Dissertationen zum Thema „Information Technology|Engineering, General|Engineering, Electronics and Electrical“

Hypotheses were developed and tested to measure the cable modems operational metrics response to a reconfiguration of the cable modems' transmitted RF applied to the CMTS. The purpose of this experiment was to compare two groups on the use of non-federal RF spectrum to determine if configuring the cable modems' transmitted RF from 25.2 MHz, at 6.4 MHz Wide, 64 QAM and 31 MHz, at 6.4 MHz Wide, 64 QAM to 34.8 MHz, 6.4 MHz Wide, 64QAM improved the data services operational metrics measured by a wire line service operator to determine the quality of their product. The experiment tests the theory; configuring cable modems' transmitted RF to 34.8 MHz, 6.4 MHz Wide, 64QAM on the CMTS significantly impacted a cable modem's operational metrics, and as a result, increased operational effectiveness.

A randomized experiment on 117,084 cable modems resulted in a significant impact on SNR and transmit rates but did not present a significant impact on error rates and the trouble call metrics. The results showed that reconfiguring the cable modems' transmitted RF from 25.2 MHz, at 6.4 MHz Wide, 64 QAM and 31 MHz, at 6.4 MHz Wide, 64 QAM, to 34.8 MHz, 6.4 MHz Wide, 64QAM did significantly increase the SNR and transmit rates but did not significantly impact error rates and the trouble call truck roll metrics. The results are discussed in relation to other work implicating engineering RF management strategies and the impact on the cable modems operational metrics by reconfiguring the cable modems' RF from the lower ends of the RF spectrum into the middle of the RF spectrum configured on a wire line service operator's CMTS.

Noise is a fundamental hurdle that impedes the processing of information-bearing signals, specifically the extraction of salient information. Processing that is both optimal and efficient is desired; optimality ensures the extracted information has the highest fidelity allowed by the noise, while efficiency ensures limited resource usage. Optimal detectors and estimators have long been known, e.g., for maximum likelihood or minimum mean-squared error criteria, but might not admit an efficient implementation. A tradeoff often exists between the two goals. This thesis explores the tradeoff between optimality and efficiency in a passive radar system and an analog-to-digital converter. A passive radar system opportunistically uses illuminating signals from the environment to detect and track targets of interest, e.g., airplanes or vehicles. As an opportunistic user of signals, the system does not have control over the transmitted waveform. The available waveforms are not designed for radar and often have undesirable properties for radar systems, so the burden is on the receiver processing to overcome these obstacles. A novel technique is proposed for the processing of digital television signals as passive radar illuminators that eases the need for complex detection and tracking schemes while incurring only a small penalty in detection performance. An analog-to-digital converter samples analog signals for digital processing. The Shannon-Nyquist theorem describes a sufficient sampling and recovery scheme for bandlimited signals from uniformly spaced samples taken at a rate twice the bandwidth of the signal. Frequency-sparse signals are composed of relatively few frequency components and have fewer degrees of freedom than a frequency-dense bandlimited signal. Recent results in compressed sensing describe sufficient sampling and recovery schemes for frequency-sparse signals that require a sampling rate proportional to the spectral density and the logarithm of the bandwidth, while providing high fidelity and requiring many fewer samples, which saves resources. A proposed sampling and simple recovery scheme is shown to efficiently recover the locations of tones in a large bandwidth nearly-optimally using relatively few samples. The proposed sampling scheme is further optimized for full recovery of the input signal by matching the statistics of the scheme to the statistics of the input signal.

Recently, wireless sensor network (WSN) has become a promising technologywith a wide range of applications such as supply chain monitoringand environment surveillance. It is typically composed of multiple tiny devicesequipped with limited sensing, computing and wireless communicationcapabilities. Design of such networks presents several technique challengeswhile dealing with various requirements and diverse constraints. Performanceanalysis techniques are required to provide insight on design parametersand system behaviors.

Based on network calculus, we present a deterministic analysis methodfor evaluating the worst-case delay and buffer cost of sensor networks. Tothis end, three general traffic flow operators are proposed and their delayand buffer bounds are derived. These operators can be used in combinationto model any complex traffic flowing scenarios. Furthermore, the methodintegrates a variable duty cycle to allow the sensor nodes to operate at lowrates thus saving power. In an attempt to balance traffic load and improveresource utilization and performance, traffic splitting mechanisms areintroduced for mesh sensor networks. Based on network calculus, the delayand buffer bounds are derived in non-splitting and splitting scenarios.In addition, analysis of traffic splitting mechanisms are extended to sensornetworks with general topologies. To provide reliable data delivery in sensornetworks, retransmission has been adopted as one of the most popularschemes. We propose an analytical method to evaluate the maximum datatransmission delay and energy consumption of two types of retransmissionschemes: hop-by-hop retransmission and end-to-end retransmission.

We perform a case study of using sensor networks for a fresh food trackingsystem. Several experiments are carried out in the Omnet++ simulationenvironment. In order to validate the tightness of the two bounds obtainedby the analysis method, the simulation results and analytical results arecompared in the chain and mesh scenarios with various input traffic loads.From the results, we show that the analytic bounds are correct and tight.Therefore, network calculus is useful and accurate for performance analysisof wireless sensor network.

In this dissertation, we describe, characterize, and demonstrate the operation of a dual-in, dual-out, all-optical, fiber-based quantum switch. This "cross-bar" switch is particularly useful for applications in quantum information processing because of its low-loss, high-speed, low-noise, and quantum-state-retention properties.

