Signal-to-noise ratio estimation algorithm for advanced DVB-RCS systems

Ijaz, A, Awoseyila, AB and Evans, BG (2012) Signal-to-noise ratio estimation algorithm for advanced DVB-RCS systems IEEE Transactions on Broadcasting, 58 (4). pp. 603-608.

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Abstract

This paper presents a signal-to-noise ratio (SNR) estimation algorithm for advanced Digital Video Broadcasting - Return Channel via Satellite (DVB-RCS) systems using adaptive coding and modulation (ACM) in the reverse link of broadband satellite systems. Due to the absence of a repetitive pilot symbol structure, SNR estimation has to be performed using the fixed symbol preamble data. Moreover, sporadic nature of data traffic on the return link causes variation in interference level from slot to slot and, therefore, the estimation has to be done within one traffic slot duration. Hence, it becomes necessary to use a combination of data-aided (DA) and decision-directed (DD) algorithms so as to make use of traffic data. A non-data-aided (NDA) estimator that was previously proposed by the authors for binary phase shift keying (BPSK) and QPSK schemes is extended to 8-PSK in a decision directed manner. This estimator shows improved performance over existing estimators. The inherent bias of DD approach at low values of SNR is reduced by using a hybrid approach, i.e. using the proposed estimator at moderate/high values of SNR and the moments-based estimator (M2M4) at low values of SNR. Overall improved performance of the proposed hybrid estimator, in terms of accuracy and complexity, makes it an attractive choice for implementing ACM in advanced DVB-RCS systems.

Item Type:	Article
Divisions :	Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Communication Systems Research
Authors :	Name Email ORCID Ijaz, A Awoseyila, AB Evans, BG
Date :	1 December 2012
Identification Number :	10.1109/TBC.2012.2218074
Additional Information :	© 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Depositing User :	Symplectic Elements
Date Deposited :	18 Dec 2012 09:58
Last Modified :	31 Oct 2017 14:53
URI:	http://epubs.surrey.ac.uk/id/eprint/735660

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