Petrella, Angelo (2009) Synchronization Algorithms for FBMC Systems. [Tesi di dottorato] (Inedito)

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Tipologia del documento: Tesi di dottorato
Lingua: English
Titolo: Synchronization Algorithms for FBMC Systems
Autori:
AutoreEmail
Petrella, Angeloangelopetrella83@hotmail.com
Data: 2009
Numero di pagine: 201
Istituzione: Università degli Studi di Napoli Federico II
Dipartimento: Ingegneria biomedica, elettronica e delle comunicazioni
Scuola di dottorato: Ingegneria dell'informazione
Dottorato: Ingegneria elettronica e delle telecomunicazioni
Ciclo di dottorato: 22
Coordinatore del Corso di dottorato:
nomeemail
Rinaldi, Niccolònirinarld@unina.it
Tutor:
nomeemail
Tanda, Mariotanda@unina.it
Data: 2009
Numero di pagine: 201
Parole chiave: FBMC, Synchronization, FMT, OFDM/OQAM, Blind, Data-Aided, Symbol Timing, Carrier Frequency Offset
Settori scientifico-disciplinari del MIUR: Area 09 - Ingegneria industriale e dell'informazione > ING-INF/03 - Telecomunicazioni
Depositato il: 24 Mag 2010 10:36
Ultima modifica: 30 Apr 2014 19:39
URI: http://www.fedoa.unina.it/id/eprint/3906
DOI: 10.6092/UNINA/FEDOA/3906

Abstract

Filter bank multicarrier (FBMC) systems, such as FMT and OFDM/OQAM systems, can provide reduced sensitivity to narrowband interference, high flexibility to allocate group of subchannels to different users and a high spectral containment. On the other hand, as all the multicarrier modulation schemes, one of their major drawbacks is their sensitivity to CFO and symbol timing errors. In this thesis the problem of CFO and symbol timing synchronization is examined and new data-aided and blind estimation techniques are proposed. Specifically, it is presented a new joint symbol timing and CFO synchronization algorithm based on the LS approach. Moreover, the joint ML phase offset, CFO and symbol timing estimator for a multiple access OFDM/OQAM system is considered. It is also proposed a closed-form CFO estimator based on the best linear unbiased estimation principle for FMT systems. Blind CFO estimators based on the ML principle for low SNR are also considered and, moreover, a closed-form CFO synchronization algorithm based on the LS method is derived. Finally, it is also proposed, under the assumption of low SNR, the joint ML symbol timing and phase offset estimator.

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