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Abstract-In this paper, we present an efficient hybrid spatialspectral formulation of the method of moment (MoM) in conjunction with the Mixed-Potential Integral Equation (MPIE) for planar circuit analysis. This method is based on the decomposition of the Green's functions in two parts: quasi-static in the near field region and the dynamic contribution in the far field region. Using this decomposition of Green's functions, the method of moment matrix entries can be reduced to a sum of two integrals. The first one is expressed in the spatial field and corresponds to the quasi-static contribution. It is analytically evaluated after a development in Taylor series of the exponential terms in the function to be integrated. The integrals expressed in the spectral field and corresponding to the dynamic part have the advantage of being calculated on a finite range and this is independent of the choice of the basis and test functions. The integrals expressed in the spectral field are performed by using numerical integration. It is also demonstrated that this hybrid method has accelerated the matrix fill in time by using a Fast Fourier Transform (FFT) algorithm. In order to validate the proposed method, numerical results are presented.

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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.

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