Desarrollo de una forma de onda GFDM con radio definida por software

In this paper the performance of a Generalized Frequency Division Multiplexing waveform is evaluated when compared to an Orthogonal Frequency Division Multiplexing signal. For the development of the previous waveforms, the GNU radio software and the Software Defined Radio (SDR) equipment USRP N210 are used. Through a spectrum analyzer the power of both waveforms are measured and the Out-of-Band Radiation is analyzed. Then, the results obtained are compared and the advantages and disadvantages of the implementation of GFDM as a waveform within the fifth generation systems are exposed.En este documento se evalúa el desempeño de una forma de onda GFDM (Generalized Frequency Division Multiplexing) que es comparada con una señal OFDM (Orthogonal Frequency Division Multiplexing). Para el desarrollo de las anteriores formas de onda se utilizan el software GNU radio y los equipos de Radio Definida por Software (SDR) USRP N210. Mediante un analizador de espectros se mide la potencia de ambas formas de onda y se analiza la Radiación Fuera de Banda (OOB). Luego, se comparan los resultados obtenidos y se exponen las ventajas e inconvenientes de la implementación de GFDM como forma de onda dentro de los sistemas de quinta generación

A Survey on Aerial Swarm Robotics

The use of aerial swarms to solve real-world problems has been increasing steadily, accompanied by falling prices and improving performance of communication, sensing, and processing hardware. The commoditization of hardware has reduced unit costs, thereby lowering the barriers to entry to the field of aerial swarm robotics. A key enabling technology for swarms is the family of algorithms that allow the individual members of the swarm to communicate and allocate tasks amongst themselves, plan their trajectories, and coordinate their flight in such a way that the overall objectives of the swarm are achieved efficiently. These algorithms, often organized in a hierarchical fashion, endow the swarm with autonomy at every level, and the role of a human operator can be reduced, in principle, to interactions at a higher level without direct intervention. This technology depends on the clever and innovative application of theoretical tools from control and estimation. This paper reviews the state of the art of these theoretical tools, specifically focusing on how they have been developed for, and applied to, aerial swarms. Aerial swarms differ from swarms of ground-based vehicles in two respects: they operate in a three-dimensional space and the dynamics of individual vehicles adds an extra layer of complexity. We review dynamic modeling and conditions for stability and controllability that are essential in order to achieve cooperative flight and distributed sensing. The main sections of this paper focus on major results covering trajectory generation, task allocation, adversarial control, distributed sensing, monitoring, and mapping. Wherever possible, we indicate how the physics and subsystem technologies of aerial robots are brought to bear on these individual areas