The occurrence of wildlife vehicle collisions (WVCs) is an increasing problem in Sweden with a calculated increase of 45 percent from 2015 to 2022. The highest measured number of WVCs occurred in 2021 with over 67,000 reported incidents, where only the payment for the search of wounded animals were approximately 60 million Swedish crowns. The Swedish transport agency works actively with the problem by constructing several types of wildlife passages to mitigate the increasing problem, inter alia, ecoducts and fauna bridges.   The aim of this study was to evaluate the mitigation effect of wildlife passages, in this case ecoducts and fauna bridges. In addition, were also the spatial extent of the mitigation effect together with the relationship between mitigation effect and the annual daily traffic (ADT) evaluated.   The evaluation of mitigation effect was conducted by the usage of several types of geographical information systems (GIS) tools in the software ArcGIS Pro. A selection of seven passages was made, based on several requirements and each passage was assigned a study area with an area of 100 square kilometers. The mitigation effect was initially determined by conducting an Emerging hot spot analysis, categorizing the result into showing trend of decrease or showing no trend of decrease. The spatial extent of the mitigating effect was evaluated through the Emerging hot spot results while the relation between ADT and WVCs was evaluated in an overlay analysis.   Two of the passages were concluded as to having a mitigating effect, three passages were concluded as to showing no mitigating effect and two passages were excluded from further evaluation due to high uncertainty in the results. At the passages with stated mitigating effect were the spatial extent of effect shown in the whole study area. The result showed no evident correlation between ADT and mitigating effects which led to further reflections on the degree of influence that ADT has on the occurrence of WVCs.

No / A new approach for implementing QO-STBC and DHSTBC over OFDM for four, eight and sixteen transmitter antennas is presented, which eliminates interference from the detection matrix and improves performance by increasing the diversity order on the transmitter side. The proposed code promotes diversity gain in comparison with the STBC scheme, and also reduces Inter Symbol Interference.

ITC/USA 2009 Conference Proceedings / The Forty-Fifth Annual International Telemetering Conference and Technical Exhibition / October 26-29, 2009 / Riviera Hotel & Convention Center, Las Vegas, Nevada / Space-time Coding (STC) for Multiple-Input Multiple-Output (MIMO) wireless communication systems is an effective technique for providing robust wireless link performance in telemetry systems. This paper investigates the degradation in system performance when synchronization errors between the transmitter and receiver are present. Specifically, expressions that quantify the increase in symbol-error-rate as a function of symbol synchronization error are derived for a two-transmit and single receive antenna MISO system using binary frequency shift keying waveforms. These results are then extended to the MIMO case. The analytic results are verified with simulation results that show close agreement between the theoretical expressions and Monte Carlo simulation runs.

This thesis presents new methodologies to improve performance of wireless cooperative networks using the Golden Code. As a form of space-time coding, the Golden Code can achieve diversity-multiplexing tradeoff and the data rate can be twice that of the Alamouti code. In practice, however, asynchronism between relay nodes may reduce performance and channel quality can be degraded from certain antennas. Firstly, a simple offset transmission scheme, which employs full interference cancellation (FIC) and orthogonal frequency division multiplexing (OFDM), is enhanced through the use of four relay nodes and receiver processing to mitigate asynchronism. Then, the potential reduction in diversity gain due to the dependent channel matrix elements in the distributed Golden Code transmission, and the rate penalty of multihop transmission, are mitigated by relay selection based on two-way transmission. The Golden Code is also implemented in an asynchronous one-way relay network over frequency flat and selective channels, and a simple approach to overcome asynchronism is proposed. In one-way communication with computationally efficient sphere decoding, the maximum of the channel parameter means is shown to achieve the best performance for the relay selection through bit error rate simulations. Secondly, to reduce the cost of hardware when multiple antennas are available in a cooperative network, multi-antenna selection is exploited. In this context, maximum-sum transmit antenna selection is proposed. End-to-end signal-to-noise ratio (SNR) is calculated and outage probability analysis is performed when the links are modelled as Rayleigh fading frequency flat channels. The numerical results support the analysis and for a MIMO system maximum-sum selection is shown to outperform maximum-minimum selection. Additionally, pairwise error probability (PEP) analysis is performed for maximum-sum transmit antenna selection with the Golden Code and the diversity order is obtained. Finally, with the assumption of fibre-connected multiple antennas with finite buffers, multiple-antenna selection is implemented on the basis of maximum-sum antenna selection. Frequency flat Rayleigh fading channels are assumed together with a decode and forward transmission scheme. Outage probability analysis is performed by exploiting the steady-state stationarity of a Markov Chain model.

