In this paper presents a compact MIMO array platform to operate at 2.6GHz Long Term Evolution (LTE) band for wireless communication systems. The array consists of four compact patch antennas on a dielectric substrate with total dimensions of 125x62.5x1.27mm 3 . Modifications of the ground plane along with systematic placement and orientation of each antenna on top of the substrate plays a key role to reduce the mutual coupling which normally degrades the MIMO arrays performance. The modifications of the ground plane, placement, and orientation of each antenna on the array was done based on the insights provided by the theory of CM. The CM-based approach considers the chassis as a fundamental structure, and by examining the set of characteristic currents in the PCB/dielectric substrate, allows the designer to define the position of each antenna of the MIMO array.The performance of this MIMO array has been evaluated through simulations and measurements of the scattering parameters and radiation patterns. The isolation obtained is over 25dB between all the antennas, and the maximum achieved gain of a single antenna is 3.14dBi with other antennas terminated with appropriate loads (50-ohms).One metric that provides very important information about the performance of the array for MIMO systems is the correlation. This enveloped correlation coefficient between signals received by the antennas of the array can be computed through the S-parameters with the assumption that the incoming signals are uniformly distributed, i.e. the direction of arrival of each multipath component has equal probability. The results of the correlation coefficients calculated through the measured S-parameters are much less than 0.000015 at 2.6Ghz; these very low values can potentially enable the generation of more independent and parallel subchannels producing high performance wireless communication systems with MIMO arrays..
The sum of lognormal variables has been a topic of interest in several fields of research such as engineering, biology and finance, among others. For example, in the field of telecommunications, the aggregate interference of radio frequency signals is modeled as a sum of lognormal variables. To date, there is no closed expression for the probability distribution function (PDF) of this sum. Several authors have proposed approximations for this PDF, with which they calculate the mean and variance. However, each method has limitations in its range of parameters for mean, variance and number of random variables to be added. In other cases, long approximations as power series are used, which makes the analytical treatment impractical and reduces the computational performance of numerical operations. This paper shows an alternative method for calculating the mean and variance of the sum of lognormal random variables from a computational performance approach. Our method has been evaluated extensively by Monte Carlo simulations. As a result, this method is computationally efficient and yields a low approximation error computation for a wide range of mean values, variances and number of random variables.
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