Collaborative Blind Equalization for Time-Varying OFDM Applications Enabled by Normalized Least Mean and Recursive Square Methodologies

In this work, a collaborative blind equalization method for the orthogonal frequency division multiplexing (OFDM) signals in time-varying channels is presented. Equalizers are eliminated the inter-symbol interference (ISI) in the received signals caused by channel distortions. The conventional adapt...
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Gespeichert in:

Autor*in:	Li Deng [verfasserIn] Yong Mao Huang [verfasserIn] Qian Chen [verfasserIn] Yuanhua He [verfasserIn] Xiubao Sui [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2020

Schlagwörter:	Blind equalization normalized least mean square (NLMS) orthogonal frequency division modulation (OFDM) recursive least square (RLS) time-varying channel

Übergeordnetes Werk:	In: IEEE Access - IEEE, 2014, 8(2020), Seite 103073-103087
Übergeordnetes Werk:	volume:8 ; year:2020 ; pages:103073-103087

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1109/ACCESS.2020.2999387

Katalog-ID:	DOAJ072490063

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520			\|a In this work, a collaborative blind equalization method for the orthogonal frequency division multiplexing (OFDM) signals in time-varying channels is presented. Equalizers are eliminated the inter-symbol interference (ISI) in the received signals caused by channel distortions. The conventional adaptive equalization requires sending the training-sequences periodically to synthesize the channel model, which can only provide redundant information, and consequently decrease the channel utilization and complicate the system. To overcome this drawback, the blind equalization methods, which need not send the training-sequences periodically, is developed. However, the conventional blind equalization methods still suffer from various disadvantages. The normalized least mean square (NLMS) method is able to converge rapidly, whereas its equalization error is relatively large. The recursive least square (RLS) method has smaller steady-state error but low convergence rate, demanding massive training sequences. To further enhance the equalization performance of time-varying OFDM systems, which is typically with massive calculation, a collaborative blind equalization is proposed in this work, which is able to effectively combine the characteristics of the conventional NLMS and RLS methods together. The numerical simulations demonstrate the proposed LM-RS method can exhibit quite good performance. Particularly, as compared with the conventional NLMS and RLS methods, the proposed LM-RS method achieves smaller steady-state error and lower complexity, as well as similar convergence rate. All these results indicate that the proposed collaborative LM-RS blind equalization method is suitable for the OFDM transmission under the time-varying wireless application environments.
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allfields	10.1109/ACCESS.2020.2999387 doi (DE-627)DOAJ072490063 (DE-599)DOAJb1c952038f61433f8adb7addc371b297 DE-627 ger DE-627 rakwb eng TK1-9971 Li Deng verfasserin aut Collaborative Blind Equalization for Time-Varying OFDM Applications Enabled by Normalized Least Mean and Recursive Square Methodologies 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this work, a collaborative blind equalization method for the orthogonal frequency division multiplexing (OFDM) signals in time-varying channels is presented. Equalizers are eliminated the inter-symbol interference (ISI) in the received signals caused by channel distortions. The conventional adaptive equalization requires sending the training-sequences periodically to synthesize the channel model, which can only provide redundant information, and consequently decrease the channel utilization and complicate the system. To overcome this drawback, the blind equalization methods, which need not send the training-sequences periodically, is developed. However, the conventional blind equalization methods still suffer from various disadvantages. The normalized least mean square (NLMS) method is able to converge rapidly, whereas its equalization error is relatively large. The recursive least square (RLS) method has smaller steady-state error but low convergence rate, demanding massive training sequences. To further enhance the equalization performance of time-varying OFDM systems, which is typically with massive calculation, a collaborative blind equalization is proposed in this work, which is able to effectively combine the characteristics of the conventional NLMS and RLS methods together. The numerical simulations demonstrate the proposed LM-RS method can exhibit quite good performance. Particularly, as compared with the conventional NLMS and RLS methods, the proposed LM-RS method achieves smaller steady-state error and lower complexity, as well as similar convergence rate. All these results indicate that the proposed collaborative LM-RS blind equalization method is suitable for the OFDM transmission under the time-varying wireless application environments. Blind equalization normalized least mean square (NLMS) orthogonal frequency division modulation (OFDM) recursive least square (RLS) time-varying channel Electrical engineering. Electronics. Nuclear engineering Yong Mao Huang verfasserin aut Qian Chen verfasserin aut Yuanhua He verfasserin aut Xiubao Sui verfasserin aut In IEEE Access IEEE, 2014 8(2020), Seite 103073-103087 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:8 year:2020 pages:103073-103087 https://doi.org/10.1109/ACCESS.2020.2999387 kostenfrei https://doaj.org/article/b1c952038f61433f8adb7addc371b297 kostenfrei https://ieeexplore.ieee.org/document/9106318/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2020 103073-103087
