresholding with Combined Variable Step Size and Momentum (IHT-wCVSSnM)-based estimator. Computer simulations carried out in the context of a wireless communication system operating in a dynamic sparse channel, show that the proposed IHT-wCVSSnM-based estimator performs better than all the other estimators significantly. However, the computational complexity cost of the proposed estimator is slightly higher than the closely performing channel estimator. Nevertheless, the inherent complexity cost of the proposed estimator could be compromised in a situation where the system’s performance is of higher priority when compared with the computational complexity cost. |
| first_indexed | 2024-03-10T12:41:18Z |
| format | Article |
| id | doaj.art-274c2dcf371f4da5a4624827ee09081f |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-10T12:41:18Z |
| publishDate | 2021-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-274c2dcf371f4da5a4624827ee09081f2023-11-21T13:49:48ZengMDPI AGElectronics2079-92922021-04-0110784210.3390/electronics10070842Iterative Hard Thresholding with Combined Variable Step Size & Momentum-Based Estimator for Wireless Communication Systems with Dynamic Sparse ChannelsOlutayo Oyeyemi Oyerinde0Adam Flizikowski1Tomasz Marciniak2School of Electrical and Information Engineering, University of the Witwatersrand, Johannesburg 2050, South AfricaFaculty of Telecommunications, Computer Science and Electrical Engineering, UTP University of Science and Technology, 85-796 Bydgoszcz, PolandFaculty of Telecommunications, Computer Science and Electrical Engineering, UTP University of Science and Technology, 85-796 Bydgoszcz, PolandThe channel of the broadband wireless communications system can be modeled as a dynamic sparse channel. Such a channel is difficult to reconstruct by using linear channel estimators that are normally employed for dense channels’ estimation because of their lack of capacity to use the inherent channel’s sparsity. This paper focuses on reconstructing this type of time-varying sparse channel by extending a recently proposed dynamic channel estimator. Specifically, variable step size’s mechanism and variable momentum parameter are incorporated into traditional Iterative Hard Thresholding-based channel estimator to develop the proposed Iterative Hard Thresholding with Combined Variable Step Size and Momentum (IHT-wCVSSnM)-based estimator. Computer simulations carried out in the context of a wireless communication system operating in a dynamic sparse channel, show that the proposed IHT-wCVSSnM-based estimator performs better than all the other estimators significantly. However, the computational complexity cost of the proposed estimator is slightly higher than the closely performing channel estimator. Nevertheless, the inherent complexity cost of the proposed estimator could be compromised in a situation where the system’s performance is of higher priority when compared with the computational complexity cost.https://www.mdpi.com/2079-9292/10/7/842sparse wireless channelsbroadband wireless communication systemscompressive sensingtemporal correlationiterative hard thresholding |
| spellingShingle | Olutayo Oyeyemi Oyerinde Adam Flizikowski Tomasz Marciniak Iterative Hard Thresholding with Combined Variable Step Size & Momentum-Based Estimator for Wireless Communication Systems with Dynamic Sparse Channels Electronics sparse wireless channels broadband wireless communication systems compressive sensing temporal correlation iterative hard thresholding |
| title | Iterative Hard Thresholding with Combined Variable Step Size & Momentum-Based Estimator for Wireless Communication Systems with Dynamic Sparse Channels |
| title_full | Iterative Hard Thresholding with Combined Variable Step Size & Momentum-Based Estimator for Wireless Communication Systems with Dynamic Sparse Channels |
| title_fullStr | Iterative Hard Thresholding with Combined Variable Step Size & Momentum-Based Estimator for Wireless Communication Systems with Dynamic Sparse Channels |
| title_full_unstemmed | Iterative Hard Thresholding with Combined Variable Step Size & Momentum-Based Estimator for Wireless Communication Systems with Dynamic Sparse Channels |
| title_short | Iterative Hard Thresholding with Combined Variable Step Size & Momentum-Based Estimator for Wireless Communication Systems with Dynamic Sparse Channels |
| title_sort | iterative hard thresholding with combined variable step size momentum based estimator for wireless communication systems with dynamic sparse channels |
| topic | sparse wireless channels broadband wireless communication systems compressive sensing temporal correlation iterative hard thresholding |
| url | https://www.mdpi.com/2079-9292/10/7/842 |
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