A survey of measurement-based spectrum occupancy modeling for cognitive radios

Spectrum occupancy models are very useful in cognitive radio designs. They can be used to increase spectrum sensing accuracy for more reliable operation, to remove spectrum sensing for higher resource usage efficiency, or to select channels for better opportunistic access, among other applications. In this survey, various spectrum occupancy models from measurement campaigns taken around the world are investigated. These models extract different statistical properties of the spectrum occupancy from the measured data. In addition to these models, spectrum occupancy prediction is also discussed, where autoregressive and/or moving-average models are used to predict the channel status at future time instants. After comparing these different methods and models, several challenges are also summarized based on this survey

Empirical Time-Dimension Model of Spectrum Use Based on a Discrete-Time Markov Chain With Deterministic and Stochastic Duty Cycle Models

The spectrum occupancy models widely used to date in dynamic spectrum access/cognitive radio (DSA/CR) research frequently rely on assumptions and oversimplifications that have not been validated with empirical measurement data. In this context, this paper presents an empirical time-dimension model of spectrum use that is appropriate for DSA/CR studies. Concretely, a two-state discrete-time Markov chain with novel deterministic and stochastic duty cycle models is proposed as an adequate mean to accurately describe spectrum occupancy in the time domain. The validity and accuracy of the proposed modeling approach is evaluated and corroborated with extensive empirical data from a multiband spectrum measurement campaign. The obtained results demonstrate that the proposed approach is able to accurately capture and reproduce the relevant statistical properties of spectrum use observed in real-world channels of various radio technologies. The importance of accurately modeling spectrum use in the design and evaluation of novel DSA/CR techniques is highlighted with a practical case study.Peer Reviewe

Empirical Time-Dimension Model of Spectrum Use Based on a Discrete-Time Markov Chain With Deterministic and Stochastic Duty Cycle Models

The spectrum occupancy models widely used to date in dynamic spectrum access/cognitive radio (DSA/CR) research frequently rely on assumptions and oversimplifications that have not been validated with empirical measurement data. In this context, this paper presents an empirical time-dimension model of spectrum use that is appropriate for DSA/CR studies. Concretely, a two-state discrete-time Markov chain with novel deterministic and stochastic duty cycle models is proposed as an adequate mean to accurately describe spectrum occupancy in the time domain. The validity and accuracy of the proposed modeling approach is evaluated and corroborated with extensive empirical data from a multiband spectrum measurement campaign. The obtained results demonstrate that the proposed approach is able to accurately capture and reproduce the relevant statistical properties of spectrum use observed in real-world channels of various radio technologies. The importance of accurately modeling spectrum use in the design and evaluation of novel DSA/CR techniques is highlighted with a practical case study.Peer Reviewe

Modelo de decisión del espectro para radio cognitiva que integra las pérdidas de propagación en la banda GSM del espectro radioeléctrico

Esta tesis en una investigación enmarcada dentro de la tecnología de la radio cognitiva, específicamente en la etapa de decisión del espectro, donde se selecciona(n) la(s) banda(s) más apropiada(s) para la transmisión con base en la información recopilada durante la etapa de detección del espectro y los requerimientos de los usuarios no licenciados, para esto se aplico un modelo de decisión a través de las técnicas de selección por análisis multicriterio. Dentro de este desarrollo se efectuaron mediciones en tres puntos de la ciudad de Bogotá durante un total de trece días. Con los resultados obtenidos se diseñó un modelo de decisión del espectro que integra, dentro de sus parámetros de decisión, las pérdidas de propagación en la banda GSM dentro de Bogotá y permite hacer un uso un 26% más eficiente del espectro.This research thesis is framed within the cognitive radio technology, specifically in the spectrum decision step from the cognitive cycle, where is selected the most suitable band for transmission, based on the information gathered during the step before of detecting the spectrum and the requirements of non-licensed users, then the decision model was developed through multiple-criteria decision analysis. Within this development were made measurements at three points in Bogota for a total of thirteen days. The main result was a decision model that integrates propagation loss within its decision parameters, in the GSM band and allows us to use the spectrum an 26% more efficiently

TOWARD ENHANCED WIRELESS COEXISTENCE IN THE 2.4GHZ ISM BAND VIA TEMPORAL CHARACTERIZATION AND EMPIRICAL MODELING OF 802.11B/G/N NETWORKS A DISSERTATION

