Ramoni O. Adeogun

Parametric Channel Prediction for Narrowband Mobile MIMO Systems Using Spatio-Temporal Correlation Analysis

In this paper, we propose an ESPRIT-based parametric prediction scheme for narrowband MIMO systems that fully exploits both temporal and spatial correlations in realistic MIMO channels. The proposed predictor uses a vector transmit spatial signature model and two-dimensional ESPRIT for the estimation of the channel parameters. The proposed scheme outperforms existing algorithms and is well suited to both two dimensional azimuth only and three dimensional MIMO spatial channel models.

Novel algorithm for prediction of wideband mobile MIMO wireless channels

We investigate the prediction of wideband MIMO spatial channels. We propose a two-stage long range parametric prediction scheme that exploits the temporal, spatial and frequency correlations in a realistic cluster based fading channel. The proposed scheme utilizes the frequency correlation in an ESPRIT-like approach to estimate the cluster delays and scattering coefficients. The spatial and temporal correlations are then used to jointly estimate the angles of arrival, angles of departure and Doppler shifts via a 3D ESPRIT algorithm. Simulation results using the standardized 3GPP/WINNER II spatial channel model show that the proposed algorithm offers improved prediction performance over previous methods and can achieve longer prediction range.

Extrapolation of MIMO Mobile-to-Mobile Wireless Channels Using Parametric-Model-Based Prediction

This paper investigates the prediction of multiple-input-multiple-output (MIMO) narrow-band multipath fading channels for mobile-to-mobile (M-to-M) wireless communication systems. Using a statistical model for M-to-M communication in urban and suburban environments, we derive a parameterized double directional model and utilize a multidimensional extension of the ESPRIT algorithm to jointly estimate the angles of departure (AoD), angles of arrival (AoA), and effective Doppler frequencies. A simple method is also proposed for mobile velocity estimation. The parameter estimates are then used to forecast the M-to-M channel. The bound on the prediction error is derived using a vector formulation of the Cramer-Rao lower bound (CRLB). Simulations are used to evaluate the performance of the prediction scheme and to compare it to the derived error bound.

Parametric Channel Prediction for Narrowband MIMO Systems Using Polarized Antenna Arrays

A novel prediction scheme for polarized narrowband MIMO channels is proposed in this paper. The prediction scheme is based on estimation of the parameters of a double directional polarized propagation model. The proposed algorithm transforms the channel impulse response matrix in such a manner that a multidimensional extension of the ESPRIT algorithm can be utilized to jointly estimate the angles of arrival, angles of departure, Doppler shifts and complex polarimetric weights of the dominant multipath components. Simulation results show that the proposed algorithm outperforms repeated application of one dimensional ESPRIT based approach with similar computational complexity.

Long range parametric channel prediction for narrowband MIMO systems with joint parameter estimation

In this paper, we propose a novel long range prediction scheme for narrowband MIMO systems using realistic spatial channel model. The algorithm exploits both the temporal and spatial structure of the MIMO channel to jointly estimate the multipath parameters via a subspace based three dimensional ESPRIT approach. We propose simple transformations to convert the channel impulse response into a space-time manifold matrix exhibiting translational invariance in three dimensions. Simulation results show that the proposed prediction scheme outperforms existing algorithms and can achieve prediction range of several wavelengths.

Asymptotic Error Bounds on Prediction of Narrowband MIMO Wireless Channels

In this letter, we derive simple expressions for the lower bound on the prediction error variance for narrowband MIMO channel with uniform linear array at both ends of the link. The derived bounds show the relationship between the achievable prediction performance and prediction algorithm design parameters, thereby providing useful insights into the development of fading channel prediction algorithms.

A Robust MUSIC based Scheme for Interference Location in Satellite Systems with Multibeam Antennas

In this paper, we investigate methods for interference location in satellite communication system using satellite multi-beam antenna with subspace based schemes. A novel MUSIC based approach is proposed for estimating the direction of arrival of the interfering sources. The proposed method provides super resolution and asymptotic maximum likelihood estimates of the direction of arrivals even at low SNR values. Simulations were performed using typical satellite multi-beam antenna configurations and results show that the proposed scheme can effectively estimates the direction of arrival in the azimuth and elevation spectra. Compared to the support vector regression method, the proposed approach offer improved estimation accuracy at low SNR values.

Cluster Based Channel Model and Performance Analysis for MIMO Satellite Formation Flying Communication Systems

Satellite formation flying is an essential capability for many space missions that allow several closely spaced smaller satellites to be deployed. Depending on mission requirements, the ground receive station may carry several antennas and receive signal from each of the satellites in order to increase spectral efficiency and Quality of Service (QoS). In this paper, we propose an improved cluster based distributed MIMO channel model based on MIMO models for terrestrial communications in the WINNER/3GPP project for satellite formation flying systems. Monte Carlo simulations were also performed to evaluate the performance of formation flying satellite systems with different configurations using the proposed spatial channel model and comparisons were made with the single satellite-single receive station system using capacity ratio and capacity difference as metrics. Our results show the effects of several factors such as type of formation, number of satellites, number of receive antennas, and SNR on capacity for the single satellite and multi-satellite systems.