Space time coding for polynomial phase modulated signals

Polynomial phase modulated (PPM) signals have been shown to provide improved error rate performance with respect to conventional modulation formats under additive white Gaussian noise and fading channels in single-input single-output (SISO) communication systems. In this dissertation, systems with two and four transmit antennas using PPM signals were presented. In both cases we employed full-rate space-time block codes in order to take advantage of the multipath channel. For two transmit antennas, we used the orthogonal space-time block code (OSTBC) proposed by Alamouti and performed symbol-wise decoding by estimating the phase coefficients of the PPM signal using three different methods: maximum-likelihood (ML), sub-optimal ML (S-ML) and the high-order ambiguity function (HAF). In the case of four transmit antennas, we used the full-rate quasi-OSTBC (QOSTBC) proposed by Jafarkhani. However, in order to ensure the best error rate performance, PPM signals were selected such as to maximize the QOSTBC’s minimum coding gain distance (CGD). Since this method does not always provide a unique solution, an additional criterion known as maximum channel interference coefficient (CIC) was proposed. Through Monte Carlo simulations it was shown that by using QOSTBCs along with the properly selected PPM constellations based on the CGD and CIC criteria, full diversity in flat fading channels and thus, low BER at high signal-to-noise ratios (SNR) can be ensured. Lastly, the performance of symbol-wise decoding for QOSTBCs was evaluated. In this case a quasi zero-forcing method was used to decouple the received signal and it was shown that although this technique reduces the decoding complexity of the system, there is a penalty to be paid in terms of error rate performance at high SNRs.

Treefrogs in Forested Swamps at the La Selva Biological Station: Assemblage Variation through Space and Time

Swamp-breeding treefrogs form conspicuous components of many tropical forest sites, yet remain largely understudied. The La Selva Biological Station, a rainforest reserve in Costa Rica, harbors a rich swamp-breeding treefrog fauna that has been studied in only one of the many swamps found at the site. To understand if the species composition of treefrogs at La Selva varies over space or time, frogs were censused in 1982-83, 1994-95, 2005 and 2011 at two ponds located in the reserve. Data on treefrog habitat utilization were also collected. Species composition varied spatially only in 2011. Temporal variation was observed at both ponds for all groups tested. Habitat use varied among species and between swamps. The pattern of variation suggests that temporally dynamic systems such as temporary Neotropical forest swamps will converge and diverge in species composition over time.

Diversity and knowledge in the age of nation-building: Space and time in the thought of Yanagita Kunio

The study examines the thought of Yanagita Kunio (1875–1962), an influential Japanese nationalist thinker and a founder of an academic discipline named minzokugaku. The purpose of the study is to bring into light an unredeemed potential of his intellectual and political project as a critique of the way in which modern politics and knowledge systematically suppresses global diversity. The study reads his texts against the backdrop of the modern understanding of space and time and its political and moral implications and traces the historical evolution of his thought that culminates in the establishment of minzokugaku. My reading of Yanagita’s texts draws on three interpretive hypotheses. First, his thought can be interpreted as a critical engagement with John Stuart Mill’s philosophy of history, as he turns Mill’s defense of diversity against Mill’s justification of enlightened despotism in non-Western societies. Second, to counter Mill’s individualistic notion of progressive agency, he turns to a Marxian notion of anthropological space, in which a laboring class makes history by continuously transforming nature, and rehabilitates the common people (jomin) as progressive agents. Third, in addition to the common people, Yanagita integrates wandering people as a countervailing force to the innate parochialism and conservatism of agrarian civilization. To excavate the unrecorded history of ordinary farmers and wandering people and promote the formation of national consciousness, his minzokugaku adopts travel as an alternative method for knowledge production and political education. In light of this interpretation, the aim of Yanagita’s intellectual and political project can be understood as defense and critique of the Enlightenment tradition. Intellectually, he attempts to navigate between spurious universalism and reactionary particularism by revaluing diversity as a necessary condition for universal knowledge and human progress. Politically, his minzokugaku aims at nation-building/globalization from below by tracing back the history of a migratory process cutting across the existing boundaries. His project is opposed to nation-building from above that aims to integrate the world population into international society at the expense of global diversity.

