Spectrum usage models for the analysis, design and simulation of cognitive radio networks

Abstract

The owned spectrum allocation policy, in use since the early days of modern radio communications, has been proven to effectively control interference among radio communication systems. However, the overwhelming proliferation of new operators, innovative services and wireless technologies during the last years has resulted, under this static regulatory regime, in the depletion of spectrum bands with commercially attractive radio propagation characteristics. An important number of spectrum measurements, however, have shown that spectrum is mostly underutilized, thus indicating that the virtual spectrum scarcity problem actually results from static and inflexible spectrum management policies rather than the physical scarcity of radio resources. This situation has motivated the emergence of Dynamic Spectrum Access (DSA) methods based on the Cognitive Radio (CR) paradigm, which has gained popularity as a promising solution to conciliate the existing conflicts between spectrum demand growth and spectrum underutilization. The basic underlying idea of DSA/CR is to allow unlicensed (secondary) users to access in an opportunistic and non-interfering manner some licensed bands temporarily unoccupied by the licensed (primary) users.

Due to the opportunistic nature of this principle, the behavior and performance of a DSA/CR network depends on the spectrum occupancy patterns of the primary system. A realistic and accurate modeling of such patterns becomes therefore essential and extremely useful in the domain of DSA/CR research. The potential applicability of spectrum usage models ranges from analytical studies to the design and dimensioning of secondary networks as well as the development of innovative simulation tools and more efficient DSA/CR techniques. Spectrum occupancy modeling in the context of DSA/CR constitutes a rather unexplored research area. This dissertation addresses the problem of modeling spectrum usage in the context of DSA/CR by contributing a comprehensive and holistic set of realistic models capable to accurately capture and reproduce the statistical properties of spectrum usage in real radio communication systems in the time, frequency and space dimensions.

The first part of this dissertation addresses the development of a unified methodological framework for spectrum measurements in the context of DSA/CR and presents the results of an extensive spectrum measurement campaign performed over a wide variety of locations and scenarios in the metropolitan area of Barcelona, Spain, to identify potential bands of interest for future DSA/CR deployments. To the best of the author's knowledge, this is the first study of these characteristics performed under the scope of the Spanish spectrum regulation and one of the earliest studies in Europe. The second part deals with various specific aspects related to the processing of measurements to extract spectrum occupancy patterns, which is largely similar to the problem of spectrum sensing in DSA/CR. The performance of energy detection, the most widely employed spectrum sensing technique in DSA/CR, is first assessed empirically. The outcome of this study motivates the development of a more accurate theoretical-empirical performance model as well as an improved energy detection scheme capable to outperform the conventional method while preserving a similar level of complexity, computational cost and application. The findings of these studies are finally applied in the third part of the dissertation to the development of innovative spectrum usage models for the time (in discrete- and continuous-time versions), frequency and space domains. The proposed models can been combined and integrated into a unified modeling approach where the time, frequency and space dimensions of spectrum usage can simultaneously be reproduced, thus providing a complete and holistic characterization of spectrum usage in real systems for the analysis, design and simulation of the future DSA/CR networks.