SPECTRUM OBSERVATORY BASED TRAFFIC MODELING AND CHANNEL SELECTION IN SUPPORT OF DYNAMIC SPECTRUM ACCESS

It is well known that the exponential growth in popularity of wireless devices has created a demand for radio spectrum that cannot be met with current regulatory policies. Despite the difficulty in procuring access to new spectrum resources, many empirical studies have indicated that the majority of spectrum is in-fact unused in the temporal, spatial and/or spectral domains, representing an untapped wealth that must be exploited. Dynamic Spectrum Access (DSA) is a promising technology which aims to improve the efficiency of future radios and alleviate the issue of spectrum under-utilization. This dissertation utilizes the data from the IIT Spectrum Observatory to develop models of channel activity on the Land Mobile Radio (LMR) band (used for critical communication by organizations such as public safety) and shows how such models can be applied to improve the performance of DSA. We demonstrate that LMR traffic may possess multi-timescale behavior – such as clustering and dispersion over different time periods – and propose a novel statistical model to account for these observations based on a multiple emission hidden Markov model. We then used this model to design a collision constrained channel selection algorithm that can permit the re-use of licensed spectrum while minimizing interference with incumbent users. The findings in this work are primarily developed for public safety, however the techniques developed are general enough to be applied to other types of traffic possessing similar characteristics. The proposed model, in particular, is well suited for further analytic work and simulations studies in this area.Ph.D. in Electrical and Computer Engineering, May 201

Empirical Modeling of Public Safety to Voice Traffic to Aid Emergency Capacity

An RF measurement system with high time resolution is implemented to determine the statistical characteristics of various channels in the Land Mobile Radio bands. The applicability of simple statistical models to the observed data is investigated, as well as their validity over short and long periods of time. The results show that the statistics of the idle and holding times of communication on these channels vary significantly over time and demonstrate daily periodicity, requiring non-stationary models to accurately represent them. Over short durations of time however, conventional distributions such as the exponential and lognormal may adequately characterize the properties of these quantities, allowing convenient and compact representations of the data. Results based on empirical data are presented to quantify the probability of stationarity for voice traffic within a time span of given length. The findings are useful for network planning or streamlining, network simulation and modeling, and investigation of dynamic spectrum access.Sponsorship: National Science Foundation, Federal Communications Commission, Motorola, Cleversafe, Roberson & Associates LL

Learning Branching Heuristics for Propositional Model Counting

Propositional model counting, or #SAT, is the problem of computing the number of satisfying assignments of a Boolean formula. Many problems from different application areas, including many discrete probabilistic inference problems, can be translated into model counting problems to be solved by #SAT solvers. Exact #SAT solvers, however, are often not scalable to industrial size instances. In this paper, we present Neuro#, an approach for learning branching heuristics to improve the performance of exact #SAT solvers on instances from a given family of problems. We experimentally show that our method reduces the step count on similarly distributed held-out instances and generalizes to much larger instances from the same problem family. It is able to achieve these results on a number of different problem families having very different structures. In addition to step count improvements, Neuro# can also achieve orders of magnitude wall-clock speedups over the vanilla solver on larger instances in some problem families, despite the runtime overhead of querying the model

Solar Hydrogen Hybrid System (semester?), IPRO 301

The photovoltaic/hydrogen hybrid energy system IPRO was started eight years ago. A group of students with their faculty advisor began a semester to investigate the use of solar energy to power an electric sign. Since that time, a significant amount of progress has been made. The project progressed from the design phase to the laboratory phase. Once functioning, it was transferred to the roof of the Co-Gen plant on the IIT main campus. During this phase of the project, Phase I, a photovoltaic system was set up that included several solar panels on the roof. Also, a large LED sign was installed on the roof. An array of power management devices were set up at the project site inside the Co-Gen plant. Phase II of the project was planned in order to incorporate an electrolyzer and fuel cell as an energy back up system in conjunction with the PV system. Although these components exist at the work site, they are not integrated into the complete system and are merely there to demonstrate using hydrogen to power an electric load.Deliverables for IPRO 301: Solar Hydrogen Hybrid System for the Fall 2004 semeste

Solar Hydrogen Hybrid System (semester?), IPRO 301: Solar Hydrogen Hybrid System IPRO 301 Poster F04

The photovoltaic/hydrogen hybrid energy system IPRO was started eight years ago. A group of students with their faculty advisor began a semester to investigate the use of solar energy to power an electric sign. Since that time, a significant amount of progress has been made. The project progressed from the design phase to the laboratory phase. Once functioning, it was transferred to the roof of the Co-Gen plant on the IIT main campus. During this phase of the project, Phase I, a photovoltaic system was set up that included several solar panels on the roof. Also, a large LED sign was installed on the roof. An array of power management devices were set up at the project site inside the Co-Gen plant. Phase II of the project was planned in order to incorporate an electrolyzer and fuel cell as an energy back up system in conjunction with the PV system. Although these components exist at the work site, they are not integrated into the complete system and are merely there to demonstrate using hydrogen to power an electric load.Deliverables for IPRO 301: Solar Hydrogen Hybrid System for the Fall 2004 semeste

Solar Hydrogen Hybrid System (semester?), IPRO 301: Solar Hydrogen Hybrid System IPRO 301 Final Report F04

The photovoltaic/hydrogen hybrid energy system IPRO was started eight years ago. A group of students with their faculty advisor began a semester to investigate the use of solar energy to power an electric sign. Since that time, a significant amount of progress has been made. The project progressed from the design phase to the laboratory phase. Once functioning, it was transferred to the roof of the Co-Gen plant on the IIT main campus. During this phase of the project, Phase I, a photovoltaic system was set up that included several solar panels on the roof. Also, a large LED sign was installed on the roof. An array of power management devices were set up at the project site inside the Co-Gen plant. Phase II of the project was planned in order to incorporate an electrolyzer and fuel cell as an energy back up system in conjunction with the PV system. Although these components exist at the work site, they are not integrated into the complete system and are merely there to demonstrate using hydrogen to power an electric load.Deliverables for IPRO 301: Solar Hydrogen Hybrid System for the Fall 2004 semeste

Hatching Havens: Identifying Mosquito Larval Habitats at the KSU Field Station

Several species of mosquitoes found in the greater Atlanta metropolitan region are known vectors of West Nile and La Crosse viruses. Infection with these arthropod-borne viruses may result in febrile illness, neuroinvasion, long-term neurological sequelae, or death. We investigated the potential for mosquito breeding habitats at the Kennesaw State University (KSU) Field Station. The KSU Field Station is a 25-acre property located in Cobb County, GA, that is used for teaching and research activities, which range from farming to ecological studies involving native flora and fauna. The classes and ongoing research projects taking place at the KSU Field Station require frequent visitation and outdoor work involving students, staff, and faculty – potentially putting these persons at risk of mosquito bites and thus any circulating arthropod-borne virus that might be present. The KSU Field Station was surveyed on August 25th, 2023 for artificial water holding containers and the presence or absence of mosquito larvae. The Container Index (CI) was calculated per World Health Organization (WHO) guidelines. We determined the CI for the KSU Field Station was 29.0%, which per the WHO indicates a high threat of pathogen transmission (in event arthropod-borne viruses are circulating). Critically needed public health education materials were then developed for KSU students, staff, and faculty. Public health communication efforts were subsequently launched at the KSU Field Station to disseminate and educate persons working at and visiting the Field Station on methods to decrease mosquito exposure and thereby prevent bites