International Telemetering Conference Proceedings / October 23-26, 2000 / Town & Country Hotel and Conference Center, San Diego, California / The presence of multipath fading has been shown to degrade the performance of a wireless channel. This paper quantifies the effects of multipath interference on signal performance based on the estimated parameters of the multipath signal. Theoretical results are compared with actual results obtained through the Advanced Range Telemetry (ARTM) program.

The world's demand for energy is an ongoing challenge, which has yet to be overcome. The efforts to find clean energy alternatives to fossil fuels have been hampered by the lack of investment in technology and research. Among these clean energy alternatives are ocean waves and wind. Wind power is generated through the use of wind generators that harness the wind's kinetic energy; it has gained worldwide popularity as a large-scale energy source, but only provides less than one percent of global energy consumption. Due to infrastructure limitations on installations of wind turbines at locations where high winds exist, wind energy faces critical challenges difficult to overcome to continue improving electricity generation. Ocean wave energy on the other hand seems like a promising adjunction to wind energy. Ocean energy comes in a variety of forms such as marine currents, tidal currents, geothermal vents and waves. Most of today's research however is based on wave energy. It has been estimated that approximately 257 Terawatt hour per year (TWh/year) could be extracted from ocean waves alone. This amount of energy could be enough to meet the U.S. energy demands of 28 TWh/year. Technologies such as point absorbers, attenuators and overtopping devices are examples of wave energy converters. Point absorbers use a floating structure with components that move relative to each other due to the wave action. The relative motion is used to drive electromechanical or hydraulic energy converters. The total energy throughput of a single point absorber however, does not justify for the great engineering cost and effort by researchers. Thus the need to explore other alternatives of wave conversion that result in no extra-added cost but yet increases throughput. Our research focuses on exploring a novel method to maximize wave energy conversion of an array-based point absorber wave farm. Unlike previous research, our method incorporates a predictive control algorithm to aid the wave farm with the prediction of dynamics and optimal control trajectory over a finite time and space horizon of ocean waves. By using a predictive control algorithm, wave energy conversion throughput can be increased as opposed to a system without. This algorithm requires that the wave characteristics of the incoming wave be provided in advance for appropriate processing. This thesis focuses on designing an efficient and reliable wireless communications system capable of delivering wave information such as speed, height and direction to each point absorber in the network for further processing by the predictive control algorithm. This process takes place in the presence of harsh environmental conditions where the random shape of waves and moving surface can further affect the communication channel. In this work we focus on the physical layer where the transmission of bits over the wireless medium takes place. Specifically we are interested in reducing the bit error rate with a unique relaying protocol to increase packet transmission reliability. We make use of cooperative diversity and existing protocols to achieve our goal of merit and improve end-to-end system performance. / Graduation date: 2012

Master of Science / Department of Statistics / Christopher Vahl / Sample size estimation is generally based on assumptions made during the planning stage of a clinical trial. Often, there is limited information available to estimate the initial sample size. This may result in a poor estimate. For instance, an insufficient sample size may not have the capability to produce statistically significant results, while an over-sized study will lead to a waste of resources or even ethical issues in that too many patients are exposed to potentially ineffective treatments. Therefore, an interim analysis in the middle of a trial may be worthwhile to assure that the significance level is at the nominal level and/or the power is adequate to detect a meaningful treatment difference. In this report, the impact of sample size re-estimation on the type I error rate for the continuous end-point in a clinical trial with two treatments is evaluated through a simulation study. Two sample size estimation methods are taken into consideration: blinded and partially unblinded. For the blinded method, all collected data for two groups are used to estimate the variance, while only data from the control group are used to re-estimate the sample size for the partially unblinded method. The simulation study is designed with different combinations of assumed variance, assumed difference in treatment means, and re-estimation methods. The end-point is assumed to follow normal distribution and the variance for both groups are assumed to be identical. In addition, equal sample size is required for each group. According to the simulation results, the type I error rates are preserved for all settings.

Data resulting from eye-tracking experiments allows researchers to analyze the decision making process as study participants consider alternative items prior to the ultimate end point selection. The aim of such an analysis is to extract the underlying cognitive decision making process that develops throughout the experiment. Resulting data can be difficult to analyze, however, as eye-tracking curves have very high autocorrelation values which consists of measurements that are milliseconds apart, as mandated by the nature of eye movements. We propose an analytic approach to eye-tracking data that tests for statistically significant differences at every time point along the curve while calculating an appropriate familywise error rate correction which is based upon an autoregressive correlation assumption of the test statistics. Our technique has been implemented in the R package BDOTS with various extensions relevant to the real-world analysis of highly correlated nonlinear data. A popular alternative approach to analyzing eye-tracking data is to fit mixed models to the area under the curve. Through simulation studies we provide evidence for the benefit of using information criterion measures in selection of the random effects structure and make an argument against current industry-standard approaches such as sequential likelihood ratio tests or always using a maximal random effects structure.

