9 research outputs found
Multiband Spectrum Access: Great Promises for Future Cognitive Radio Networks
Cognitive radio has been widely considered as one of the prominent solutions
to tackle the spectrum scarcity. While the majority of existing research has
focused on single-band cognitive radio, multiband cognitive radio represents
great promises towards implementing efficient cognitive networks compared to
single-based networks. Multiband cognitive radio networks (MB-CRNs) are
expected to significantly enhance the network's throughput and provide better
channel maintenance by reducing handoff frequency. Nevertheless, the wideband
front-end and the multiband spectrum access impose a number of challenges yet
to overcome. This paper provides an in-depth analysis on the recent
advancements in multiband spectrum sensing techniques, their limitations, and
possible future directions to improve them. We study cooperative communications
for MB-CRNs to tackle a fundamental limit on diversity and sampling. We also
investigate several limits and tradeoffs of various design parameters for
MB-CRNs. In addition, we explore the key MB-CRNs performance metrics that
differ from the conventional metrics used for single-band based networks.Comment: 22 pages, 13 figures; published in the Proceedings of the IEEE
Journal, Special Issue on Future Radio Spectrum Access, March 201
Sub-Nyquist Wideband Spectrum sensing for Cognitive Radio Networks: Matrix Completion via seed values
Introducci贸n: La Radio Cognitiva (CR) hace un uso eficiente del recurso radioel茅ctrico, para ello realiza la Detecci贸n de Espectro (SS) con el fin de identificar el espectro disponible. Pero debido a la r谩pida evoluci贸n de los transceptores, la microelectr贸nica y las altas frecuencias de propagaci贸n, se hace necesario que en CR se apliquen algoritmos de SS en bandas de frecuencia y se realice un muestreo inferior a la tasa de Nyquist.
Objetivo: Adaptar un algoritmo para Detecci贸n de Espectro Sub-Nyquist en Banda Ancha (WBSS) para redes de CR mediante la Compleci贸n de Matrices (MC) que integra valores semilla a partir de las muestras conocidas, con el fin de completar las entradas no muestreadas de la banda a evaluar, reconstruir las se帽ales e identificar el espectro disponible.
Metodolog铆a: Se realiz贸 una adaptaci贸n al algoritmo Aproximaci贸n Matricial de la Zona de Inter茅s (IZMA), para ello se dise帽a la etapa de reconstrucci贸n y se elige un m茅todo de detecci贸n de espectro en banda estrecha para conformar el banco de detectores; el algoritmo que se denomina IZMA_SV es evaluado a nivel de simulaci贸n, por tanto se reconstruyen se帽ales determin铆sticas en diferentes SNR y se identifica el estado del canal como ocupado o libre.
Resultados: Las simulaciones indican que el algoritmo adaptado presenta diferencias entre los valores conocidos de la matriz de muestreo M y la matriz recuperada X en SNR inferiores a -8 dB, mientras que la diferencia tiende a cero en SNR superiores a 2 dB. Conclusiones: El algoritmo IZMA-SV logra reducir el n煤mero de operaciones para llegar a la matriz aproximada X, reconstruyendo se帽ales muestreadas al 75% de la tasa Nyquist y a煤n con un muestreo del 20% se mantienen las caracter铆sticas de la se帽al que hacen posible la detecci贸n de espectro en banda ancha. Introduction: Cognitive Radio (CR) makes efficient use of the radio resource, for this it performs Spectrum Sensing (SS) in order to identify the available spectrum. But due to the rapid evolution of transceivers, microelectronics and high propagation frequencies, it is necessary for SS algorithms to be applied in frequency bands in CR and for sampling below the Nyquist rate.
Objective: Adapt an algorithm for Wideband Sub-Nyquist Spectrum Detection (WBSS) for CR networks using Matrix Completion (MC) integrating seed values from known samples, in order to complete the unsampled inputs of the band to evaluate, reconstruct the signals and the identify the available spectrum.
Method: An adaptation to the Interest Zone Matrix Approximation (IZMA) algorithm was carried out, for this purpose the reconstruction stage is designed and a narrow band spectrum sensing method is chosen to form the detector bank; the algorithm called IZMA_SV is evaluated at the simulation level, therefore deterministic signals are reconstructed in different SNRs and the channel status is identified as busy or free.
Results: The simulations indicate that the adapted algorithm shows differences between the known values of the sampling matrix M and the recovered matrix X in SNRs lower than -8 dB, while the difference tends to zero in SNRs greater than 2 dB.
Conclusions: The IZMA-SV algorithm manages to reduce the number of operations to arrive at the approximate matrix X, reconstructing signals sampled at 75% of the Nyquist rate and even with a sampling of 20% the characteristics of the signal that make possible the detection of wideband spectrum
Detecci贸n de espectro en banda ancha Sub-Nyquist para redes Radio Cognitiva: compleci贸n de matrices mediante valores semilla
Introduction: Cognitive Radio (CR) makes efficient use of the radio resource, for this it performs Spectrum Sensing (SS) in order to identify the available spectrum. But due to the rapid evolution of transceivers, microelectronics and high propagation frequencies, it is necessary for SS algorithms to be applied in frequency bands in CR and for sampling below the Nyquist rate.