Building upon on our lab's prior development of an ultrafast demultiplexer ^[1-3] , the new cross-bar switch can be used as a tunable multiplexer and demultiplexer. In addition to this more functional geometry, we present results demonstrating faster performance with a switching window of ≈45 ps, corresponding to >20-GHz switching rates. We show a switching fidelity of >98%, i. e., switched polarization-encoded photonic qubits are virtually identical to unswitched photonic qubits. We also demonstrate the ability to select one channel from a two-channel quantum data stream with the state of the measured (recovered) quantum channel having >96% relative fidelity with the state of that channel transmitted alone. We separate the two channels of the quantum data stream by 155 ps, corresponding to a 6.5-GHz datastream.

Finally, we describe, develop, and demonstrate an application that utilizes the switch's higher-speed, lower-loss, and spatio-temporal-encoding features to perform quantum state tomographies on entangled states in higher-dimensional Hilbert spaces. Since many previous demonstrations show bipartite entanglement of two-level systems, we define "higher" as d > 2 where d represents the dimensionality of a photon. We show that we can generate and measure time-bin-entangled, two-photon, qutrit (d = 3) and ququat (d = 4) states with >85% and >64% fidelity to an ideal maximally entangled state, respectively. Such higher-dimensional states have applications in dense coding ^[4] , loophole-free tests of nonlocality ^[5] , simplifying quantum logic gates ^[6] , and increasing tolerance to noise and loss for quantum information processing ^[7] .

Godkänd; 2012; Bibliografisk uppgift: Nicholas Etherden works at STRI AB (www.stri.se) in Gothenburg, Sweden. When he is not pursuing his half-time PhD studies he works as a specialist consultant in the field of Power Utility Automation, specialising on the IEC 61850 standard for power utility automation (today widely used in substations as well as some wind parks, hydro plants and DER and Smart Grid applications such as vehicle-to-grid integration). The author of this thesis received his Master of Science in Engineering Physics from Uppsala University 2000. Side tracks during his engineering studies included studies in theoretical philosophy, chemistry, ecology and environmental sciences as well as chairing the Swedish student committee of the Pugwash Conferences on Science and Worlds Affairs and later board member of the International Network of Engineers and of Scientists for Global Responsibility (INES) and chair of Swedish Scientists and Engineers Against Nuclear Arms. He has been a trainee at ABB in Västerås Sweden and spent six years as developer and team leader for the application development of a new relay protection family (ABB IED 670 series). In parallel to his professional work he studied power system engineering at Mälardalens University and travelled to all continents of the world. Since 2008 he is responsible for the STRI IEC 61850 Independent Interoperability Laboratory and a member of IEC Technical Committee 57 working group 10 "Power system communication and associated data models” and UCA/IEC 61850 User group testing subcommittee. He is co-author of IEC 61850-1 and main contributor to “Technical Report on Functional Test of IEC 61850 systems” and has held over 25 hands-on courses around the world on IEC 61850 “Communication networks and systems for power utility automation”.; 20120514 (niceth); LICENTIATSEMINARIUM Ämnesområde: Energiteknik/Energy Engineering Examinator: Professor Math Bollen, Institutionen för teknikvetenskap och matematik, Luleå tekniska universitet Diskutant: Professor Sami Repo, Tampere University of Technology, Finland Tid: Onsdag den 13 juni 2012 kl 10.00 Plats: Hörsal A, campus Skellefteå, Luleå tekniska universitet

From night vision goggles, to infrared imagers, to remote controlled bomb disposal robots; we are increasingly employing electronic vision sensors to extend or enhance the limitations of our own visual sensory system. And while we can make these systems better in terms of the amount of power they use, how much information they capture, or how much information they can send to the viewer, it is also important to keep in mind the capabilities of the human who must receive this visual information from the sensor and display system. The best interface between our own visual sensory system and that of the electronic image sensor and display system is one where the least amount of visual information is sent to our own sensory system for processing, yet contains all the visual information that we need to understand the desired environment and to make decisions based on that information. In order to do this it is important to understand both the physiology of the visual sensory system and the psychophysics of how this information is used. We demonstrate this idea by researching and designing the components needed to optimize the compression of dynamic range information onto a display, for the sake of maximizing the amount of perceivable visual information shown to the human visual system.

An idea that is repeated in the construction of our optimal system is the link between designing, modeling, and validating both the design and the model through human testing. Compressing the dynamic range of images while trying to maximize the amount of visual information shown is a unique approach to dynamic range cornpression. So the first component needed to develop our optimal compression method is a way to measure the amount of visual information present in a compressed image. We achieve this by designing an Information Content Quality Assessment metric and we validate the metric using data from our psychophysical experiments [in preparation]. Our psychophysical experiments compare different dynamic range compression methods in terms of the amount of information that is visible after compression. Our quality assessment metric is unique in that it models visual perception using information theory rather than biology. To validate this approach, we extend our model so that it can predict human visual fixation. We compare the predictions of our model against human fixation data and the fixation predictions of similar state of the art fixation models. We show that the predictions of our model are at least corn-parable or better than the predictions of these fixation models. We also present preliminary results on applying the saliency model to identify potentially salient objects in out-of-focus locations due to a finite depth-of-field [in preparation]. The final component needed to implement the optimization is a way to combine the quality assessment model with the results of the psychophysical experiments to reach an optimal compression setting. We discuss how this could be implemented in the future using a generic dynamic range compression algorithm. We also present the design of a wide dynamic range image sensor and a mixed mode readout scheme to improve the accuracy of illumination measurements for each pixel over the entire dynamic range of the imager.