Quasi-Orthogonal Space-Time Block Coding Using Polynomial Phase Modulation

Recently, polynomial phase modulation (PPM) was shown to be a power- and bandwidth-efficient modulation format. These two characteristics are in high demand nowadays specially in mobile applications, where devices with size, weight, and power (SWaP) constraints are common. In this paper, we propose implementing a full-diversity quasiorthogonal space-time block code (QOSTBC) using polynomial phase signals as modulation format. QOSTBCs along with PPM are used in order to improve the power efficiency of communication systems with four transmit antennas. We obtain the optimal PPM constellations that ensure full diversity and maximize the QOSTBC's minimum coding gain distance. Simulation results show that by using QOSTBCs along with a properly selected PPM constellation, full diversity in flat fading channels and thus low BER at high signal-to-noise ratios (SNR) can be ensured. More importantly, it is also shown that QOSTBCs using PPM achieve a better error performance than those using conventional modulation formats.

Space-for-Time Substitution Works in Everglades Ecological Forecasting Models

Space-for-time substitution is often used in predictive models because long-term time-series data are not available. Critics of this method suggest factors other than the target driver may affect ecosystem response and could vary spatially, producing misleading results. Monitoring data from the Florida Everglades were used to test whether spatial data can be substituted for temporal data in forecasting models. Spatial models that predicted bluefin killifish (Lucania goodei) population response to a drying event performed comparably and sometimes better than temporal models. Models worked best when results were not extrapolated beyond the range of variation encompassed by the original dataset. These results were compared to other studies to determine whether ecosystem features influence whether space-for-time substitution is feasible. Taken in the context of other studies, these results suggest space-for-time substitution may work best in ecosystems with low beta-diversity, high connectivity between sites, and small lag in organismal response to the driver variable.

Space-for-Time Substitution Works in Everglades Ecological Forecasting Models

Space-for-time substitution is often used in predictive models because long-term time-series data are not available. Critics of this method suggest factors other than the target driver may affect ecosystem response and could vary spatially, producing misleading results. Monitoring data from the Florida Everglades were used to test whether spatial data can be substituted for temporal data in forecasting models. Spatial models that predicted bluefin killifish (Lucania goodei) population response to a drying event performed comparably and sometimes better than temporal models. Models worked best when results were not extrapolated beyond the range of variation encompassed by the original dataset. These results were compared to other studies to determine whether ecosystem features influence whether space-for-time substitution is feasible. Taken in the context of other studies, these results suggest space-fortime substitution may work best in ecosystems with low beta-diversity, high connectivity between sites, and small lag in organismal response to the driver variable.

Improving the predictability of time series by chaotic parameter estimation

Limited literature regarding parameter estimation of dynamic systems has been identified as the central-most reason for not having parametric bounds in chaotic time series. However, literature suggests that a chaotic system displays a sensitive dependence on initial conditions, and our study reveals that the behavior of chaotic system: is also sensitive to changes in parameter values. Therefore, parameter estimation technique could make it possible to establish parametric bounds on a nonlinear dynamic system underlying a given time series, which in turn can improve predictability. By extracting the relationship between parametric bounds and predictability, we implemented chaos-based models for improving prediction in time series. ^ This study describes work done to establish bounds on a set of unknown parameters. Our research results reveal that by establishing parametric bounds, it is possible to improve the predictability of any time series, although the dynamics or the mathematical model of that series is not known apriori. In our attempt to improve the predictability of various time series, we have established the bounds for a set of unknown parameters. These are: (i) the embedding dimension to unfold a set of observation in the phase space, (ii) the time delay to use for a series, (iii) the number of neighborhood points to use for avoiding detection of false neighborhood and, (iv) the local polynomial to build numerical interpolation functions from one region to another. Using these bounds, we are able to get better predictability in chaotic time series than previously reported. In addition, the developments of this dissertation can establish a theoretical framework to investigate predictability in time series from the system-dynamics point of view. ^ In closing, our procedure significantly reduces the computer resource usage, as the search method is refined and efficient. Finally, the uniqueness of our method lies in its ability to extract chaotic dynamics inherent in non-linear time series by observing its values. ^