Objective: Adapt an algorithm for Wideband Sub-Nyquist Spectrum Detection (WBSS) for CR networks using Matrix Completion (MC) integrating seed values from known samples, in order to complete the unsampled inputs of the band to evaluate, reconstruct the signals and the identify the available spectrum.
Method: An adaptation to the Interest Zone Matrix Approximation (IZMA) algorithm was carried out, for this purpose the reconstruction stage is designed and a narrow band spectrum sensing method is chosen to form the detector bank; the algorithm called IZMA_SV is evaluated at the simulation level, therefore deterministic signals are reconstructed in different SNRs and the channel status is identified as busy or free.
Results: The simulations indicate that the adapted algorithm shows differences between the known values of the sampling matrix M and the recovered matrix X in SNRs lower than -8 dB, while the difference tends to zero in SNRs greater than 2 dB.
Conclusions: The IZMA-SV algorithm manages to reduce the number of operations to arrive at the approximate matrix X, reconstructing signals sampled at 75% of the Nyquist rate and even with a sampling of 20% the characteristics of the signal that make possible the detection of wideband spectrum.Introducci贸n: La Radio Cognitiva (CR) hace un uso eficiente del recurso radioel茅ctrico, para ello realiza la Detecci贸n de Espectro (SS) con el fin de identificar el espectro disponible. Pero debido a la r谩pida evoluci贸n de los transceptores, la microelectr贸nica y las altas frecuencias de propagaci贸n, se hace necesario que en CR se apliquen algoritmos de SS en bandas de frecuencia y se realice un muestreo inferior a la tasa de Nyquist.
Objetivo: Adaptar un algoritmo para Detecci贸n de Espectro Sub-Nyquist en Banda Ancha (WBSS) para redes de CR mediante la Compleci贸n de Matrices (MC) que integra valores semilla a partir de las muestras conocidas, con el fin de completar las entradas no muestreadas de la banda a evaluar, reconstruir las se帽ales e identificar el espectro disponible.
Metodolog铆a: Se realiz贸 una adaptaci贸n al algoritmo Aproximaci贸n Matricial de la Zona de Inter茅s (IZMA), para ello se dise帽a la etapa de reconstrucci贸n y se elige un m茅todo de detecci贸n de espectro en banda estrecha para conformar el banco de detectores; el algoritmo que se denomina IZMA_SV es evaluado a nivel de simulaci贸n, por tanto se reconstruyen se帽ales determin铆sticas en diferentes SNR y se identifica el estado del canal como ocupado o libre.
Resultados: Las simulaciones indican que el algoritmo adaptado presenta diferencias entre los valores conocidos de la matriz de muestreo M y la matriz recuperada X en SNR inferiores a -8 dB, mientras que la diferencia tiende a cero en SNR superiores a 2 dB. Conclusiones: El algoritmo IZMA-SV logra reducir el n煤mero de operaciones para llegar a la matriz aproximada X, reconstruyendo se帽ales muestreadas al 75% de la tasa Nyquist y a煤n con un muestreo del 20% se mantienen las caracter铆sticas de la se帽al que hacen posible la detecci贸n de espectro en banda ancha. 
Comprehensive survey on quality of service provisioning approaches in cognitive radio networks : part one
Much interest in Cognitive Radio Networks (CRNs) has been raised recently by enabling unlicensed (secondary) users to utilize the unused portions of the licensed spectrum. CRN utilization of residual spectrum bands of Primary (licensed) Networks (PNs) must avoid harmful interference to the users of PNs and other overlapping CRNs. The coexisting of CRNs depends on four components: Spectrum Sensing, Spectrum Decision, Spectrum Sharing, and Spectrum Mobility. Various approaches have been proposed to improve Quality of Service (QoS) provisioning in CRNs within fluctuating spectrum availability. However, CRN implementation poses many technical challenges due to a sporadic usage of licensed spectrum bands, which will be increased after deploying CRNs. Unlike traditional surveys of CRNs, this paper addresses QoS provisioning approaches of CRN components and provides an up-to-date comprehensive survey of the recent improvement in these approaches. Major features of the open research challenges of each approach are investigated. Due to the extensive nature of the topic, this paper is the first part of the survey which investigates QoS approaches on spectrum sensing and decision components respectively. The remaining approaches of spectrum sharing and mobility components will be investigated in the next part
Wideband Spectrum Sensing With Sub-Nyquist Sampling in Cognitive Radios
Multi-rate asynchronous sub-Nyquist sampling (MASS) is proposed for wideband spectrum sensing. Corresponding spectral recovery conditions are derived and the probability of successful recovery is given. Compared to previous approaches, MASS offers lower sampling rate, and is an attractive approach for cognitive radio networks
Wideband spectrum sensing with sub-nyquist sampling in cognitive radios
Multi-rate asynchronous sub-Nyquist sampling (MASS) is proposed for wideband spectrum sensing. Corresponding spectral recovery conditions are derived and the probability of successful recovery is given. Compared to previous approaches, MASS offers lower sampling rate, and is an attractive approach for cognitive radio networks. 漏 2012 IEEE
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Wideband Spectrum Sensing With Sub-Nyquist Sampling in Cognitive Radios
Multi-rate asynchronous sub-Nyquist sampling (MASS) is proposed for wideband spectrum sensing. Corresponding spectral recovery conditions are derived and the probability of successful recovery is given. Compared to previous approaches, MASS offers lower sampling rate, and is an attractive approach for cognitive radio networks