Although introductory courses in special relativity give an introduction to the causal structure of Minkowski space, it is common for causal structure in general space- times to be regarded as an advanced topic, and omitted from introductory courses in general relativity, although the related topic of gravitational lensing is often included. Here a numerical approach to visualizing the light cones in exterior Schwarzschild space taking advantage of the symmetries of Schwarzschild space and the conformal invariance of null geodesics is formulated, and used to make some of these ideas more accessible. By means of the Matlab software developed, a user is able to produce figures showing how light cones develop in Schwarzschild space, starting from an arbitrary point and developing for any length of time. The user can then interact with the figure, changing their point of view, or zooming in or out, to investigate them. This approach is then generalised, using the symbolic manipulation facility of Matlab, to allow the user to specify a metric as well as an initial point and time of development. Finally, the software is demonstrated with a selection of metrics.

The detection of weak, ground-moving targets can be improved through effective utilization of additional target signal energy collected over an extended dwell time. The signal model used in conventional radar processing limits integration of signal energy over an extended dwell. Two solutions that consider the complexity of the extended-dwell signal model and effectively combine signal energy collected over a long dwell are presented. The first solution is a single-channel algorithm that provides an estimate of the optimal detector to maximize output signal-to-interference-plus-noise ratio for the extended dwell time signal. Rather than searching for the optimal detector in an intractably large filter bank that contains all combinations of phase components, the single-channel algorithm projects dictionary entries against the data to estimate the signal’s linear and nonlinear phase components sequentially with small, phase-specific dictionaries in a multistage process. When used as the detector, the signal model formed from the estimated phase components yields near optimal performance for a wide range of target parameters for dwell times up to four seconds. In comparison, conventional radar processing methods are limited to an integration time of approximately 100 milliseconds. The second solution is a multichannel, multistage algorithm based on element-space pre-Doppler space-time-adaptive processing with two modifications that make it suitable for detection of weak targets whose energy is collected over an extended dwell time. The multichannel solution detects targets with lower radial velocities at significantly lower signal-to-noise ratios (SNRs) than conventional radar processing methods. The decrease in required input SNR for the multichannel solution as compared to conventional methods nearly doubles the detection range for a typical target of interest. Future related research includes extension of these concepts to other radar applications and investigation of algorithm performance for the multiple-target scenario.

ITC/USA 2015 Conference Proceedings / The Fifty-First Annual International Telemetering Conference and Technical Exhibition / October 26-29, 2015 / Bally's Hotel & Convention Center, Las Vegas, NV / Fading estimation in wireless communication systems depend on an expected fading model and assumptions about the channel itself. The bit error rate (BER) performance of the communication system is affected by how closely the assumptions made in de- signing the estimation technique match the deployment environment. Any unforeseen disturbances or hindrances in the environment deteriorate the BER performance of the system when the estimation system is not designed to combat the same. To combat such obstacles, estimation techniques must either be reinforced with modular systems which combat such observed types of disturbances, or be redesigned as a whole considering such observations of disturbances. In this paper a modular scheme to detect and combat sinusoidal variation in fading power is developed and tested by employing the developed scheme in a multiple-input-multiple-output (MIMO) wireless communication system which adopts Space-Time Block Coding (STBC) techniques.

