Robust massive MIMO Equilization for mmWave systems with low resolution ADCs

Leveraging the available millimeter wave spectrum will be important for 5G. In this work, we investigate the performance of digital beamforming with low resolution ADCs based on link level simulations including channel estimation, MIMO equalization and channel decoding. We consider the recently agreed 3GPP NR type 1 OFDM reference signals. The comparison shows sequential DCD outperforms MMSE-based MIMO equalization both in terms of detection performance and complexity. We also show that the DCD based algorithm is more robust to channel estimation errors. In contrast to the common believe we also show that the complexity of MMSE equalization for a massive MIMO system is not dominated by the matrix inversion but by the computation of the Gram matrix.Comment: submitted to WCNC 2018 Workshop

FEEDBACK EQUALIZER FOR VEHICULAR CHANNEL

In this fast moving world, the number of fatal accidents is increasing day by day and this leads to the requirement of the availability of the traffic condition and road conditions related data to the users. Therefore, to support Vehicle-to-vehicle (V2V) communication in high speed mobility condition, it is required to have reliable and secure of communication. Here, the performance of multiple input and multiple output (MIMO) system as a combination of nonlinear decision feedback receiver (DFE) have been investigated in V2V channel. In this paper, through the simulation, the results are presented to show the effect of the channel correlation coefficient and Doppler shift (Fd) (because of the relative velocity of the vehicle) over the performance of the MIMO system. As a counter measure of those problems non-linear receivers have been formulated and analyzed

Robust and Reliable Modulation Classification for MIMO Systems

Abstract: This paper develops a feature-based Automatic Modulation Classification (AMC) algorithm for spatially multiplexed Multiple-Input Multiple-Output (MIMO) systems. The proposed algorithm employs two Higher Order Cumulants (HOCs) of the estimated transmit signal streams as discriminating features, and a multiclass Support Vector Machine (SVM) as a classification system. A multi-classifier classification system is introduced to improve the robustness of the decision made by the classifier at each estimated transmit signal stream. Furthermore, an optimal decision fusion scheme using a Maximum-Likelihood (ML) criterion is also introduced to improve the accuracy and reliability of the final classification decision made in the fusion center. The proposed algorithm shows good performance under different operating conditions, over an acceptable range of SNR, without any prior information about the channel state

Sum-capacity optimization of MU-MIMO systems for linear and rectangular arrays at the base station

Orientador: Gustavo FraidenraichDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de ComputaçãoResumo: O objetivo do presente trabalho de mestrado é investigar o impacto do uso de antenas não-uniformemente espaçadas, em arranjos lineares e retangulares, e apresentar a influência da correlação entre as antenas na capacidade do sistema MU-MIMO (Multiuser Multiple-Input Multiple-Output). Inicialmente, é proposto um problema de otimização buscando encontrar a máxima capacidade soma de canal para arranjos não-uniformes. Apesar de ótima, esta solução não apresenta forma analítica. Como alternativa ao modelo analítico, é proposto um arranjo, para geometrias linear e retangular, não-uniforme baseado em progressão aritmética, chamado PA. Na sequência, os arranjos ótimo, proposto e uniforme são estudados estando sujeitos aos efeitos da correlação entre as antenas. Finalmente, a mesma analise é estendida para a utilização do Maximum Ratio Combining (MRC), Zero-Forcing (ZF) e Minimum Mean Square Error (MMSE)Abstract: The aim of this master thesis is to present an investigation on the impact of the use of non-uniformly spaced antennas, in linear and rectangular arrays, and also to present the influence of the correlation between the antenna elements in the MU-MIMO (multiuser multiple-input-multiple-output) capacity. Initially, we propose an optimization problem to find the maximum capacity for non-uniformly spaced arrays. Although optimal, this solution is numerical and does not present an analytical form. As an alternative analytical method, we derive a non-uniformly spaced array, for linear and rectangular geometries, based on the arithmetic progression series. Subsequently, we investigate the optimal, our proposed PA and uniform antenna arrays subject to the correlation between the elements. Finally, we extend the same investigations using the Maximum Ratio Combining (MRC), Zero-Forcing (ZF) and Minimum Mean Square Error (MMSE) receiversMestradoTelecomunicações e TelemáticaMestre em Engenharia Elétrica154999/2016-4CNP