Estimador de canal basado en sensado compresivo y LDPC para OFDM usando SDR

Contenido principal del artículo

Juan Paúl Inga Ortega http://orcid.org/0000-0003-2580-9677
Anthony Yanza Verdugo http://orcid.org/0000-0002-1710-3052
Christian Pucha Cabrera http://orcid.org/0000-0002-4734-7218

Keywords

Sensado Compresivo, Estimación de Canal, LDPC, OFDM, SDR

Resumen

Este trabajo propone la aplicación de un estimador de canal basado en sensado compresivo (CS, del inglés Compressive Sensing) sobre un sistema que usa multiplexación por división de frecuencias ortogonales (OFDM, del inglés Orthogonal Frequency Division Multiplexing) usando dispositivos de radio definido por \emph{software} (SDR, del inglés Software Defined Radio). La aplicación de la teoría de CS se da a través del uso de algoritmos de reconstrucción dispersa como Orthogonal Matching Pursuit (OMP) y Compressive Sampling Matching Pursuit (CoSaMP) con el fin de aprovechar la naturaleza dispersa de las subportadoras piloto usadas en OFDM optimizando el ancho de banda del sistema. Además, para mejorar el rendimiento de estos algoritmos, se utiliza el concepto de la matriz de comprobación de paridad dispersa que se implementa en el despliegue de códigos de comprobación de paridad de baja densidad (LDPC, del inglés Low Density Parity Check) para obtener una matriz de sensado que mejore la propiedad de restricción isométrica (RIP, del inglés Isometric Restriction Property) perteneciente al paradigma de CS. El documento muestra el modelo implementado en los equipos SDR analizando la tasa de error de bit y la cantidad de símbolos piloto usados.
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Citas

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