Space division multiple access for wireless sensor networks

This dissertation proposed a self-organizing medium access control protocol (MAC) for wireless sensor networks (WSNs). The proposed MAC protocol, space division multiple access (SDMA), relies on sensor node position information and provides sensor nodes access to the wireless channel based on their spatial locations. SDMA divides a geographical area into space divisions, where there is one-to-one map between the space divisions and the time slots. Therefore, the MAC protocol requirement is the sensor node information of its position and a prior knowledge of the one-to-one mapping function. The scheme is scalable, self-maintaining, and self-starting. It provides collision-free access to the wireless channel for the sensor nodes thereby, guarantees delay-bounded communication in real time for delay sensitive applications. This work was divided into two parts: the first part involved the design of the mapping function to map the space divisions to the time slots. The mapping function is based on a uniform Latin square. A Uniform Latin square of order k = m 2 is an k x k square matrix that consists of k symbols from 0 to k-1 such that no symbol appears more than once in any row, in any column, or in any m x in area of main subsquares. The uniqueness of each symbol in the main subsquares presents very attractive characteristic in applying a uniform Latin square to time slot allocation problem in WSNs. The second part of this research involved designing a GPS free positioning system for position information. The system is called time and power based localization scheme (TPLS). TPLS is based on time difference of arrival (TDoA) and received signal strength (RSS) using radio frequency and ultrasonic signals to measure and detect the range differences from a sensor node to three anchor nodes. TPLS requires low computation overhead and no time synchronization, as the location estimation algorithm involved only a simple algebraic operation.

The role of neighborhood organizations in the production of gentrifiable urban space: The case of Wynwood, Miami's Puerto Rican barrio

Partnerships between government and community-based actors and organizations are considered the hallmark of contemporary governance arrangements for the revitalization and gentrification of economically distressed, inner city areas. This dissertation uses historical, narrative analysis and ethnographic methods to examine the formation, evolution and operation of community-based governance partnerships in the production of gentrifiable urban space in the Wynwood neighborhood of Miami, FL between 1970 and 2010. This research is based on more than four years of participant observation, 60 in-depth interviews with respondents recruited through a purposive snowball sample, review of secondary and archival sources, and descriptive, statistical and GIS analysis. This study examines how different organizations formed in the neighborhood since the 1970s have facilitated the recent gentrification of Wynwood. It reveals specifically how partnerships between neighborhood-based government agencies, nonprofit organizations and real estate developers were constructed to be exclusionary and lead to inequitable economic development outcomes for Wynwood residents. The key factors conditioning these inequalities include both the rationalities of action of the organizations involved and the historical contexts in which their leaders’ thinking and actions were shaped. The historical contexts included the ethnic politics of organizational funding in the 1970s and the “entrepreneurial” turn of community-based economic development and Miami urban politics since the 1980s. Over time neighborhood organizations adopted highly pragmatic rationalities and repertoires of action. By the 2000s when Wynwood experienced unprecedented investment and redevelopment, the pragmatism of community-based organizations led them to become junior partners in governance arrangements and neighborhood activists were unable to directly challenge the inequitable processes and outcomes of gentrification.

