RF channel characterization for cognitive radio using support vector machines

Cognitive Radio promises to revolutionize the ways in which a user interfaces with a communications device. In addition to connecting a user with the rest of the world, a Cognitive Radio will know how the user wants to connect to the rest of the world as well as how to best take advantage of unused spectrum, commonly called white space\u27. Through the concept of Dynamic Spectrum Acccess a Cognitive Radio will be able to take advantage of the white space in the spectrum by first identifying where the white space is located and designing a transmit plan for a particular white space. In general a Cognitive Radio melds the capabilities of a Software Defined Radio and a Cognition Engine. The Cognition Engine is responsible for learning how the user interfaces with the device and how to use the available radio resources while the SDR is the interface to the RF world. At the heart of a Cognition Engine are Machine Learning Algorithms that decide how best to use the available radio resources and can learn how the user interfaces to the CR. To decide how best to use the available radio resources, we can group Machine Learning Algorithms into three general categories which are, in order of computational cost: 1.) Linear Least Squares Type Algorithms, e.g. Discrete Fourier Transform (DFT) and their kernel versions, 2.) Linear Support Vector Machines (SVMs) and their kernel versions, and 3.) Neural Networks and/or Genetic Algorithms. Before deciding on what to transmit, a Cognitive Radio must decide where the white space is located. This research is focused on the task of identifying where the white space resides in the spectrum, herein called RF Channel Characterization. Since previous research into the use of Machine Learning Algorithms for this task has focused on Neural Networks and Genetic Algorithms, this research will focus on the use of Machine Learning Algorithms that follow the Support Vector optimization criterion for this task. These Machine Learning Algorithms are commonly called Support Vector Machines. Results obtained using Support Vector Machines for this task are compared with results obtained from using Least Squares Algorithms, most notably, implementations of the Fast Fourier Transform. After a thorough theoretical investigation of the ability of Support Vector Machines to perform the RF Channel Characterization task, we present results of using Support Vector Machines for this task on experimental data collected at the University of New Mexico.\u2

Transceiver architectures and sub-mW fast frequency-hopping synthesizers for ultra-low power WSNs

Wireless sensor networks (WSN) have the potential to become the third wireless revolution after wireless voice networks in the 80s and wireless data networks in the late 90s. This revolution will finally connect together the physical world of the human and the virtual world of the electronic devices. Though in the recent years large progress in power consumption reduction has been made in the wireless arena in order to increase the battery life, this is still not enough to achieve a wide adoption of this technology. Indeed, while nowadays consumers are used to charge batteries in laptops, mobile phones and other high-tech products, this operation becomes infeasible when scaled up to large industrial, enterprise or home networks composed of thousands of wireless nodes. Wireless sensor networks come as a new way to connect electronic equipments reducing, in this way, the costs associated with the installation and maintenance of large wired networks. To accomplish this task, it is necessary to reduce the energy consumption of the wireless node to a point where energy harvesting becomes feasible and the node energy autonomy exceeds the life time of the wireless node itself. This thesis focuses on the radio design, which is the backbone of any wireless node. A common approach to radio design for WSNs is to start from a very simple radio (like an RFID) adding more functionalities up to the point in which the power budget is reached. In this way, the robustness of the wireless link is traded off for power reducing the range of applications that can draw benefit form a WSN. In this thesis, we propose a novel approach to the radio design for WSNs. We started from a proven architecture like Bluetooth, and progressively we removed all the functionalities that are not required for WSNs. The robustness of the wireless link is guaranteed by using a fast frequency hopping spread spectrum technique while the power budget is achieved by optimizing the radio architecture and the frequency hopping synthesizer Two different radio architectures and a novel fast frequency hopping synthesizer are proposed that cover the large space of applications for WSNs. The two architectures make use of the peculiarities of each scenario and, together with a novel fast frequency hopping synthesizer, proved that spread spectrum techniques can be used also in severely power constrained scenarios like WSNs. This solution opens a new window toward a radio design, which ultimately trades off flexibility, rather than robustness, for power consumption. In this way, we broadened the range of applications for WSNs to areas in which security and reliability of the communication link are mandatory

Development of Simulation Components for Wireless Communication

abstract: This thesis work present the simulation of Bluetooth and Wi-Fi radios in real life interference environments. When information is transmitted via communication channels, data may get corrupted due to noise and other channel discrepancies. In order to receive the information safely and correctly, error correction coding schemes are generally employed during the design of communication systems. Usually the simulations of wireless communication systems are done in such a way that they focus on some aspect of communications and neglect the others. The simulators available currently will either do network layer simulations or physical layer level simulations. In many situations, simulations are required which show inter-layer aspects of communication systems. For all such scenarios, a simulation environment, WiscaComm which is based on time-domain samples is built. WiscaComm allows the study of network and physical layer interactions in detail. The advantage of time domain sampling is that it allows the simulation of different radios together which is better than the complex baseband representation of symbols. The environment also supports study of multiple protocols operating simultaneously, which is of increasing importance in today's environment.Dissertation/ThesisMasters Thesis Electrical Engineering 201

Timing and Carrier Synchronization in Wireless Communication Systems: A Survey and Classification of Research in the Last 5 Years

