In this dissertation a computationally efficient cognitive multiple-input multiple-output (MIMO) orthogonal frequency division duplexing (OFDM) detector is designed to decode perfect space-time coded signals which are able maximize the diversity and multiplexing properties of a rich fading MIMO channel. The adaptive nature of the cognitive detector allows a MIMO OFDM communication system to better meet to needs of future wireless communication networks which require both high reliability and low run-time complexity depending on the propagation environment. The cognitive detector in conjunction with perfect space-time coding is able to achieve up to a 2 dB bit-error rate (BER) improvement at low signal-to-noise ratio (SNR) while also achieving comparable runtime complexity in high SNR scenarios.
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 new learning algorithm for prediction of channel states outperforms the traditional BP algorithm and Hybrid GA-PSO method with respect to classification accuracy, probability of misdetection, and Probability of false alarm.
This dissertation presents beamforming designs. Using novel techniques and methods, the performance of the beamforming is improved on dual-band, tri-band, flexible function, tunable function in THz, and dynamic controllability on incident wave.
In this dissertation, some multi-function and flexible RF/microwave devices have been studied to solve the issues in the modern microwave system designs. First, a power divider with two functions is proposed. The first function is a zero-phase delay power divider using zero-phase impedance transformer. The second function is a power divider with impedance transforming property. To achieve the first function, the two arms are treated as zero-phase impedance transformers. When the phase requirement is relaxed, the second function is obtained. Shunt transmission line stubs are employed to connect the isolation resistor, which provides great flexibility in the design. Then, a balun with transparent termination impedance and flexible open arms is designed. The design parameters of the balun are independent to the port impedance. This property allows the balun to work with different system impedances. Furthermore, the two output ports of the balun do not need to be connected together, which enables the device to have a very flexible structure. Finally, the continuous research of a tunable/reconfigurable coupler with equal output impedance is presented. In addition to the tunable/reconfigurable responses, unequal output impedance property is added to the microstrip line coupler. To shrink the size at the low frequency and make it easy for fabrication at higher frequency, the coupler is redesigned using lumped components. To validate the design theories, simulations are carried out. Moreover, prototypes of the power divider and the balun are fabricated and characterized. The simulation and measurement results match well with the theoretical calculation.
In situations where information infrastructure is destroyed or not available, on-demand information infrastructure is pivotal for the success of rescue missions. In this paper, a drone-carried on-demand information infrastructure for long-distance WiFi transmission system is developed. It can be used in the areas including emergency response, public event, and battlefield. In years development, the Drone WIFI System has developed from single-CPU platform, twin-CPU platform, Atmega2560 platform to NVIDIA Jetson TX2 platform. By the upgrade of the platform, the hardware shows more and more reliable and higher performance which make the application of the platform more and more exciting. The latest TX2 platform can provide real time and thermal video transmission, also application of deep learning of object recognition and target tracing. All these up-to-date technology brings more application scenarios to the system. Therefore, the system can serve more people in more scenarios.
This dialog allows you to filter your current search.
Each of the Years listed note their name and the number of records that will be limited down to if you choose that option.
This dialog allows you to filter your current search.
Each of the Months listed note their name and the number of records that will be limited down to if you choose that option.
This dialog allows you to filter your current search.
Each of the Rights Access listed note their name and the number of records that will be limited down to if you choose that option.