Cognitive Radio (CR) technology creates the opportunity for unlicensed users to make use of the spectral band provided it does not interfere with any licensed user. It is a prominent tool with spectrum sensing functionality to identify idle channels and let the unlicensed users avail them. Thus, the CR technology provides the consumers access to a very large spectrum, quality spectral utilization, and energy efficiency due to spectral load balancing. However, the full potential of the CR technology can be realized only with CRs equipped with accurate mechanisms to predict/sense the spectral holes and vacant spectral bands without any prior knowledge about the characteristics of traffic in a real-time environment. Multi-layered perception (MLP), the popular neural network trained with the back-propagation (BP) learning algorithm, is a keen tool for classification of the spectral bands into "busy" or "idle" states without any a priori knowledge about the user system features. In this dissertation, we proposed the use of an evolutionary algorithm, Bacterial Foraging Optimization Algorithm (BFOA), for the training of the MLP NN. We have compared the performance of the proposed system with the traditional algorithm and with the Hybrid GA-PSO method. With the results of a simulation experiment that this …

Consumer drones have used both standards such as Wi-Fi as well as proprietary communication protocols, such as DJI's OcuSync. While these methods are well suited to certain flying scenarios, they are limited in range to around 4.3 miles. Government and military unmanned aerial vehicles (UAVs) controlled through satellites allow for a global reach in a low-latency environment. To address the range issue of commercial UAVs, this thesis investigates using standardized cellular technologies for command and control of UAV systems. The thesis is divided into five chapters: Chapter 1 is the introduction to the thesis. Chapter 2 describes the equipment used as well as the test setup. This includes the drone used, the cellular module used, the microcontroller used, and a description of the software written to collect the data. Chapter 3 describes the data collection goals, as well as locations in the sky that were flown in order to gather experimental data. Finally, the results are presented in Chapter 4, which draws limited correlation between the collected data and flight readiness Chapter 5 wraps up the thesis with a conclusion and future areas for research are also presented.

RSA cryptography is one of the most widely used cryptosystems in the world. FPGA/ASIC implementations for the classic RSA cryptosystem have high resource utilization due to the use of the Extended Euclid's algorithm for MOD inverse generation, the MOD exponent operation for encryption and decryption, and through non finite-field arithmetic. This thesis translates the RSA cryptosystem into the finite-field domain of arithmetic which greatly increases the range of encryption and decryption keys and replaces the MOD exponent with a multiplication. A new algorithm, the SPX algorithm, is presented and shown to outperform Euclid's algorithm, which is the most widely used mechanism to compute the GCD in FPGA implementations of RSA. The SPX algorithm is then extended to support the computation of the MOD inverse and supply decryption keys. Lastly, a finite-field RSA system is created and shown to support character encryption and decryption while being designed to be integrated into any larger system.