spelling	10.1109/ACCESS.2020.2999387 doi (DE-627)DOAJ072490063 (DE-599)DOAJb1c952038f61433f8adb7addc371b297 DE-627 ger DE-627 rakwb eng TK1-9971 Li Deng verfasserin aut Collaborative Blind Equalization for Time-Varying OFDM Applications Enabled by Normalized Least Mean and Recursive Square Methodologies 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this work, a collaborative blind equalization method for the orthogonal frequency division multiplexing (OFDM) signals in time-varying channels is presented. Equalizers are eliminated the inter-symbol interference (ISI) in the received signals caused by channel distortions. The conventional adaptive equalization requires sending the training-sequences periodically to synthesize the channel model, which can only provide redundant information, and consequently decrease the channel utilization and complicate the system. To overcome this drawback, the blind equalization methods, which need not send the training-sequences periodically, is developed. However, the conventional blind equalization methods still suffer from various disadvantages. The normalized least mean square (NLMS) method is able to converge rapidly, whereas its equalization error is relatively large. The recursive least square (RLS) method has smaller steady-state error but low convergence rate, demanding massive training sequences. To further enhance the equalization performance of time-varying OFDM systems, which is typically with massive calculation, a collaborative blind equalization is proposed in this work, which is able to effectively combine the characteristics of the conventional NLMS and RLS methods together. The numerical simulations demonstrate the proposed LM-RS method can exhibit quite good performance. Particularly, as compared with the conventional NLMS and RLS methods, the proposed LM-RS method achieves smaller steady-state error and lower complexity, as well as similar convergence rate. All these results indicate that the proposed collaborative LM-RS blind equalization method is suitable for the OFDM transmission under the time-varying wireless application environments. Blind equalization normalized least mean square (NLMS) orthogonal frequency division modulation (OFDM) recursive least square (RLS) time-varying channel Electrical engineering. Electronics. Nuclear engineering Yong Mao Huang verfasserin aut Qian Chen verfasserin aut Yuanhua He verfasserin aut Xiubao Sui verfasserin aut In IEEE Access IEEE, 2014 8(2020), Seite 103073-103087 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:8 year:2020 pages:103073-103087 https://doi.org/10.1109/ACCESS.2020.2999387 kostenfrei https://doaj.org/article/b1c952038f61433f8adb7addc371b297 kostenfrei https://ieeexplore.ieee.org/document/9106318/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2020 103073-103087
allfields_unstemmed	10.1109/ACCESS.2020.2999387 doi (DE-627)DOAJ072490063 (DE-599)DOAJb1c952038f61433f8adb7addc371b297 DE-627 ger DE-627 rakwb eng TK1-9971 Li Deng verfasserin aut Collaborative Blind Equalization for Time-Varying OFDM Applications Enabled by Normalized Least Mean and Recursive Square Methodologies 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this work, a collaborative blind equalization method for the orthogonal frequency division multiplexing (OFDM) signals in time-varying channels is presented. Equalizers are eliminated the inter-symbol interference (ISI) in the received signals caused by channel distortions. The conventional adaptive equalization requires sending the training-sequences periodically to synthesize the channel model, which can only provide redundant information, and consequently decrease the channel utilization and complicate the system. To overcome this drawback, the blind equalization methods, which need not send the training-sequences periodically, is developed. However, the conventional blind equalization methods still suffer from various disadvantages. The normalized least mean square (NLMS) method is able to converge rapidly, whereas its equalization error is relatively large. The recursive least square (RLS) method has smaller steady-state error but low convergence rate, demanding massive training sequences. To further enhance the equalization performance of time-varying OFDM systems, which is typically with massive calculation, a collaborative blind equalization is proposed in this work, which is able to effectively combine the characteristics of the conventional NLMS and RLS methods together. The numerical simulations demonstrate the proposed LM-RS method can exhibit quite good performance. Particularly, as compared with the conventional NLMS and RLS methods, the proposed LM-RS method achieves smaller steady-state error and lower complexity, as well as similar convergence rate. All these results indicate that the proposed collaborative LM-RS blind equalization method is suitable for the OFDM transmission under the time-varying wireless application environments. Blind equalization normalized least mean square (NLMS) orthogonal frequency division modulation (OFDM) recursive least square (RLS) time-varying channel Electrical engineering. Electronics. Nuclear engineering Yong Mao Huang verfasserin aut Qian Chen verfasserin aut Yuanhua He verfasserin aut Xiubao Sui verfasserin aut In IEEE Access IEEE, 2014 8(2020), Seite 103073-103087 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:8 year:2020 pages:103073-103087 https://doi.org/10.1109/ACCESS.2020.2999387 kostenfrei https://doaj.org/article/b1c952038f61433f8adb7addc371b297 kostenfrei https://ieeexplore.ieee.org/document/9106318/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2020 103073-103087
