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This paper proposes a novel convolutional neural network (CNN) based joint classification method to characterize the signal-to-noise power ratio (SNR) and Doppler shift using spectrogram images, in order to enable efficient adaptive modulation and coding (AMC) designs. It is necessary to maintain high communication performances even in stringent environments where transceivers move at high speed due to the diversification of wireless applications. To optimize the transmission rate in such dynamic environments, AMC scheme is known to be effective. AMC is generally designed based on feedback information (FBI) such as the SNR and Doppler shift acquired on the receiving side. Here, the challenge is an increase in calculation burden, processing delay and estimation accuracy of the FBI. We focused on the spectrogram which is composed of power values in the time and frequency domains. Its two-dimensional fluctuation represents the Doppler shift as well as noise values. In the proposed method, such key information for AMC can be simultaneously extracted from a single spectrogram via a trained CNN. Therefore it is expected to contribute to reducing the computational burden and speeding up the signal processing. Simulation results are presented to demonstrate that the proposed method achieves better performance than traditional methods. [ABSTRACT FROM AUTHOR]

In this paper, blind channel order and signal to noise ratio (SNR) estimators based on time-varying autocorrelation function (TVAF) are proposed for orthogonal frequency division multiplexing systems. The TVAF of the received signal reveals clearly the inherent periodicity introduced by cyclic prefix (CP) and carries rich information of channel and additive noise. To investigate the relationships among the TVAF, channel order, and SNR, a newly close-form expression of the TVAF of the received signal is derived. Not only the CP-induced TVAF components but the channel-spread TVAF elements are employed to derive the proposed estimators. Specifically, the two kinds of the TVAF components are separate from the components superimposed by the additive noise, which enables optimal estimation performance even for the low SNR regime. Numerical results show that, in contrast with the alternative methods, the proposed estimators achieve significant performance gain in the low SNR regime, while hold competitive performance in the high SNR regime.

In the channel-varying environment, it is very important to estimate the signal to noise ratio (SNR) of received signal and to transmit the signal effectively for the modern communication system. The performance of existing non-data-aided SNR estimation methods are substantially degraded for high level modulation scheme such as M-ary amplitude and phase shift keying or quadrature amplitude modulation. In this paper, we propose a SNR estimation method which uses zero point auto-correlation of received signal per block and auto/cross-correlation of decision feedback signal in orthogonal frequency division multiplexing (OFDM) system. Proposed method can be studied into two types; Type 1 can estimate SNR by zero point auto-correlation of decision feedback signal based on the second moment property. Type 2 uses both zero point auto-correlation and cross-correlation based on the fourth moment property. In block-by-block reception of OFDM system, these two SNR estimation methods can be possible for the practical implementation due to correlation based the estimation method and they show more stable estimation performance than the previous SNR estimation methods. Also, we mathematically derive the SNR estimation expression according to computational difference of auto/cross-correlation. Finally, Monte Carlo simulations are used to verify the proposed method. [ABSTRACT FROM AUTHOR]

Abstract: SNR is a crucial parameter for OFDM system and the assistant technology thereof such as Turbo coding, channel equalization. In this paper, we propose an improved SNR estimator which can be applied for the pilot structure in 3GPP standard. The modified second order moments of the pilot points after FFT are used to estimate noise variance in OFDM packets. The channel frequency responses of four subcarriers from adjacent two pilot points in distinct symbols could be used to inhibit the channel fading. Simulation results show that the proposed algorithm is robust to frequency selectivity and time selectivity in wireless channels, and its performance is considerably improved compared with the available methods. [Copyright &y& Elsevier]

Abstract: The purpose of this paper is to propose two fast timing synchronization methods of OFDM System which has two preamble symbols, the two preamble symbols are used for SNR estimation for OFDM systems. The synchronization techniques are examined in Multipath fading environments for comparison. The results of the performance comparison are presented in terms of mean obtained by simulations. [Copyright &y& Elsevier]

Abstract: Blind noise variance and SNR estimators based on information theoretic criteria for orthogonal frequency division multiplexing (OFDM) systems are proposed in this paper. By using the redundancy induced by the cyclic-prefix, the unknown channel order is estimated via minimum length description (MDL) or Akaike information criterion (AIC), and the noise variance and SNR can be obtained subsequently. The proposed methods do not require any pilot symbols and therefore improve the spectrum efficiency. Simulation results are presented to highlight the benefit of the proposed algorithms compared with the other existing blind methods. [Copyright &y& Elsevier]

This letter deals with the problem of non data aided (NDA) signal to noise ratio (SNR) estimation of OFDM signals transmitted through unknown multipath fading channel. Most of existing OFDM SNR estimators are based on the knowledge of pilot sequences which is not applicable in some contexts such as cognitive radio for instance. We show that it is possible to take advantage of the periodic redundancy induced by the cyclic prefix to get an accurate NDA SNR estimator. Numerical simulations highlight the benefit of the proposed method compared with the state of the art. [ABSTRACT FROM PUBLISHER]