This study suggests a two-step approach to identifying and interpreting regional convergence clubs in Europe. The first step involves identifying the number and composition of clubs using a space-time panel data model for annual income growth rates in conjunction with Bayesian model comparison methods. A second step uses a Bayesian space-time panel data model to assess how changes in the initial endowments of variables (that explain growth) impact regional income levels over time. These dynamic trajectories of changes in regional income levels over time allow us to draw inferences regarding the timing and magnitude of regional income responses to changes in the initial conditions for the clubs that have been identified in the first step. This is in contrast to conventional practice that involves setting the number of clubs ex ante, selecting the composition of the potential convergence clubs according to some a priori criterion (such as initial per capita income thresholds for example), and using cross-sectional growth regressions for estimation and interpretation purposes. (authors' abstract)

This thesis is concerned with channel estimation and data detection of MIMO-OFDM communication systems using Space-Time Block Coding (STBC) and Space-Frequency Block Coding (SFBC) under frequency selective channels. A new iterative joint channel estimation and signal detection technique for both STBC-OFDM and SFBC-OFDM systems is proposed. The proposed algorithm is based on a processive sequence of events for space time and space frequency coding schemes where pilot subcarriers are used for channel estimation in the first time instant, and then in the second time instant, the estimated channel is used to decode the data symbols in the adjacent data subcarriers. Once data symbols are recovered, the system recursively performs a new channel estimation using the decoded data symbols as pilots. The iterative process is repeated until all MIMO-OFDM symbols are recovered. In addition, the proposed channel estimation technique is based on the maximum likelihood (ML) approach which offers linearity and simplicity of implementation. Due to the orthogonality of STBC and SFBC, high computation efficiency is achieved since the method does not require any matrix inversion for estimation and detection at the receiver. Another major novel contribution of the thesis is the proposal of a new group decoding method that reduces the processing time significantly via the use of sub-carrier grouping for transmitted data recovery. The OFDM symbols are divided into groups to which a set of pilot subcarriers are assigned and used to initiate the channel estimation process. Designated data symbols contained within each group of the OFDM symbols are decoded simultaneously in order to improve the decoding duration. Finally, a new mixed STBC and SFBC channel estimation and data detection technique with a joint iterative scheme and a group decoding method is proposed. In this technique, STBC and SFBC are used for pilot and data subcarriers alternatively, forming the different combinations of STBC/SFBC and SFBC/STBC. All channel estimation and data detection methods for different MIMO-OFDM systems proposed in the thesis have been simulated extensively in many different scenarios and their performances have been verified fully.

Heterogeneity in modern datacenters is on the rise, in hardware resource characteristics, in workload characteristics, and in dynamic characteristics (e.g., a memoryresident copy of input data). As a result, which machines are assigned to a given job can have a significant impact. For example, a job may run faster on the same machine as its input data or with a given hardware accelerator, while still being runnable on other machines, albeit less efficiently. Heterogeneity takes on more complex forms as sets of resources differ in the level of performance they deliver, even if they consist of identical individual units, such as with rack-level locality. We refer to this as combinatorial heterogeneity. Mixes of jobs with strict SLOs on completion time and increasingly available runtime estimates in production datacenters deepen the challenge of matching the right resources to the right workloads at the right time. In this dissertation, we hypothesize that it is possible and beneficial to simultaneously leverage all of this information in the form of declaratively specified spacetime soft constraints. To accomplish this, we first design and develop our principal building block—a novel Space-Time Request Language (STRL). It enables the expression of jobs’ preferences and flexibility in a general, extensible way by using a declarative, composable, intuitive algebraic expression structure. Second, building on the generality of STRL, we propose an equally general STRL Compiler that automatically compiles STRL expressions into Mixed Integer Linear Programming (MILP) problems that can be aggregated and solved to maximize the overall value of shared cluster resources. These theoretical contributions form the foundation for the system we architect, called TetriSched, that instantiates our conceptual contributions: (a) declarative soft constraints, (b) space-time soft constraints, (c) combinatorial constraints, (d) orderless global scheduling, and (e) in situ preemption. We also propose a set of mechanisms that extend the scope and the practicality of TetriSched’s deployment by analyzing and improving on its scalability, enabling and studying the efficacy of preemption, and featuring a set of runtime mis-estimation handling mechanisms to address runtime prediction inaccuracy. In collaboration with Microsoft, we adapt some of these ideas as we design and implement a heterogeneity-aware resource reservation system called Aramid with support for ordinal placement preferences targeting deployment in production clusters at Microsoft scale. A combination of simulation and real cluster experiments with synthetic and production-derived workloads, a range of workload intensities, degrees of burstiness, preference strengths, and input inaccuracies support our hypothesis that leveraging space-time soft constraints (a) significantly improves scheduling quality and (b) is possible to achieve in a practical deployment.