Non-data-aided SNR estimation for QPSK modulation in AWGN channel

Abstract

Signal-to-noise ratio (SNR) estimation is an important parameter that is required in any receiver or communication systems. It can be computed either by a pilot signal data-aided approach in which the transmitted signal would be known to the receiver, or without any knowledge of the transmitted signal, which is a non-data-aided (NDA) estimation approach. In this paper, a NDA SNR estimation algorithm for QPSK signal is proposed. The proposed algorithm modifies the existing Signalto-Variation Ratio (SVR) SNR estimation algorithm in the aim to reduce its bias and mean square error in case of negative SNR values at low number of samples of it. We first present the existing SVR algorithm and then show the mathematical derivation of the new NDA algorithm. In addition, we compare our algorithm to two baselines estimation methods, namely the M2M4 and SVR algorithms, using different test cases. Those test cases include low SNR values, extremely high SNR values and low number of samples. Results showed that our algorithm had a better performance compared to second and fourth moment estimation (M2M4) and original SVR algorithms in terms of normalized mean square error (NMSE) and bias estimation while keeping almost the same complexity as the original algorithms.

Signal-Power-Based Combination Weight Rule for Distributed Blind Equalization in WSN Model

“…However, the noise variance is difficult to know in most applications. Although the noise variance may be obtained by SNR estimation [31], the information about the noise variance is difficult to obtain when the signal power is lower than the noise power [31]. In addition, the SNR estimation algorithms are based on some assumptions, for example, those signal boundaries are known and the background noise is stationary [32].…”

Instant SNR Estimation on Digital Symbols

“…The SNR estimation methods can be classified into two: Data aided and Non-data aided estimation (Abeida, 2010;Salman, Badawy, Elfouly, Khattab, & Mohamed, 2014). The first one generally requires the transmission of a data that is known to receiver.…”

Signal-to-noise ratio estimation for M-QAM signals in η−μand κ−μfading channels

“…*Correspondence: waslon@ieee.org 3 Department of Electrical Engineering, Federal University of Paraíba, João Pessoa, Brazil Full list of author information is available at the end of the article Usually, the choice of the estimation technique depends on the complexity of the mathematical model of the signal in the receiver [4,7]. Depending on that complexity, one can use a method belonging to the class of estimators that use a training sequence (that is, a data-aided method (DA)) [8,9], or a method belonging to the class of estimators that do not have a priori knowledge of the transmitted sequence of symbols (that is, a non-data-aided method (NDA)) [10].…”