allfieldsGer	10.1109/ACCESS.2020.2999387 doi (DE-627)DOAJ072490063 (DE-599)DOAJb1c952038f61433f8adb7addc371b297 DE-627 ger DE-627 rakwb eng TK1-9971 Li Deng verfasserin aut Collaborative Blind Equalization for Time-Varying OFDM Applications Enabled by Normalized Least Mean and Recursive Square Methodologies 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this work, a collaborative blind equalization method for the orthogonal frequency division multiplexing (OFDM) signals in time-varying channels is presented. Equalizers are eliminated the inter-symbol interference (ISI) in the received signals caused by channel distortions. The conventional adaptive equalization requires sending the training-sequences periodically to synthesize the channel model, which can only provide redundant information, and consequently decrease the channel utilization and complicate the system. To overcome this drawback, the blind equalization methods, which need not send the training-sequences periodically, is developed. However, the conventional blind equalization methods still suffer from various disadvantages. The normalized least mean square (NLMS) method is able to converge rapidly, whereas its equalization error is relatively large. The recursive least square (RLS) method has smaller steady-state error but low convergence rate, demanding massive training sequences. To further enhance the equalization performance of time-varying OFDM systems, which is typically with massive calculation, a collaborative blind equalization is proposed in this work, which is able to effectively combine the characteristics of the conventional NLMS and RLS methods together. The numerical simulations demonstrate the proposed LM-RS method can exhibit quite good performance. Particularly, as compared with the conventional NLMS and RLS methods, the proposed LM-RS method achieves smaller steady-state error and lower complexity, as well as similar convergence rate. All these results indicate that the proposed collaborative LM-RS blind equalization method is suitable for the OFDM transmission under the time-varying wireless application environments. Blind equalization normalized least mean square (NLMS) orthogonal frequency division modulation (OFDM) recursive least square (RLS) time-varying channel Electrical engineering. Electronics. Nuclear engineering Yong Mao Huang verfasserin aut Qian Chen verfasserin aut Yuanhua He verfasserin aut Xiubao Sui verfasserin aut In IEEE Access IEEE, 2014 8(2020), Seite 103073-103087 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:8 year:2020 pages:103073-103087 https://doi.org/10.1109/ACCESS.2020.2999387 kostenfrei https://doaj.org/article/b1c952038f61433f8adb7addc371b297 kostenfrei https://ieeexplore.ieee.org/document/9106318/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2020 103073-103087
allfieldsSound	10.1109/ACCESS.2020.2999387 doi (DE-627)DOAJ072490063 (DE-599)DOAJb1c952038f61433f8adb7addc371b297 DE-627 ger DE-627 rakwb eng TK1-9971 Li Deng verfasserin aut Collaborative Blind Equalization for Time-Varying OFDM Applications Enabled by Normalized Least Mean and Recursive Square Methodologies 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this work, a collaborative blind equalization method for the orthogonal frequency division multiplexing (OFDM) signals in time-varying channels is presented. Equalizers are eliminated the inter-symbol interference (ISI) in the received signals caused by channel distortions. The conventional adaptive equalization requires sending the training-sequences periodically to synthesize the channel model, which can only provide redundant information, and consequently decrease the channel utilization and complicate the system. To overcome this drawback, the blind equalization methods, which need not send the training-sequences periodically, is developed. However, the conventional blind equalization methods still suffer from various disadvantages. The normalized least mean square (NLMS) method is able to converge rapidly, whereas its equalization error is relatively large. The recursive least square (RLS) method has smaller steady-state error but low convergence rate, demanding massive training sequences. To further enhance the equalization performance of time-varying OFDM systems, which is typically with massive calculation, a collaborative blind equalization is proposed in this work, which is able to effectively combine the characteristics of the conventional NLMS and RLS methods together. The numerical simulations demonstrate the proposed LM-RS method can exhibit quite good performance. Particularly, as compared with the conventional NLMS and RLS methods, the proposed LM-RS method achieves smaller steady-state error and lower complexity, as well as similar convergence rate. All these results indicate that the proposed collaborative LM-RS