Deep Stacked CNN-LSTM (DS-CNN-LSTM) based Spectrum Sensing in Cognitive Radio

The multidimensionality of spectrum sensing, the intrinsic complexity of its dependence, and the unpredictability associated with spectrum data all contribute to the difficulty of the task. The network of cognitive radio (CR) is comprised of both primary and secondary users inside its network. The SUs that are part of the CR network are able to identify the spectrum band and access white space in an opportunistic manner. Enhancing spectrum efficiency may be accomplished by using white spaces. This study presents a Deep Stacked CNN-LSTM (DS-CNN-LSTM)-based spectrum sensing strategy that learns implicit features from spectrum data, such as temporal correlation. This approach is based on the research that we have conducted. The effectiveness of the recommended method is shown by a sufficient number of simulations, and the results of the simulations demonstrate that it outperforms the current state of the art in terms of detection probability and classification accuracy. A comparison is made between the most cutting-edge spectrum sensing approaches and the DS-CNN-LSTM method that has been recommended. The results of the experiments indicate that the proposed methods improve detection performance and classification accuracy even when the signal-to-noise ratio is low. As we can see, the improvement that was achieved comes at the price of a longer amount of time spent on training and a little increase in the amount of time spent on execution

Trends evaluation of precipitation and temperature in Iberian Peninsula

35 páginas, ilustraciones[ES] El cambio climático es uno de los mayores problemas ambientales al que nos enfrentamos actualmente como sociedad. La frecuencia y severidad de los fenómenos climáticos extremos como sequías e inundaciones no deja de crecer debido a aumentos en la temperatura media global y a cambios en los patrones de movimiento atmosférico. El objetivo de este trabajo es verificar la existencia de tendencias en el territorio español peninsular para la temperatura, precipitación e índice NAO, definido como la diferencia anómala entre el anticiclón de las Azores y la borrasca islandesa. Se busca analizar también cómo afecta la oscilación del Atlántico norte en las precipitaciones y la temperatura española en diferentes estaciones. Utilizando el programa de análisis estadístico Rstudio junto a datos de 67 estaciones meteorológicas con seguimiento durante al menos ochenta años, se realizaron cuatro tipos de pruebas capaces de analizar tendencias y establecer patrones relacionales entre distribuciones de datos. Una prueba K-S, una regresión lineal, la prueba de Mann-Kendall y una correlación de kendall. Se encontraron evidencias claras de la existencia de tendencias positivas en la temperatura durante todo el siglo pasado, afectando especialmente al interior de la peninsula y al litoral mediterráneo. En cuanto a la precipitación, se determinó que el cambio climático no afecta significativamente a los regímenes de precipitación a escala local, pero si lo hace de forma indirecta, modificando la oscilación del Atlántico norte de tal forma que los movimientos atmosféricos tiendan a dirigirse hacia Centroeuropa llevándose las nubes con ellos, disminuyendo la precipitación y aumentando la temperatura en la península[EN] Climate change is one of the biggest environmental problems we are currently facing as a society. The frequency and severity of extreme climatic phenomena such as droughts and floods is constantly increasing due to increases in global mean temperature and changes in atmospheric movements. The aim of this work is to verify the existence of trends in the Spanish peninsular territory in temperature, precipitation and NAO index, defined as the anomalous difference between the Azores anticyclone and the Icelandic cyclone , as well as to determine how the orth Atlantic oscillation affects Spanish precipitation and temperature in different seasons. Using the statistical analysis program Rstudio together with data from 67 meteorological stations tracked for at least eighty years, four types of tests capable of analyzing trends and establishing relational patterns between data distributions were performed. A K-S test, a linear regression, the Mann-Kendall test and a kendall correlation. Clear evidence was found for the existence of positive trends in temperature throughout the last century, especially affecting the interior of the peninsula and the Mediterranean coast. As for precipitation, it was determined that climate change does not significantly affect precipitation regimes on a local scale, but does so indirectly, modifying the North Atlantic oscillation in such a way that atmospheric movements tend to move towards Central Europe, taking clouds with them, decreasing precipitation and increasing temperature in the peninsul

Spectrum sensing and multicarrier systems optimization for cognitive radio

Dizertační práce se zabývá problematikou sledování kmitočtového spektra a následném využití daného frekvenčního pásma komunikačním systémem s více nosnými frekvencemi, jehož nastavení parametrů je provedeno na základě optimalizace. Nastavení adaptace může být prováděno s přihlédnutím k několika požadavkům a také stavu a obsazenosti jednotlivých přenosových kanálů. Systém, který je charakterizován zmíněnými vlastnostmi, je často označován jako kognitivní rádio. Uplatnění zařízení, pracujících na principech kognitivního rádia bude nejspíše v blízké budoucnosti hojně využíváno z důvodů omezeného volného kmitočtového spektra. Přínosem práce je zejména využití Kolmogorova – Smirnova statistického testu jako jedna z možností detekce přítomnosti signálu primárních uživatelů. Dále také zavedení nové kriteriální funkce u optimalizace využívající roje částic (PSO) a zahrnutí parametru EVM, kvantifikujícího odchylku bodů konstelačního diagramu, do adaptivního greedy algoritmu a do optimalizace PSO. Součástí dizertační práce je i zahrnutí nepřesné informace o stavu sledovaného kmitočtového spektra do modifikovaného greedy algoritmu. Navrhované metody jsou podloženy výsledky vytvořených simulací a v případě energetické detekce ve frekvenční oblasti i implementací metody na vývojovou desku s obvodem FPGA.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.