Improving the Correlation Lower Bound for Simultaneous Orthogonal Matching Pursuit

The simultaneous orthogonal matching pursuit (SOMP) algorithm aims to find the joint support of a set of sparse signals acquired under a multiple measurement vector model. Critically, the analysis of SOMP depends on the maximal inner product of any atom of a suitable dictionary and the current signal residual, which is formed by the subtraction of previously selected atoms. This inner product, or correlation, is a key metric to determine the best atom to pick at each iteration. This letter provides, for each iteration of SOMP, a novel lower bound of the aforementioned metric for the atoms belonging to the correct and common joint support of the multiple signals. Although the bound is obtained for the noiseless case, its main purpose is to intervene in noisy analyses of SOMP. Finally, it is shown for specific signal patterns that the proposed bound outperforms state-of-the-art results for SOMP and orthogonal matching pursuit (OMP) as a special case

A Polarized Clustered Channel Model for Indoor Multiantenna Systems at 3.6 GHz

Multiple-input-multiple-output (MIMO) technologies allow high data rates to be obtained, but they suffer from interantenna correlation caused by the limits in interantenna spacing. Polarized MIMO systems resolve this problem by using colocated perpendicularly polarized antennas that have low interantenna correlation. In this paper, a polarized single-directional channel model for 2 x N MIMO systems at 3.6 GHz in an indoor environment is presented. The wireless channel is modeled as a sum of clusters, where each cluster has specular and diffuse components. The polarization of the specular component of the clusters is included by considering a per-path polarization. The diffuse component of the clusters is modeled with a Fisher-Bingham (FB5) spectrum in the azimuth-coelevation domain and with an exponential power delay profile. Polarization is analyzed by introducing the cross-polar discrimination of the exponential power delay profile parameters. All of the parameters in the model are extracted from an experimental measurement campaign performed in an indoor environment at 3.6 GHz. Individual paths are extracted from the measurements with the space-alternating generalized expectation-maximization (SAGE) algorithm. These paths are grouped in clusters within the azimuth of arrival-elevation of arrival-delay domains at the receiver side using automatic clustering algorithms. The specular component properties of the clusters are then determined. Finally, the diffuse components of the clusters are investigated and parameterized by applying a beam-forming algorithm on the diffuse part of the impulse response

Multipolarized MIMO Channel Characteristics: Analytical Study and Experimental Results

MIMO technologies enable high communication data rates, but suffer from the large antenna spacing that is required to achieve sufficiently low inter-antenna correlation. Cross-polarized antenna systems resolve this problem by using perpendicular antennas. Correlation is reduced while keeping antennas co-located. Inter-antenna correlation and cross-polar discrimination (XPD) are two fundamental parameters of these polarized antenna systems. This paper proposes an analytical channel model, from which closed-form solutions for the correlation coefficient and the XPD are deduced. The environment is supposed to have a truncated Laplacian power azimuth spectrum that is widely used in standardization bodies. The receiving di- or tri-pole antenna can have random orientation. The correlation and the XPD show to be highly sensitive to receiver orientation, azimuth spread and environment depolarization behavior. Measurements have been conducted at 3.5 GHz to validate the solution obtained. Good agreement is achieved when comparing theoretical curves and experimental results for different receiver orientations, both for the correlation coefficient and the XPD