In this paper, we propose a new method to simultaneously estimate the maximum Doppler Spread (DS), the mean Angle of Arrival (AoA) and the Angular Spread (AS). To this end, the derivatives of the cross-correlation functions (DCCF) of the received signal at a Uniform Linear Array (ULA) are exploited. The Rayleigh channel model where the received signal AoAs follow a Gaussian angular distribution is considered. Simulation results show that, the proposed approach offers better accuracy for maximum DS than the algorithm developed in [1]. For the mean AoA and AS estimation, our approach presents NRMSEs close to the one developed in [2].
In this paper, the authors propose a new method to simultaneously estimate the mean angle of arrival (AoA), the angular spread (AS) and the maximum Doppler spread (DS). They exploit the multiple-input multiple-output (MIMO) Rayleigh channel with uniform linear arrays at both the transmitter and the receiver. They also consider the Gaussian and the Laplacian angular distributions for the incoming AoAs. The proposed method uses the first and the second derivatives of the received signals cross-correlation functions. They take as benchmarks two estimators from the literature for the three parameters estimates. The spread root multiple signal classification (MUSIC) (SRM) estimator is used for the mean AoA and the AS parameters, whereas the auto-correlation function (ACF)-based approach is considered for the maximum DS estimates. These methods were developed for single-input multiple-output and singleinput single-output systems. In this paper, the authors extend these algorithms to a MIMO configuration. Simulation results show that their algorithm outperforms the SRM one for the mean AoA and the AS estimation. For the maximum DS estimation, their approach offers lower error rate than the ACF-based one when the AS and the mean AoA are small. For higher values of the couple AS and mean AoA, their algorithm presents similar results.
In this paper, we propose a new low-complexity joint estimator of the mean angle of arrival (AoA), the angular spread (AS), and the maximum Doppler spread (DS) for single-input multiple-output (SIMO) wireless channel configurations in a macrocell environment. The non-line-of-sight (NLOS) case is considered. The space-time correlation matrix is used to jointly estimate the three parameters. Closed-form expressions are developed for the desired parameters using the modules and the phases of the cross-correlation coefficients. Simulation results show that our approach offers a better tradeoff between computational complexity and accuracy than the most recent estimators in the literature.
In this paper, three different nominal Angle of Arrival (AoA) and Angular Spread (AS) estimators are compared. A single source transmitter through a Rayleigh channel scenario is considered. First, the Maximum Likelihood (ML) estimator is studied. Then, low-complexity estimators wich are the Spread Root-MUSIC and the two-stage approach, are presented. Simulation results show that the ML offers lower error estimation while the other estimators present a good compromise between computational complexity and estimation accuracy.
In this work, we develop a new method for the maximum Doppler Spread (DS), the Angular Spread (AS) and the mean Angle of Arrival (AoA) estimation in a Rayleigh channel with a Single Input Multiple Output (SIMO) system using an Uniform Linear Array (ULA) at the receiver. We also consider a macro-cell environment. In this paper, the cross-correlation matrix is defined for the Laplacian angular distribution and their derivatives are used to estimate the three parameters. Simulation results show that, our proposed algorithm outperforms the Auto-Correlation Function (ACF) based approach developed in [1] for the maximum DS estimation. For the mean AoA and the AS estimation, our approach offers lower Root Mean Square Error (RMSE) than the Spread Root MUSIC (SRM) estimator [2].
In this paper, three different low-complexity maximum Doppler Spread (DS) estimators are compared. A single source transmitter through a Rayleigh channel scenario is considered. The first studied method is based on velocity estimation and correlation properties of narrow-band mobile communication channels. The second low-complexity considered approach is the robust Doppler Spread estimation in the presence of residual carrier frequency offset which exploits the covariance matrix of the received signal. The third one uses reduced interference timefrequency distribution of the received signals. Simulation results shows that the second approach offers lower estimation error with a good compromise between computational complexity and estimation accuracy.
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