blind equalization method is suitable for the OFDM transmission under the time-varying wireless application environments. Blind equalization normalized least mean square (NLMS) orthogonal frequency division modulation (OFDM) recursive least square (RLS) time-varying channel Electrical engineering. Electronics. Nuclear engineering Yong Mao Huang verfasserin aut Qian Chen verfasserin aut Yuanhua He verfasserin aut Xiubao Sui verfasserin aut In IEEE Access IEEE, 2014 8(2020), Seite 103073-103087 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:8 year:2020 pages:103073-103087 https://doi.org/10.1109/ACCESS.2020.2999387 kostenfrei https://doaj.org/article/b1c952038f61433f8adb7addc371b297 kostenfrei https://ieeexplore.ieee.org/document/9106318/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2020 103073-103087
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source	In IEEE Access 8(2020), Seite 103073-103087 volume:8 year:2020 pages:103073-103087
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topic_facet	Blind equalization normalized least mean square (NLMS) orthogonal frequency division modulation (OFDM) recursive least square (RLS) time-varying channel Electrical engineering. Electronics. Nuclear engineering
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callnumber-first	T - Technology
author	Li Deng
spellingShingle	Li Deng misc TK1-9971 misc Blind equalization misc normalized least mean square (NLMS) misc orthogonal frequency division modulation (OFDM) misc recursive least square (RLS) misc time-varying channel misc Electrical engineering. Electronics. Nuclear engineering Collaborative Blind Equalization for Time-Varying OFDM Applications Enabled by Normalized Least Mean and Recursive Square Methodologies
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topic_title	TK1-9971 Collaborative Blind Equalization for Time-Varying OFDM Applications Enabled by Normalized Least Mean and Recursive Square Methodologies Blind equalization normalized least mean square (NLMS) orthogonal frequency division modulation (OFDM) recursive least square (RLS) time-varying channel
topic	misc TK1-9971 misc Blind equalization misc normalized least mean square (NLMS) misc orthogonal frequency division modulation (OFDM) misc recursive least square (RLS) misc time-varying channel misc Electrical engineering. Electronics. Nuclear engineering
topic_unstemmed	misc TK1-9971 misc Blind equalization misc normalized least mean square (NLMS) misc orthogonal frequency division modulation (OFDM) misc recursive least square (RLS) misc time-varying channel misc Electrical engineering. Electronics. Nuclear engineering
topic_browse	misc TK1-9971 misc Blind equalization misc normalized least mean square (NLMS) misc orthogonal frequency division modulation (OFDM) misc recursive least square (RLS) misc time-varying channel misc Electrical engineering. Electronics. Nuclear engineering
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title	Collaborative Blind Equalization for Time-Varying OFDM Applications Enabled by Normalized Least Mean and Recursive Square Methodologies
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title_full	Collaborative Blind Equalization for Time-Varying OFDM Applications Enabled by Normalized Least Mean and Recursive Square Methodologies
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title_sort	collaborative blind equalization for time-varying ofdm applications enabled by normalized least mean and recursive square methodologies
callnumber	TK1-9971
title_auth	Collaborative Blind Equalization for Time-Varying OFDM Applications Enabled by Normalized Least Mean and Recursive Square Methodologies
abstract	In this work, a collaborative blind equalization method for the orthogonal frequency division multiplexing (OFDM) signals in time-varying channels is presented. Equalizers are eliminated the inter-symbol interference (ISI) in the received signals caused by channel distortions. The conventional adaptive equalization requires sending the training-sequences periodically to synthesize the channel model, which can only provide redundant information, and consequently decrease the channel utilization and complicate the system. To overcome this drawback, the blind equalization methods, which need not send the training-sequences periodically, is developed. However, the conventional blind equalization methods still suffer from various disadvantages. The normalized least mean square (NLMS) method is able to converge rapidly, whereas its equalization error is relatively large. The recursive least square (RLS) method has smaller steady-state error but low convergence rate, demanding massive training sequences. To further enhance the equalization performance of time-varying OFDM systems, which is typically with massive calculation, a collaborative blind equalization is proposed in this work, which is able to effectively combine the characteristics of the conventional NLMS and RLS methods together. The numerical simulations demonstrate the proposed LM-RS method can exhibit quite good performance. Particularly, as compared with the conventional NLMS and RLS methods, the proposed LM-RS method achieves smaller steady-state error and lower complexity, as well as similar convergence rate. All these results indicate that the proposed collaborative LM-RS blind equalization method is suitable for the OFDM transmission under the time-varying wireless application environments.