Modeling, simulation, and characterization of space debris in low-Earth orbit

Every space launch increases the overall amount of space debris. Satellites have limited awareness of nearby objects that might pose a collision hazard. Astrometric, radiometric, and thermal models for the study of space debris in low-Earth orbit have been developed. This modeled approach proposes analysis methods that provide increased Local Area Awareness for satellites in low-Earth and geostationary orbit. Local Area Awareness is defined as the ability to detect, characterize, and extract useful information regarding resident space objects as they move through the space environment surrounding a spacecraft. The study of space debris is of critical importance to all space-faring nations. Characterization efforts are proposed using long-wave infrared sensors for space-based observations of debris objects in low-Earth orbit. Long-wave infrared sensors are commercially available and do not require solar illumination to be observed, as their received signal is temperature dependent. The characterization of debris objects through means of passive imaging techniques allows for further studies into the origination, specifications, and future trajectory of debris objects. Conclusions are made regarding the aforementioned thermal analysis as a function of debris orbit, geometry, orientation with respect to time, and material properties. Development of a thermal model permits the characterization of debris objects based upon their received long-wave infrared signals. Information regarding the material type, size, and tumble-rate of the observed debris objects are extracted. This investigation proposes the utilization of long-wave infrared radiometric models of typical debris to develop techniques for the detection and characterization of debris objects via signal analysis of unresolved imagery. Knowledge regarding the orbital type and semi-major axis of the observed debris object are extracted via astrometric analysis. This knowledge may aid in the constraint of the admissible region for the initial orbit determination process. The resultant orbital information is then fused with the radiometric characterization analysis enabling further characterization efforts of the observed debris object. This fused analysis, yielding orbital, material, and thermal properties, significantly increases a satellite's Local Area Awareness via an intimate understanding of the debris environment surrounding the spacecraft.

Revolutionaries in Space? A Counter-Review of Interstellar

Should the radical Left interpret the Nolans' Interstellar as a tribute to (neo)liberal expansionism or should we view it as a cautionary tale about a future that is just around the corner, which won't be solved by worm holes or time travel? This review takes the latter position against the recent Jacobin review, which argues the former. Here, I show that Interstellar can be productively reinterpreted as a film about a series of things that will NOT save us from our-late-capitalist-selves.

Modeling, Simulation, and Characterization of Space Debris in low-Earth Orbit

Every space launch increases the overall amount of space debris. Satellites have limited awareness of nearby objects that might pose a collision hazard. Astrometric, radiometric, and thermal models for the study of space debris in low-Earth orbit have been developed. This modeled approach proposes analysis methods that provide increased Local Area Awareness for satellites in low-Earth and geostationary orbit. Local Area Awareness is defined as the ability to detect, characterize, and extract useful information regarding resident space objects as they move through the space environment surrounding a spacecraft. The study of space debris is of critical importance to all space-faring nations. Characterization efforts are proposed using long-wave infrared sensors for space-based observations of debris objects in low-Earth orbit. Long-wave infrared sensors are commercially available and do not require solar illumination to be observed, as their received signal is temperature dependent. The characterization of debris objects through means of passive imaging techniques allows for further studies into the origination, specifications, and future trajectory of debris objects. Conclusions are made regarding the aforementioned thermal analysis as a function of debris orbit, geometry, orientation with respect to time, and material properties. Development of a thermal model permits the characterization of debris objects based upon their received long-wave infrared signals. Information regarding the material type, size, and tumble-rate of the observed debris objects are extracted. This investigation proposes the utilization of long-wave infrared radiometric models of typical debris to develop techniques for the detection and characterization of debris objects via signal analysis of unresolved imagery. Knowledge regarding the orbital type and semi-major axis of the observed debris object are extracted via astrometric analysis. This knowledge may aid in the constraint of the admissible region for the initial orbit determination process. The resultant orbital information is then fused with the radiometric characterization analysis enabling further characterization efforts of the observed debris object. This fused analysis, yielding orbital, material, and thermal properties, significantly increases a satellite’s Local Area Awareness via an intimate understanding of the debris environment surrounding the spacecraft.