Exploiting Historical Spectrum Occupancy Information for Adaptive Spectrum Sensing

Wellens, M.; Baynast, A. de; Mähönen, Petri

doi:10.1109/wcnc.2008.132

Cited by 51 publications

(21 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Possible enhancements include the intelligent selection of which channels should be sensed or how frequent a channel should be examined. However, we showed in earlier work that such deterministic behaviour is rather rare in current communication systems [38]. This may change with an increasing amount of machine-to-machine communication.…”

Section: Spectrum Usage Analysismentioning

confidence: 74%

Measuring Complexity and Predictability in Networks with Multiscale Entropy Analysis

2009

View full text Add to dashboard Cite

Abstract-We propose to use multiscale entropy analysis in characterisation of network traffic and spectrum usage. We show that with such analysis one can quantify complexity and predictability of measured traces in widely varying timescales. We also explicitly compare the results from entropy analysis to classical characterisations of scaling and self-similarity in time series by means of fractal dimension and the Hurst parameter. Our results show that the used entropy analysis indeed complements these measures, being able to uncover new information from traffic traces and time series models. We illustrate the application of these techniques both on time series models and on measured traffic traces of different types. As potential applications of entropy analysis in the networking area, we highlight and discuss anomaly detection and validation of traffic models. In particular, we show that anomalous network traffic can have significantly lower complexity than ordinary traffic, and that commonly used traffic and time series models have different entropy structures compared to the studied traffic traces. We also show that the entropy metrics can be applied to the analysis of wireless communication and networks. We point out that entropy metrics can improve the understanding of how spectrum usage changes over time and can be used to enhance the efficiency of dynamic spectrum access networks.

show abstract

Section: Spectrum Usage Analysismentioning

confidence: 74%

Measuring Complexity and Predictability in Networks with Multiscale Entropy Analysis

2009

View full text Add to dashboard Cite

show abstract

“…For comparison, we have also shown the prediction accuracy using the 1st-order Markov Chain model (1st MC), which is one of the most commonly used models in the existing papers [15], [17], [20]. We could see that the prediction accuracy of the 1st MC is only around 80%, which is much lower than that of FPM-2D, except for those services whose occupancy is high.…”

Section: Experiments Resultsmentioning

confidence: 99%

“…A direct consequence of this is that it does not have the memoryless property, i.e., how long a channel is going to remain in a certain state is a function of its history, rather than being independent of it. This latter independence assumption has been commonly used in channel access studies, see for example [15], [17], [20]. More precisely, these studies assume a two-state Markov chain model for the channel (i.e., an Eliot-Gilbert model).…”

Section: A Channel Vacancy Duration (Cvd) Distributionmentioning

confidence: 99%

Mining Spectrum Usage Data: A Large-Scale Spectrum Measurement Study

Yin

Chen

Zhang

et al. 2012

IEEE Trans. on Mobile Comput.

182

View full text Add to dashboard Cite

Dynamic spectrum access has been a hot topic for extensive study in recent years. The increasing volumes of literatures calls for a deeper understanding of the characteristics of current spectrum utilization. In this paper we present a detailed spectrum measurement study, with data collected in the 20MHz to 3GHz spectrum band and at four locations concurrently in Guangdong province of China. We examine the statistics of the collected data, including channel vacancy statistics, channel utilization within each individual wireless service, and the spectral and spatial correlation of these measures. Main findings include that the channel vacancy durations follow an exponential-like distribution, but are not independently distributed over time, and that significant spectral and spatial correlations are found between channels of the same service. We then exploit such spectrum correlation to develop a 2-dimensional frequent pattern mining algorithm that can predict channel availability based on past observations with considerable accuracy.

show abstract

“…En el contexto de la Radio Cognitiva (CR) [13], [14], los estudios de medición de espectro han dirigido su atención en el uso de la información estadística de ocupación del espectro para ser más precisos en la detección [15]. El interés en el despliegue de las tecnologías de acceso dinámico al espectro ha dado lugar a numerosas campañas de medición en diferentes países [16], [17], [18] con el fin de analizar la cantidad exacta de espectro disponible.…”

Section: Introductionunclassified

Evaluación de ocupación del espectro radioeléctrico en Bogotá-Colombia

2014

View full text Add to dashboard Cite

Este artículo describe los detalles y resultados de una campaña de medición de espectro, que tuvo lugar en Bogotá (Colombia) desde Marzo a Diciembre de 2012. El estudio incluye el análisis de ocupación de las bandas de frecuencias que van desde 54 MHz a 6 GHz. Las mediciones se ordenan de acuerdo a las diferentes bandas y servicios, a fin de proveer una visión clara de los ciclos de trabajo típicos asociados a diferentes tecnologías. Los resultados sugieren que la utilización actual del espectro es todavía muy baja, incluso en una densa área urbana.

show abstract

Exploiting Historical Spectrum Occupancy Information for Adaptive Spectrum Sensing

Cited by 51 publications

References 12 publications

Measuring Complexity and Predictability in Networks with Multiscale Entropy Analysis

Measuring Complexity and Predictability in Networks with Multiscale Entropy Analysis

Mining Spectrum Usage Data: A Large-Scale Spectrum Measurement Study

Evaluación de ocupación del espectro radioeléctrico en Bogotá-Colombia

Contact Info

Product

Resources

About