abstractGer	In this work, a collaborative blind equalization method for the orthogonal frequency division multiplexing (OFDM) signals in time-varying channels is presented. Equalizers are eliminated the inter-symbol interference (ISI) in the received signals caused by channel distortions. The conventional adaptive equalization requires sending the training-sequences periodically to synthesize the channel model, which can only provide redundant information, and consequently decrease the channel utilization and complicate the system. To overcome this drawback, the blind equalization methods, which need not send the training-sequences periodically, is developed. However, the conventional blind equalization methods still suffer from various disadvantages. The normalized least mean square (NLMS) method is able to converge rapidly, whereas its equalization error is relatively large. The recursive least square (RLS) method has smaller steady-state error but low convergence rate, demanding massive training sequences. To further enhance the equalization performance of time-varying OFDM systems, which is typically with massive calculation, a collaborative blind equalization is proposed in this work, which is able to effectively combine the characteristics of the conventional NLMS and RLS methods together. The numerical simulations demonstrate the proposed LM-RS method can exhibit quite good performance. Particularly, as compared with the conventional NLMS and RLS methods, the proposed LM-RS method achieves smaller steady-state error and lower complexity, as well as similar convergence rate. All these results indicate that the proposed collaborative LM-RS blind equalization method is suitable for the OFDM transmission under the time-varying wireless application environments.
abstract_unstemmed	In this work, a collaborative blind equalization method for the orthogonal frequency division multiplexing (OFDM) signals in time-varying channels is presented. Equalizers are eliminated the inter-symbol interference (ISI) in the received signals caused by channel distortions. The conventional adaptive equalization requires sending the training-sequences periodically to synthesize the channel model, which can only provide redundant information, and consequently decrease the channel utilization and complicate the system. To overcome this drawback, the blind equalization methods, which need not send the training-sequences periodically, is developed. However, the conventional blind equalization methods still suffer from various disadvantages. The normalized least mean square (NLMS) method is able to converge rapidly, whereas its equalization error is relatively large. The recursive least square (RLS) method has smaller steady-state error but low convergence rate, demanding massive training sequences. To further enhance the equalization performance of time-varying OFDM systems, which is typically with massive calculation, a collaborative blind equalization is proposed in this work, which is able to effectively combine the characteristics of the conventional NLMS and RLS methods together. The numerical simulations demonstrate the proposed LM-RS method can exhibit quite good performance. Particularly, as compared with the conventional NLMS and RLS methods, the proposed LM-RS method achieves smaller steady-state error and lower complexity, as well as similar convergence rate. All these results indicate that the proposed collaborative LM-RS blind equalization method is suitable for the OFDM transmission under the time-varying wireless application environments.
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title_short	Collaborative Blind Equalization for Time-Varying OFDM Applications Enabled by Normalized Least Mean and Recursive Square Methodologies
url	https://doi.org/10.1109/ACCESS.2020.2999387 https://doaj.org/article/b1c952038f61433f8adb7addc371b297 https://ieeexplore.ieee.org/document/9106318/ https://doaj.org/toc/2169-3536
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author2	Yong Mao Huang Qian Chen Yuanhua He Xiubao Sui
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doi_str	10.1109/ACCESS.2020.2999387
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up_date	2024-07-04T01:16:29.036Z
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Collaborative Blind Equalization for Time-Varying OFDM Applications Enabled by Normalized Least Mean and Recursive Square Methodologies

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