Browsing by Author "Rieser, Christian James"
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- Biologically Inspired Cognitive Radio Engine Model Utilizing Distributed Genetic Algorithms for Secure and Robust Wireless Communications and NetworkingRieser, Christian James (Virginia Tech, 2004-09-29)This research focuses on developing a cognitive radio that could operate reliably in unforeseen communications environments like those faced by the disaster and emergency response communities. Cognitive radios may also offer the potential to open up secondary or complimentary spectrum markets, effectively easing the perceived spectrum crunch while providing new competitive wireless services to the consumer. A structure and process for embedding cognition in a radio is presented, including discussion of how the mechanism was derived from the human learning process and mapped to a mathematical formalism called the BioCR. Results from the implementation and testing of the model in a hardware test bed and simulation test bench are presented, with a focus on rapidly deployable disaster communications. Research contributions include developing a biologically inspired model of cognition in a radio architecture, proposing that genetic algorithm operations could be used to realize this model, developing an algorithmic framework to realize the cognition mechanism, developing a cognitive radio simulation toolset for evaluating the behavior the cognitive engine, and using this toolset to analyze the cognitive engineà Âs performance in different operational scenarios. Specifically, this research proposes and details how the chaotic meta-knowledge search, optimization, and machine learning properties of distributed genetic algorithm operations could be used to map this model to a computable mathematical framework in conjunction with dynamic multi-stage distributed memories. The system formalism is contrasted with existing cognitive radio approaches, including traditionally brittle artificial intelligence approaches. The cognitive engine architecture and algorithmic framework is developed and introduced, including the Wireless Channel Genetic Algorithm (WCGA), Wireless System Genetic Algorithm (WSGA), and Cognitive System Monitor (CSM). Experimental results show that the cognitive engine finds the best tradeoff between a host radio's operational parameters in changing wireless conditions, while the baseline adaptive controller only increases or decreases its data rate based on a threshold, often wasting usable bandwidth or excess power when it is not needed due its inability to learn. Limitations of this approach include some situations where the engine did not respond properly due to sensitivity in algorithm parameters, exhibiting ghosting of answers, bouncing back and forth between solutions. Future research could be pursued to probe the limits of the engineà Âs operation and investigate opportunities for improvement, including how best to configure the genetic algorithms and engine mathematics to avoid engine solution errors. Future research also could include extending the cognitive engine to a cognitive radio network and investigating implications for secure communications.
- Design and Implementation of a Swept Time Delay Short Pulse (SSTDSP) Wireless Channel Sounder for LMDSRieser, Christian James (Virginia Tech, 2001-07-17)This thesis describes the theoretical development, design, and implementation of a novel measurement system, called a Sampling Swept Time Delay Short Pulse (SSTDSP) wireless channel sounder, capable of real time in field performance characterization of high speed fixed wireless links. The SSTDSP sounder has been designed to provide vital performance metrics for fixed point high data rate applications in the 28 GHz LMDS band at a fraction of the cost and complexity of existing wideband channel sounders. The SSTDSP sounder monitors the behavior of the LMDS channel by sampling the impulse response of the channel in real time. This digitized impulse response is used to assemble a power delay profile and render real-time channel performance metrics such as the mean excess delay, RMS delay spread, maximum excess delay for a given multipath threshold, and coherence bandwidth. The SSTDSP sounder is capable of recording these metrics through three modes of operation - continuous channel monitoring, single instant channel snapshot, or data logging. Swept time delay time dilation processing is combined with precise sample and hold gating to reduce the analog to digital converter sampling rate required to digitize the nanosecond short pulses from 2 Gsps to 1 Msps, while retaining the required effective Nyquist sampling rate of 2 Gsps. This dramatically reduces the memory, digital signal processing, and data logging storage requirements as well as the overall cost of the sounder system. The thesis presents the theory behind channel sounding and discusses whether there is a "bounce path" available to LMDS. Several existing channel sounding methods are compared for this application. A number of specific design and performance criteria from each of these methods are synthesized to produce the Sampling Swept Time Delay Short Pulse Sounder architecture. The design and implementation process used to realize the SSTDSP sounder is presented, including a system overview, module details, and algorithm development details. A calibration and measurement test procedure is outlined and system verification results are presented. Current work in progress on the test platform and future improvements to the modular system are outlined, as well as conclusions and future implications of the system.