Semi-blind channel estimation based on Modified CMA and unitary scrambling for massive MIMO systems

Pilot contamination is one of the main impairments in multi-cell massive Multiple-Input Multiple-Output (MIMO) systems. In order to improve the channel estimation in this context, we propose to use a semi-blind channel estimator based on the constant modulus algorithm (CMA). We consider an enhanced version of the CMA namely the Modified CMA (MCMA) which modifies the cost function of the CMA algorithm to the sum of cost functions for real and imaginary parts. Due to pilot contamination, the channel estimator may estimate the channel of a contaminating user instead of that of the user of interest (the user for which the Base Station wants to estimate the channel and then the data). To avoid this, we propose to scramble the users sequences before transmission. We consider different methods to perform unitary scrambling based on rotating the transmitted symbols (one Dimensional (1-D) scrambling) and using unitary matrices (two-Dimensional (2-D) scrambling). At the base station, the received sequence of the user of interest is descrambled leading to a better convergence of the channel estimator. We also consider the case where the Automatic Repeat reQuest (ARQ) protocol is used. In this case, using scrambling leads to a significant gain in terms of BLock Error Rate (BLER) due to the change of the contaminating users data from one transmission to another induced by scrambling.

Saturn´s Stratospheric Hazes From HST Ultraviolet Imaging

<p>We present a study on Saturn's stratospheric hazes using archived images from the Hubble Space Telescope Advanced Camera for Surveys. These observations were taken from 2005 to 2014, including the Great Storm during the years 2010 and 2011. For our research we used ultraviolet images from the Solar Blind Channel camera equipped with the F115LP and F125LP filters. At these wavelengths, the reflected spectrum is fundamentally Rayleigh-scattered, with substantial contributions from hydrocarbon absorptions and additional scattering by the aerosols in the hazes above the tropopause. The goal of this work is to analyze temporal and latitudinal changes in the characteristics of the stratospheric haze, gases and particles, analyzing the absolute reflectivity and its limb darkening. Such behavior can be reproduced using the empirical Minnaert's law. This provides nadir-viewing reflectivity and limb darkening coefficient as a function of latitude and time. This is a first approach that helps to qualitatively identify the changes occurring in the aerosol layer during this period of time, which include the massive Great White Spot of 2010. In order to quantify such aerosol changes, we use the radiative transfer code and retrieval suite NEMESIS (Non-Linear Optimal Estimator for Multivariat Spectral AnalySIS) to reproduce the observed reflectivity.  Here we will focus on the detected variations of the vertical distribution of the stratospheric particles, their integrated optical thickness and size distribution and will correlate them with the seasonal changes taken place in the atmosphere of the planet.</p>