DARPA's neXt Generation (XG) communication program proposes the use of Dynamic Spectrum Access (DSA) wherein intelligent radios can realize opportunistic usage of frequency bands by identifying the under-utilized spectrum and reasoning about it. Implementing such a flexible scheme requires changes in the current static spectrum management approach. As a result, declarative spectrum management through policy-based dynamic spectrum access has garnered significant attention recently. Policy-based dynamic spectrum access decouples the Spectrum Access Policies and Policy Processing Components from the Radio Platform. The Policies define conditions under which the radios are allowed to transmit in terms of frequencies used, geographic locations, time etc. The Policy Processing Components include a reasoning engine called the Policy Reasoner, which is responsible for enforcing these policies. This thesis describes the design and implementation of a novel policy reasoner called Bi- nary Decision Diagram based Reasoner for processing Spectrum Access Policies (BRESAP). BRESAP processes spectrum policies efficiently by reframing the policy reasoning problem as a graph based Boolean function manipulation problem. BRESAP uses Binary Decision Diagrams (BDDs) to represent, analyze and process the policies. It uses a set of efficient graph-theoretic algorithms to merge these policies into a single meta-policy and compute opportunity constraints. Our policy reasoner has the capability to respond to invalid and under-specified transmission requests sent by the System Strategy Reasoner (SSR). In case of invalid or under-specified transmission requests, BRESAP returns a set of opportunity constraints which inform the SSR of the changes needed to the transmission parameters in order to make them conform to the policies. We also propose three algorithms for computing the opportunity constraints. The complexity of the first algorithm is proportional to the number of variables in the metapolicy BDD, while the complexities of the second and third algorithms are proportional to sum of number of variables and the size (i.e., number of nodes) of the meta-policy BDD. / Master of Science

I examine the effect of television viewing and ideological orientations associated with “modern” racism such as minimization of the impact of racial discrimination and individual attribution on opposition toward preferential hiring of Blacks. Using cross-sectional General Social Survey (GSS) responses from U.S. adults between 2004 and 2010, I estimate ordered logistic regression models predicting attitudes toward preferential hiring of Blacks. Additionally, I compare agreement with key tenets of abstract liberalism to the findings of previous policy reasoning studies to determine the importance of these attitudes in predicting support for affirmative action policy. In this study, I aim to address the potential real-world implications of television exposure and abstract liberalism in influencing minority group incorporation, acceptance, and societal integration.

Cognitive radios (CRs) are devices that are capable of sensing the spectrum and using its free portions in an opportunistic manner. The free spectrum portions are referred to as white spaces or spectrum holes. It is widely believed that CRs are one of the key enabling technologies for realizing a new regulatory spectrum management paradigm, viz. dynamic spectrum access (DSA). CRs often employ software-defined radio (SDR) platforms that are capable of executing artificial intelligence (AI) algorithms to reconfigure their transmission/reception (TX/RX) parameters to communicate efficiently while avoiding interference with licensed (a.k.a. primary or incumbent) users and unlicensed (a.k.a. secondary or cognitive) users. When different stakeholders share a common resource, such as the case in spectrum sharing, security, privacy, and enforcement become critical considerations that affect the welfare of all stakeholders. Recent advances in radio spectrum access technologies, such as CRs, have made spectrum sharing a viable option for significantly improving spectrum utilization efficiency. However, those technologies have also contributed to exacerbating the difficult problems of security, privacy and enforcement. In this dissertation, we review some of the critical security and privacy threats that impact spectrum sharing. We also discuss ex ante (preventive) approaches which mitigate the security and privacy threats and help spectrum enforcement. / Ph. D.