Statistical Modeling of the Interference Noise Generated by Computing Platforms

Alban, Eduardo; Magaña, Mario E.; Skinner, Harry; Slattery, Kevin

doi:10.1109/temc.2011.2164255

Cited by 7 publications

(4 citation statements)

References 18 publications

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“…This experiment considers the RFI generated by computing equipment [27,30] that affects the transmission of the desired information signals. For an SNR = À3 dB, Figure 6 shows the RFI signal and its filtered version using 1MM SKF with its matrix evaluated with the SIT.…”

Section: Experiments Five: Radio Frequency Interference (Rfi) Signalsmentioning

confidence: 99%

Ubiquitous Filtering for Nonlinear Problems

Kontorovich¹,

Ramos-Alarcon²

2020

Research Advances in Chaos Theory

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This chapter develops and extends the general theoretical results, previously published in the chapter "Nonlinear filtering of weak chaotic signals", and presents detailed implementations of a computationally simple, robust (filtering fidelity almost insensitive to changes of the desired input signal properties) and rather precise approach for the filtering of weak signals of different physical nature (biological, seismic, voice, etc.) in presence of white Gaussian noise. The implementations rely on non-linear filtering techniques that in general can be considered as either one-moment or multi-moment, in the sense that they operate with a single sample (instantaneous fashion) or with various adjacent samples (non-instantaneous fashion). Chaotic modeling of the real input signals allows achieving an almost ubiquitous filtering approach with a computationally simple implementation. Application of the linearization strategies (for both one and twomoment filtering) provide, additionally, "invariance" of the processing algorithms to variations on the nature and statistics of the input signals.

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Section: Experiments Five: Radio Frequency Interference (Rfi) Signalsmentioning

confidence: 99%

Ubiquitous Filtering for Nonlinear Problems

Kontorovich¹,

Ramos-Alarcon²

2020

Research Advances in Chaos Theory

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“…Narrowband noise is generated by clocks of a certain frequency. Broadband noise, however, is the combination of several electromagnetic emissions, with a bandwidth that is wider than the antenna receiving bandwidth [4]. Figure 1 [5] shows the power spectrum of the platform self interference measured in the laboratory.…”

Section: Introductionmentioning

confidence: 99%

Computer Platform Adaptive Interference Cancellation Using Higher-Order Statistics

Wang¹,

Magaña²,

Skinner³

2015

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Broadband wireless interference in a computer platform is the result of multiple dynamic electromagnetic emission sources. This interference is non-Gaussian and a receiver design based on the Gaussian assumption will yield suboptimal performance. In fact, it has a double-sided K-distribution and needs to be treated differently in the design process. When dealing with this type of interference in the presence of white Gaussian noise, traditional interference/noise cancellation schemes do not produce satisfactory results. In this paper, we present an interference mitigation method which improves BER performance. We do this by using the cross-cumulant as the criterion of goodness. Specifically, our algorithm is based on higher order statistics (HOS) and is designed to reconstruct and to cancel the interference in a recursive fashion. The algorithm is tested on both BPSK and OFDM communication environments. We compare performance in terms of BER against other cancellation methods.

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“…Este experimento considera la RFI generada por equipo de cómputo[24,27] y que afecta la transmisión de señales de información deseadas. Para una SN R = −3dB la Figura 4 muestra la señal de RFI y su versión filtrada usando el SKF 1MM con su matriz de linealización evaluada mediante el SIT.…”

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Filtraje robusto de señales débiles de fenómenos reales

Kontorovich

Ramos-Alarcon

2019

ings

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En un gran número de escenarios de la vida real se requiere procesar señales de interés que se encuentran muy inmersas en medio de ruido de fondo: señales tectónicas de las entrañas de la Tierra, otras provenientes del lejano cosmos, de telemetría biomédica, acústicas lejanas, interfaces neuronales no invasivas, etc. El propósito de este trabajo es presentar la descripción de una plataforma robusta y eficiente para hacer filtraje en tiempo real de señales muy inmersas en ruido (bastante débiles) y de naturaleza muy diferente. La estrategia propuesta se basa en dos principios: el modelado de las señales de los fenómenos físicos mediante procesos caóticos y la aplicación de estrategias de filtraje basadas en la teoría de sistemas dinámicos no lineales. Tomando como caso de estudio señales sísmicas, señales de electrocardiogramas fetales, señales de tipo voz y señales de interferencias de radiofrecuencia, este trabajo experimental muestra que la metodología es eficiente (error cuadrático medio menor al 1 %) y robusta (la estructura de filtraje, basada en filtro de Kalman, es invariante ante diferentes señales fenomenológicas). La metodología presentada resulta ser muy atractiva para aplicaciones prácticas para la detección de señales débiles en tiempo real por su alta precisión de filtraje con una mínima complejidad computacional y tiempos de procesamiento muy cortos.

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Statistical Modeling of the Interference Noise Generated by Computing Platforms

Cited by 7 publications

References 18 publications

Ubiquitous Filtering for Nonlinear Problems

Ubiquitous Filtering for Nonlinear Problems

Computer Platform Adaptive Interference Cancellation Using Higher-Order Statistics

Filtraje robusto de señales débiles de fenómenos reales

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