scholarly journals Novel Methods for Approximate Maximum Likelihood Estimation of Multiple Superimposed Undamped Tones and Their Application to Radar Systems

2021 ◽  
Author(s):  
Pasquale Di Viesti ◽  
ALESSANDRO DAVOLI ◽  
Giorgio Guerzoni ◽  
Giorgio Matteo Vitetta
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Multiple Input Multiple Output ◽  
Likelihood Estimation ◽  
Approximate Maximum Likelihood ◽  
Radar Systems ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Novel Methods

<div>In this manuscript, novel methods for the detection of multiple superimposed tones in noise and the estimation of their parameters are derived, and their application to colocated multiple-input multiple-output radar systems is investigated.</div>

scholarly journals Novel Methods for Approximate Maximum Likelihood Estimation of Multiple Superimposed Undamped Tones and Their Application to Radar Systems

2021 ◽  
Author(s):  
Pasquale Di Viesti ◽  
ALESSANDRO DAVOLI ◽  
Giorgio Guerzoni ◽  
Giorgio Matteo Vitetta
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Multiple Input Multiple Output ◽  
Likelihood Estimation ◽  
Approximate Maximum Likelihood ◽  
Radar Systems ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Novel Methods

<div>In this manuscript, novel methods for the detection of multiple superimposed tones in noise and the estimation of their parameters are derived, and their application to colocated multiple-input multiple-output radar systems is investigated.</div>

scholarly journals MIMO Detectors Under Correlated Channels

2016 ◽  
Vol 37 (1) ◽  
pp. 3
Author(s):  
Bruno Felipe Costa ◽  
Alex Miyamoto Mussi ◽  
Taufik Abrão
Keyword(s):  
Maximum Likelihood ◽  
Interference Cancellation ◽  
Mean Squared Error ◽  
Multiple Input Multiple Output ◽  
Successive Interference Cancellation ◽  
Correlated Channels ◽  
Minimum Mean Squared Error ◽  
Squared Error ◽  
Multiple Input ◽  
Input Multiple Output

Este artigo analisa o desempenho de detectores com múltiplas antenas transmissoras e múltiplas antenas receptoras (MIMO – multiple-input multiple-output) em canais com desvanecimento correlacionados. Dois esquemas de detecção MIMO denominados erro quadrático médio mínimo (MMSE – minimum mean squared error) – com ou sem a etapa de cancelamento de interferência sucessiva ordenado (OSIC – ordered successive interference cancellation) – e técnica de redução treliça (LR – lattice reduction) são analisados e comparados com o limite de detecção de máxima verossimilhança (ML – maximum likelihood) em cenários específicos de interesse: (a) com incremento da eficiência espectral através do aumento do número de antenas. (b) quando há aumento nos índices de correlação de desvanecimento do canal. Neste contexto, o desempenho do detector ótimo ML-MIMO é utilizado como referência visando caracterizar o comportamento da taxa de erro de bit (BER) destes detectores MIMO e quão próximo esses estão do desempenho ML-MIMO.

Partition-Based Hybrid MIMO Decoding Schemes with Combined Depth- and Breath-First Search

2013 ◽  
Vol 284-287 ◽  
pp. 2652-2656
Author(s):  
Jong In Park ◽  
Young Po Lee ◽  
Seok Ho Yoon
Keyword(s):  
Computational Complexity ◽  
Maximum Likelihood ◽  
Multiple Input Multiple Output ◽  
Search Algorithms ◽  
Search Method ◽  
Breadth First Search ◽  
Error Performance ◽  
Search Methods ◽  
Multiple Input ◽  
Input Multiple Output

In this paper, we propose a novel maximum likelihood (ML) decoding scheme based on the combination of depth- and breadth-first search methods on a partitioned tree for multiple input multiple output systems. The proposed scheme first partitions the searching tree into several stages, each of which is then searched by a depth- or breadth-first search method, possibly exploiting the advantages of both the depth- and breadth-first search methods in an organized way. Numerical results indicate that, when the depth- and breadth-first search algorithms are adopted appropriately, the proposed scheme exhibits substantially lower computational complexity than conventional ML decoders while maintaining the ML bit error performance.

scholarly journals Novel Methods for Approximate Maximum Likelihood Estimation of Multiple Superimposed Undamped Tones and Their Application to Radar Systems

2021 ◽  
Author(s):  
Pasquale Di Viesti ◽  
ALESSANDRO DAVOLI ◽  
Giorgio Guerzoni ◽  
Giorgio Matteo Vitetta
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Multiple Input Multiple Output ◽  
Likelihood Estimation ◽  
Approximate Maximum Likelihood ◽  
Radar Systems ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Novel Methods

<div>In this manuscript, novel methods for the detection of multiple superimposed tones in noise and the estimation of their parameters are derived, and their application to colocated multiple-input multiple-output radar systems is investigated.</div>

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