In this paper, a new full-duplex (FD) relaying scheme for a cooperative cognitive underlay network is proposed. The secondary network is composed of one secondary transmitter, one full-duplex secondary relay, and one secondary destination. The relay employs the selective-decode-and-forward (SDF) protocol. The secondary destination jointly decodes the signals from the secondary transmitter and the FD secondary relay so that the direct link can be seen as useful information rather than interference. The analysis includes the effect of the interference from the primary transmitter and the self-interference at the relay. Under equal power allocation strategy, closed-form expressions for the outage probability are derived for the proposed FD cooperative cognitive scheme, and the feasibility of FD relaying under cognitive constraints is shown. Our results also reveal that the proposed full-duplex joint-decoding (FDJD) cognitive network considerably outperforms the known full-duplex dual-hop (FDDH) scheme. Moreover, we propose an optimal power allocation (OPA) scheme. On the basis of the signal-to-interference-plus noise of the secondary network, the OPA strategy can choose between two modes of operation, cooperation between source and relay or source transmission only. Our results show that the FDJD scheme under the proposed OPA policy presents the best performance among all schemes investigated in this paper.

Agradeço aos meus orientadores, professores Evelio e Samuel, pela amizade, confiança em mim, orientação durante o doutorado, atenção dedicada e aconselhamentos que guiaram de forma excelente minhas atividades acadêmicas. Obrigado. Agradeço ao professor Samuel Montejo-Sánchez pelo auxílio com esta pesquisa. Mesmo sem nos conhecermos pessoalmente, foi sempre muito prestativo, proporcionando uma troca de ideias profícua para os resultados desta tese. Muchas gracias. Agradeço aos professores Luis Lolis, Glauber Brante e Richard Souza, pelos comentários e ideias que contribuiram enormemente para o melhoramento da pesquisa contida neste trabalho. Um agradecimento especial aos colegas dos laboratórios de pesquisa da UFPR, que de forma direta ou indireta me ajudaram a começar e terminar essa caminhada acadêmica. Obrigado pela convivência, pelas conversas, debates e ideias. Por fim o agradecimento mais importante. Agradeçoà minha família, especialmente aos meus pais, Marcus e Maria Inês, por estarem sempre presentes. O presente trabalho foi parcialmente realizado com apoio da CAPES/CNPq-Brasil. "Coragem! Levanta-te! Ele te chama.". O cego se levanta, joga seu manto fora e pede que veja. Curado de sua cegueira, Bartimeu segue o caminho da verdade. Adaptado do evangelho de Sao Marcos

Strawberries are sensitive fruits that are afflicted by various pests and diseases. Therefore, there is an intense use of agrochemicals and pesticides during production. Due to their sensitivity, temperatures or humidity at extreme levels can cause various damages to the plantation and to the quality of the fruit. To mitigate the problem, this study developed an edge technology capable of handling the collection, analysis, prediction, and detection of heterogeneous data in strawberry farming. The proposed IoT platform integrates various monitoring services into one common platform for digital farming. The system connects and manages Internet of Things (IoT) devices to analyze environmental and crop information. In addition, a computer vision model using Yolo v5 architecture searches for seven of the most common strawberry diseases in real time. This model supports efficient disease detection with 92% accuracy. Moreover, the system supports LoRa communication for transmitting data between the nodes at long distances. In addition, the IoT platform integrates machine learning capabilities for capturing outliers in collected data, ensuring reliable information for the user. All these technologies are unified to mitigate the disease problem and the environmental damage on the plantation. The proposed system is verified through implementation and tested on a strawberry farm, where the capabilities were analyzed and assessed.

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We study here the vehicle-to-vehicle (V2V) visible light communication (VLC) between two cars moving along different roadway scenarios: (i) a multiple-lane rectilinear roadway and (ii) a multiple-lane curvilinear roadway. Special emphasis was given to the implementation of full-duplex (FD) cooperative communication protocols to avoid communication disruption in the absence of a line-of-sight (LOS) channel. Importantly, we found that the cooperative FD V2V-VLC is promising for avoiding communication disruptions for cars traveling in realistic curvilinear roadways. Results in this work can be easily extended to the case of vehicle-to-infrastructure (V2I), which can also be promising in cases of low-car-density environments.