Timing and carrier synchronization is a fundamental requirement for any wireless communication system to work properly. Timing synchronization is the process by which a receiver node determines the correct instants of time at which to sample the incoming signal. Carrier synchronization is the process by which a receiver adapts the frequency and phase of its local carrier oscillator with those of the received signal. In this paper, we survey the literature over the last 5 years (2010–2014) and present a comprehensive literature review and classification of the recent research progress in achieving timing and carrier synchronization in single-input single-output (SISO), multiple-input multiple-output (MIMO), cooperative relaying, and multiuser/multicell interference networks. Considering both single-carrier and multi-carrier communication systems, we survey and categorize the timing and carrier synchronization techniques proposed for the different communication systems focusing on the system model assumptions for synchronization, the synchronization challenges, and the state-of-the-art synchronization solutions and their limitations. Finally, we envision some future research directions

Mobility Analysis and Management for Heterogeneous Networks

The global mobile data traffic has increased tremendously in the last decade due to the technological advancement in smartphones. Their endless usage and bandwidth-intensive applications will saturate current 4G technologies and has motivated the need for concrete research in order to sustain the mounting data traffic demand. In this regard, the network densification has shown to be a promising direction to cope with the capacity demands in future 5G wireless networks. The basic idea is to deploy several low power radio access nodes called small cells closer to the users on the existing large radio foot print of macrocells, and this constitutes a heterogeneous network (HetNet). However, there are many challenges that operators face with the dense HetNet deployment. The mobility management becomes a challenging task due to triggering of frequent handovers when a user moves across the network coverage areas. When there are fewer users associated in certain small cells, this can lead to significant increase in the energy consumption. Intelligently switching them to low energy consumption modes or turning them off without seriously degrading user performance is desirable in order to improve the energy savings in HetNets. This dynamic power level switching in the small cells, however, may cause unnecessary handovers, and it becomes important to ensure energy savings without compromising handover performance. Finally, it is important to evaluate mobility management schemes in real network deployments, in order to find any problems affecting the quality of service (QoS) of the users. The research presented in this dissertation aims to address these challenges. First, to tackle the mobility management issue, we develop a closed form, analytical model to study the handover and ping-pong performance as a function of network parameters in the small cells, and verify its performance using simulations. Secondly, we incorporate fuzzy logic based game-theoretic framework to address and examine the energy efficiency improvements in HetNets. In addition, we design fuzzy inference rules for handover decisions and target base station selection is performed through a fuzzy ranking technique in order to enhance the mobility robustness, while also considering energy/spectral efficiency. Finally, we evaluate the mobility performance by carrying out drive test in an existing 4G long term evolution (LTE) network deployment using software defined radios (SDR). This helps to obtain network quality information in order to find any problems affecting the QoS of the users

Advanced Trends in Wireless Communications

Physical limitations on wireless communication channels impose huge challenges to reliable communication. Bandwidth limitations, propagation loss, noise and interference make the wireless channel a narrow pipe that does not readily accommodate rapid flow of data. Thus, researches aim to design systems that are suitable to operate in such channels, in order to have high performance quality of service. Also, the mobility of the communication systems requires further investigations to reduce the complexity and the power consumption of the receiver. This book aims to provide highlights of the current research in the field of wireless communications. The subjects discussed are very valuable to communication researchers rather than researchers in the wireless related areas. The book chapters cover a wide range of wireless communication topics

Realization Limits of Impulse-Radio UWB Indoor Localization Systems

In this work, the realization limits of an impulse-based Ultra-Wideband (UWB) localization system for indoor applications have been thoroughly investigated and verified by measurements. The analysis spans from the position calculation algorithms, through hardware realization and modeling, up to the localization experiments conducted in realistic scenarios. The main focus was put on identification and characterization of limiting factors as well as developing methods to overcome them

Estudio de la aplicación de técnicas de modulación OFDM para comunicaciones ópticas guiadas en el canal infrarrojo

En los últimos años, las redes guiadas de datos han experimentado una profunda transformación, alcanzándose tasas de transferencia de centenas de Megabits por segundo. Sin embargo, la filosofía de las comunicaciones personales ha cambiado y, hoy en día, el usuario final demanda conexiones de tipo inalámbrico que puedan brindarle una mayor flexibilidad y autonomía, pero que a su vez no presenten ningún tipo de limitación en cuanto a la máxima velocidad de transmisión, de tal forma que puedan desarrollarse sobre la misma aplicaciones tan exigentes como puede ser la transmisión de video de alta calidad. En este sentido, existen dos tecnologías que compiten para que lo anterior pueda llegar a hacerse realidad. Por un lado, encontramos la tecnología de radiofrecuencia, la cual ha recibido un gran apoyo por parte de las empresas y de los centros de investigación, lo que se ha traducido en el importante desarrollo que presentan actualmente las redes locales no guiadas IEEE 802.11. Por otro lado, encontramos la tecnología que hace uso del enlace infrarrojo, cuyo máximo exponente es el estándar IrDA para comunicaciones personales punto a punto de media velocidad. Esta no es, a día de hoy, una alternativa real dentro de las redes locales no guiadas, pero la tecnología infrarroja presenta una serie de características que hacen de ella una candidata muy atractiva para varios entornos de aplicación de redes de alta velocidad. En este contexto, el presente trabajo profundiza en la caracterización del canal infrarrojo con la idea de determinar sus límites prácticos de aplicación