Cognitive radio is a technology that aims to maximize the current usage of the licensed frequency spectrum. Cognitive radio aims to provide services for license-exempt users by making use of dynamic spectrum access (DSA) and opportunistic spectrum sharing strategies (OSS). Cognitive radios are defined as intelligent wireless devices capable of adapting their communication parameters in order to operate within underutilized bands while avoiding causing interference to licensed users. An underused band of frequencies in a specific location or time is known as a spectrum hole. Therefore, in order to locate spectrum holes, reliable spectrum sensing algorithms are crucial to facilitate the evolution of cognitive radio networks. Since a large and growing body of literature has mainly focused into the conventional time domain (TD) energy detector, throughout this thesis the problem of spectrum sensing is investigated within the context of a frequency domain (FD) approach. The purpose of this study is to investigate detection based on methods of nonparametric power spectrum estimation. The considered methods are the periodogram, Bartlett's method, Welch overlapped segments averaging (WOSA) and the Multitaper estimator (MTE). Another major motivation is that the MTE is strongly recommended for the application of cognitive radios. This study aims to derive the detector performance measures for each case. Another aim is to investigate and highlight the main differences between the TD and the FD approaches. The performance is addressed for independent and identically distributed (i.i.d.) Rayleigh channels and the general Rician and Nakagami fading channels. For each of the investigated detectors, the analytical models are obtained by studying the characteristics of the Hermitian quadratic form representation of the decision statistic and the matrix of the Hermitian form is identified. The results of the study have revealed the high accuracy of the derived mathematical models. Moreover, it is found that the TD detector differs from the FD detector in a number of aspects. One principal and generalized conclusion is that all the investigated FD methods provide a reduced probability of false alarm when compared with the TD detector. Also, for the case of periodogram, the probability of sensing errors is independent of the length of observations, whereas in time domain the probability of false alarm is increased when the sample size increases. The probability of false alarm is further reduced when diversity reception is employed. Furthermore, compared to the periodogram, both Bartlett method and Welch method provide better performance in terms of lower probability of false alarm but an increased probability of detection for a given probability of false alarm. Also, the performance of both Bartlett's method and WOSA is sensitive to the number of segments, whereas WOSA is also sensitive to the overlapping factor. Finally, the performance of the MTE is dependent on the number of employed discrete prolate spheroidal (Slepian) sequences, and the MTE outperforms the periodogram, Bartlett's method and WOSA, as it provides the minimal probability of false alarm.

The doctoral thesis deals with spectrum sensing and subsequent use of the frequency spectrum by multicarrier communication system, which parameters are set on the basis of the optimization technique. Adaptation settings can be made with respect to several requirements as well as state and occupancy of individual communication channels. The system, which is characterized above is often referred as cognitive radio. Equipments operating on cognitive radio principles will be widely used in the near future, because of frequency spectrum limitation. One of the main contributions of the work is the novel usage of the Kolmogorov – Smirnov statistical test as an alternative detection of primary user signal presence. The new fitness function for Particle Swarm Optimization (PSO) has been introduced and the Error Vector Magnitude (EVM) parameter has been used in the adaptive greedy algorithm and PSO optimization. The dissertation thesis also incorporates information about the reliability of the frequency spectrum sensing in the modified greedy algorithm. The proposed methods are verified by the simulations and the frequency domain energy detection is implemented on the development board with FPGA.

[pt] Nesta tese de doutorado foi investigado, por meio de simulações computacionais e em laboratório utilizando Matlab, GNU Radio e GNU Radio Companion (GRC), o desempenho de redes de Rádio Cognitivo com sensoriamento individual (SS) e com sensoriamento cooperativo (CSS) do espectro considerando o algoritmo não paramétrico de detecção de energia e diferentes abordagens deste método de detecção. Foi também implementado um cenário de medição em tempo real usando os equipamentos de rádio definido por software (SDR por suas siglas em inglês) conhecidos como Universal Software Radio Peripheral (USRP). Os cenários de medição consideram a cooperação, baseada na utilização de regras de fusão de dados do tipo hard, no sensoriamento local de sinais de TV Digital por usuários cognitivos não licenciados. A principal contribuição desta tese de doutorado baseia-se na formulação do método de energia combinando os conceitos da teoria clássica do sensoriamento de espectro das redes de Rádio Cognitivo, tanto com sensoriamento individual (SS) como sensoriamento cooperativo (CSS) de espectro, com um cenário de implementação em laboratório levando em conta os requisitos, parâmetros técnicos e de operação do equipamento de medição SDR. / [en] This PhD thesis investigate the performance of cognitive radio networks with single sensing (SS) and cooperative spectrum sensing (CSS) networks through computational and laboratory simulations using Matlab, GNU Radio and the GNU Radio Companion (GRC) computational radio software, considering the non-parametric energy detection method and different approaches to this method. The implementation also includes a real-time measurement testbed scenario using Software Defined Radio (SDR) equipment, known as Universal Software Radio Peripheral (USRP). The measurement scenarios consider the cooperative local sensing of the digital TV by non-licensed cognitive radio users, based on hard fusion rules. The main contribution of this doctoral thesis is based on the formulation of the energy detection method combining the concepts of the classical theory of the spectrum sensing of Cognitive Radio networks, with both individual sensing (SS) and cooperative spectrum sensing (CSS), in a laboratory implementation scenario according to the requirements, technical parameters and operation of the SDR measuring equipment.