A Quantitative Analysis on the Impact of Spectrum Access Policy Flexibility and DSA System Capability on Spectrum Sharing Potential

While Dynamic Spectrum Access (DSA) is premised upon the existence of technologies and policies that enable flexible access to spectrum, a quantitative understanding of the coupling among DSA system capabilities, policy definition, and spectrum sharing potential remains largely unexplored. Over ten years of technology research, development, and prototype testing has resulted in algorithms and system concept advances, including the ability to deduce policy constraints (and permissions) in situ. Knowing the constraints, however, is different than selecting operating parameters (e.g., transmission power) that lead to policy compliance (e.g., interference mitigation). The primary hurdle to in situ compliance is situational awareness uncertainty, which results from the inherently stochastic nature of wireless communications and dynamics of spectrum user activity.Situational uncertainty has a significant impact on policy specifications. Lacking trusted mechanisms for handing in situ uncertainty in DSA systems, regulators manage uncertainty and associated risk through policy specifications that impose conservative operating constraints in order to maintain high degrees of interference prevention. For example, TV Band Device policies map to “worst-case” path loss assumptions based upon the range of possible operating conditions. The result is limited spectrum sharing in the majority of operating conditions in an effort to ensure risk mitigation of significant impacts associated with rare situations.This paper asserts and tests the hypothesis that improved spectrum sharing is possible via in situ probabilistic reasoning coupled with policy specifications enabling DSA system flexibility. The assertions are based upon results of ongoing research into the relationship between DSA situational awareness uncertainty and potential DSA performance as measured by capacity gain, interference mitigation, monetary cost, and other metrics. The study is investigating the performance potential of DSA systems given policies that regulate effects (e.g., interference potential) rather than specific behaviors or system characteristics (e.g., exclusion zones or receiver sensitivity). Results demonstrate the potential to adapt DSA system behaviors to the degree of uncertainty with respect to the performance metrics: High levels of uncertainty lead to more restrictive behavior (e.g., lower transmit power) than do lower levels of uncertainty. DSA situational awareness and uncertainty assessments are derived using probabilistic Structural Causal Modeling (SCM). The probabilistic SCM approach provides a formal and systematic means for probabilistic reasoning that is built upon well-established engineering models for wireless communications and the theoretical foundation of causal networks.Results represented by the use cases studied in this effort indicate a clear gain in spectrum access as a function of increased policy flexibility and probabilistic reasoning for DSA system situational awareness. Policies that govern specific DSA mechanisms or design constraints provide limited policy flexibility and spectrum sharing potential; they similarly limit the design options available to system developers. Policies that define the desired effect (e.g., capacity goal) or impact limitations (e.g., maximum interference power) afford the greatest flexibility to a DSA system and thus the greatest potential for spectrum sharing. A DSA system’s ability to use the spectrum sharing potential is then a function of the specific situation and the DSA system’s degree of situational awareness uncertainty. Probabilistic reasoning is shown to adapt permitted behaviors such as maximum interference free transmit power (MIFTP) in accordance with observed conditions and associated degrees of uncertainty. Greater uncertainty leads to reduced spectrum access and MIFTP and greater awareness leads to increased spectrum access and MIFTP.