Current-controlled logic and single electron logic processors have been investigated with respect to thermal-induced bit error. A maximal error rate for both logic processors is regarded as one bit-error/year/chip. A maximal clock frequency and an information channel capacity at a given operation current are derived when a current-controlled logic processor works without error. An available operation range in a current-controlled processor with 100 million elements is discussed. The dependence of an error-free condition on temperature in single electron logic processors is derived. The size of the quantum dot of single electron transistor is predicted when a single electron logic processor with the a billion single electron transistors works without error at room temperature.

Current-controlled logic and single electron logic processors have been investigated with respect to thermal-induced bit error. A maximal error rate for both logic processors is regarded as one bit-error/year/chip. A maximal clock frequency and an information channel capacity at a given operation current are derived when a current-controlled logic processor works without error. An available operation range in a current-controlled processor with 100 million elements is discussed. The dependence of an error-free condition on temperature in single electron logic processors is derived. The size of the quantum dot of single electron transistor is predicted when a single electron logic processor with the a billion single electron transistors works without error at room temperature.

This thesis is focused on the proposal form filling error rate in life insurance. The theoretical part of the thesis describes main aspects of the methodology Lean Six Sigma, which will be used to decrease high error rate. Lean Six Sigma is widely used in today's companies to improve business processes by increasing their sigma. The methodology is an integration of two separate approaches, both invented in the beginning of the 20th century. The aim of the integration is to bring together the best of both of them. The practical part of the thesis shows how the seemingly separed approaches Lean and Six Sigma can work together. Lean was used to improve the process for insurance company's sales force, and Six Sigma was then applied to decrease the error rate of the forms. Both of the improvements were successfully implemented in the company and led to a desired outcome.

This thesis presents a timing error detector (TED) used in the symbol timing synchronization subsystem for digital communications. The new timing error detector is designed to minimize the probability of symbol decision error, and it is called minimum symbol error rate TED (MSERTED). The new TED resembles the TED derived using the maximum likelihood (ML) criterion but gives rise to faster convergence relative to MLTED. The new TED requires shorter training sequences for symbol timing recovery. The TED operates on the outputs of the matched filter and estimates the timing offset. The S-curve is used as a tool for analyzing the behavior of the TEDs. The faster convergence of the new TED is shown in simulation results as compared to MLTED. The new TED works well for any two-dimensional constellation with arbitrarily shaped decision regions.

The growth of broadband Internet access has paved the way for the development of many newer existing technologies. As the costs of implementing broadband access soar, the best alternative will be to use wireless technologies. At a carrier frequency of about 28 GHz, the potential benefits of Local Multipoint Distribution Service (LMDS) will eventually outweigh those of its current competitors in the wired market. Since the rural communities will reap the most benefits from this technology due to its low costs, studies on the channel behavior and terrain relationships must be done. This thesis aims to provide a preliminary study on the effects of propagating an LMDS signal over a lake surface. Currently, there is not enough information to prove the feasibility of deploying an LMDS system for this terrain. Some background on the technology and rough surface theory is provided for the reader to better understand the environment that is being investigated. Simulation results are presented as a guide to assist future researchers to conduct a field measurement campaign. A block diagram of a potential measurement system is also provided to aid in the development of the tools necessary for the measurement of an actual channel. / Master of Science

Echo state network (ESN) is a specific neural network structure composed of high dimensional nonlinear dynamics and learned readout weights. This thesis considers applying ESN for symbol detection in multiple-input, multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) systems. A new ESN structure, namely, windowed echo state networks (WESN) is introduced to further improve the symbol detection performance. Theoretical analysis justifies WESN has an enhanced short-term memory (STM) compared with the standard ESN such that WESN can offer better computing ability. Additionally, the bandwidth spent as the training set is the same as the demodulation reference signals defined in 3GPP LTE/LTE-Advanced systems for the ESN/WESN based symbol detection. Meanwhile, a unified training framework is developed for both comb and scattered pilot patterns. Complexity analysis demonstrates the advantages of ESN/WESN based symbol detector compared to conventional symbol detectors such as linear minimum mean square error (LMMSE) and sphere decoder when the system is employed with a large number of OFDM sub-carriers. Numerical evaluations show that ESN/WESN has an improvement of symbol detection performance as opposed to conventional methods in both low SNR regime and power amplifier (PA) nonlinear regime. Finally, it demonstrates that WESN can generate a better symbol detection result over ESN. / Artificial neural networks (ANN) are widely used in recognition tasks such as recommendation systems, robotics path planning, self-driving, video tracking, image classifications, etc. To further explore the applications of ANN, this thesis considers using a specific ANN, echo state network (ESN) for a wireless communications task: MIMO-OFDM symbol detection. Furthermore, it proposed an enhanced version of the standard ESN, namely, windowed echo state network (WESN). Theoretical analyses on the short term memory (STM) of ESN and WESN show that the later one has a longer STM. Besides, the training set size of this ESN/WESN based method is chosen the same as the pilot symbols used in conventional communications systems. The algorithm complexity analysis demonstrates the ESN/WESN based method performs with lower complexity compared with conventional methods, such as linear mean square error (LMMSE) and sphere decoding. Comprehensive simulations examine how the symbol detection performance can be improved by using ESN and its variant WESN when the transmission link is non-ideal.