This dissertation presents an extensive experimental characterization and empirical modelling of 802.11 temporal behavior. A detailed characterization of 802.11b/g/n homogeneous and heterogeneous network traffic patterns is featured, including idle time distribution and channel utilization. Duty cycle serves as a measure for spectrum busyness. Higher duty cycle levels directly impact transceivers using the spectrum, which either refrain from transmission or suffer from increased errors. Duty cycle results are provided for 802.11b, g and n Wi-Fi technologies at various throughput levels. Lower values are observed for 802.11b and g networks. Spectrum occupancy measurements are essential for wireless networks planning and deployment. Detailed characterization of 802.11g/n homogeneous and heterogeneous network traffic patterns, including activity and idle time distribution are presented. Distributions were obtained from time domain measurements and represent time fragment distributions for active and inactive periods during a specific test. This information can assist other wireless technologies in using the crowded ISM band more efficiently and achieve enhanced wireless coexistence. Empirical models of 802.11 networks in the 2.4 GHz Industrial, Scientific, and Medical (ISM) band are also presented. This information can assist other wireless technologies aiming to utilize the crowded ISM band more efficiently and achieve enhanced wireless coexistence. In this work models are derived for both homogeneous and heterogeneous 802.11 network idle time distribution. Additionally, two applications of 802.11 networks temporal characterization are presented. The first application investigates a novel method for identifying wireless technologies through the use of simple energy detection techniques to measure the channel temporal characteristics including activity and idle time probability distributions. In this work, a wireless technology identification algorithm was assessed experimentally. Temporal traffic pattern for 802.11b/g/n homogeneous and heterogeneous networks were measured and used as algorithm input. Identification accuracies of up to 96.83% and 85.9% are achieved for homogeneous and heterogeneous networks, respectively. The second application provides a case study using 802.15.4 ZigBee transmitter packet size on-line adjustments is also presented. Packet size is adaptively modified based on channel idle time distribution obtained using simple channel power measurements. Results demonstrate improved ZigBee performance and significant enhancement in throughput as a result of using adaptive packet size transmissions

Wideband Autonomous Cognitive Radios: Spectrum Awareness and PHY/MAC Decision Making

The cognitive radios (CRs) have opened up new ways of better utilizing the scarce wireless spectrum resources. The CRs have been made feasible by recent advances in software-defined radios (SDRs), smart antennas, reconfigurable radio frequency (RF) front-ends, and full-duplex RF front-end architectures, to name a few. Generally, a CR is considered as a dynamically reconfigurable radio capable of adapting its operating parameters to the surrounding environment. Recent developments in spectrum policy and regulatory domains also allow more flexible and efficient utilization of wider RF spectrum range in the future. In line with the future directions of CRs, a new vision of a future autonomous CR device, called Radiobots, was previously proposed. The goals of the proposed Radiobot surpass the dynamic spectrum access (DSA) to achieve wideband operability and the main features of cognition. In order to ensure the practicality and robust operation of the Radiobot structure, the research focus of this dissertation includes the following aspects: 1) robust spectrum sensing and operability in a centralized CR network setup; 2) robust multivariate non-parametric quickest detection for dynamic spectrum usage tracking in an alien RF environment; 3) joint physical layer and medium access control layer (PHY/MAC) decision-making for wideband bandwidth aggregation (simultaneous operation over multiple modes/networks); and 4) autonomous spectrum sensing scheduling solutions in an alien ultra wideband RF environment. The major contribution of this dissertation is to investigate the feasibility of the autonomous CR operation in heterogeneous RF environments, and to provide novel solutions to the fundamental and crucial problems/challenges, including spectrum sensing, spectrum awareness, wideband operability, and autonomous PHY/MAC protocols, thus bringing the autonomous Radiobot one step closer to reality

Modelo de propagación para un entorno urbano que identifica las oportunidades espectrales para redes móviles de radio cognitiva

El pronóstico de ocupación del espectro radioeléctrico es útil en el diseño de sistemas inalámbricos que aprovechan las oportunidades en el espectro como la radio cognitiva. En este documento se propone el desarrollo de un modelo de propagación, que a través del pronóstico de la potencia recibida, identifica las oportunidades espectrales en canales de una red móvil celular para un entorno urbano. El modelo propuesto integra un modelo de propagación a gran escala con un modelo neuronal wavelet, que combina las pérdidas promedio con las pérdidas instantáneas. Los resultados del modelo, obtenidos a través de simulaciones, son consistentes con el comportamiento observado en experimentos de este tipo de sistemas inalámbricos.Abstract. The forecast of the radioelectric spectrum occupancy is useful for wireless systems designs that take advantage of spectrum opportunities, such as cognitive radio. In this document the development of a propagation model is proposed, that through the forecasting of received power, identifies the spectral opportunities in channels of a cellular mobile network for an urban environment. The proposed model integrates a large-scale propagation model with a wavelet neural model, which combines the average losses with the instantaneous losses. The results of this model, which are obtained through simulations, are consistent with the behavior observed experimentally of this class of wireless systems.Doctorad