To counter the inefficiencies of the current spectrum usage, regulatory bodies, all over the world, are exploring ways to deregulate the spectrum market by allowing flexible dynamic spectrum access (DSA) in a broad range of spatio-temporal scale. Recent advances in radio technology have given an impetus to this trend. For DSA to fulfill its promise of economic and societal impact, wireless services based on DSA must be commercially successful, and a tangible spectrum market must evolve that can be supported by technology. This research project will build a realistic DSA architecture for cellular networks supported by appropriate market mechanisms in an integrated fashion that is both technically and economically viable and efficient. This is a truly trans-disciplinary approach spanning the fields of wireless networking and systems, algorithmics, economics, simulation and modeling, which leads to a deeper understanding of the dynamics of the spectrum market by (i) realistic modeling of various market entities (i.e., buyers, sellers, and the market mechanisms), (ii) dynamic spectrum demands and bids based on innovative and realistic population dynamics models, and (iii) new and robust market clearing mechanisms with provable performance guarantees. The results will be validated using large-scale simulations, and experiments on a prototype test bed with reconfigurable radio hardware. In addition to fostering new topics in trans-disciplinary education, this project will offer insights into market driven spectrum sharing, provide useful tools for policymakers, and ultimately guide spectrum policy decisions in DSA technology. This will, in turn, open up new business opportunities in the use of wireless spectrum.
The overall goal of this grant was to understand efficient ways for allocating and sharing spectrum. The specific research goals for our team were to study and develop a deeper understanding of the dynamics of the spectrum market by modeling various market entities--buyers, sellers, and the market mechanisms-- and develop tools for studying them in realistic settings. The project was completed in context of the FCC’s discussion on the deregulation of wireless spectrum. We found that the modeling spectrum demand for cellular providers is a key prerequisite for this task-- purely theoretical analysis, using simplistic models of spectrum demand and bids by providers is unlikely to capture the richness of strategies and mechanisms that could be adopted by the bidders. Data of this kind is proprietary, and it is hard to obtain for academic research. Therefore, we developed a first principles based framework for modeling the mobility and wireless spectrum demand in urban regions. We used it to generate models of spectrum demand for various cities in the US and analyzed their spatio-temporal variation. We also developed a computational framework, SIGMA-spectrum, used to spectrum markets. This framework allows coupling of disaggregated demand models and physical clearing models to account for wireless interference with different kinds of auction mechanisms at the primary and secondary level. The spectrum demand model is used to develop bid profiles for providers, as input to the SIGMA-spectrum. We have used this model for a number of studies, including the analysis of the primary market and the role of speculators and colluders, effect of geographic complementarity on secondary markets, and the efficacy of policy instruments for spectrum markets. Our tool for modeling mobility and wireless spectrum demand turns out to be useful in a much broader setting than spectrum markets. We have used it to analyze the vulnerability in the cellular network infrastructure and its impact in the event of a natural or human initiated cascading failures.
