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Performance of an echo canceller and channel estimator for on-channel repeaters in DVB-T/H networks

Performance of an echo canceller and channel estimator for on-channel repeaters in DVB-T/H networks

Nasr, Karim Medhat ORCID: 0000-0002-8604-6274, Cosmas, John P., Bard, Maurice and Gledhill, Jeff (2007) Performance of an echo canceller and channel estimator for on-channel repeaters in DVB-T/H networks. IEEE Transactions on Broadcasting, 53 (3). pp. 609-618. ISSN 0018-9316 (doi:https://doi.org/10.1109/TBC.2007.903612)

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Abstract

This paper investigates the design and performance of an FIR echo canceller for on-channel repeaters in DVB-T/H network within the framework of the PLUTO project. The possible approaches for echo cancellation are briefly reviewed and the main guidelines for the design of such systems are presented. The main system parameters are discussed. The performance of an FIR echo canceller based on an open loop feedforward approach for channel estimation is tested for different radio channel conditions and for different number of taps of the FIR filter. It is shown that a minimum number of taps is recommended to achieve a certain mean rejection ratio or isolation depending on the type of channel. The expected degradation in performance due to the use of fixed point rather than floating point arithmetic in hardware implementation is presented for different number of bits. Channel estimation based on training sequences is investigated. The performance of maximum length sequences and constant amplitude zero autocorrelation (CAZAC) sequences is compared for different channels. Recommendations are given for training sequence type, length and level for DVB-T/H on-channel repeater deployment.

Item Type: Article
Uncontrolled Keywords: training sequences, constant amplitude zero autocorrelation, maximum length sequences, FIR filter, FIR echo canceller, PLUTO project, DVB-T/H networks, on channel repeaters, channel estimator
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Faculty / Department / Research Group: Faculty of Engineering & Science
Faculty of Engineering & Science > Department of Engineering Science
Last Modified: 02 Oct 2019 12:35
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
URI: http://gala.gre.ac.uk/id/eprint/25340

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