Bustamante, Pedro and Gomez, Marcela and Weiss, Martin B.H. and Znati, Taieb and Park, Jung-Min (Jerry) and Das, Debarun and Rose, J. Stephanie
(2018)
Agent-Based Modelling Approach for Developing Enforcement Mechanisms in Spectrum Sharing Scenarios: An application for the 1695-1710MHz band.
In: Telecommunications Policy Research Conference, 21-22 Sept 2018, Washington DC.
Abstract
As radio spectrum sharing matures, one of the main challenges becomes finding adequate governance systems and the appropriate enforcement mechanisms. Historically, these processes were assigned to a central entity (in most cases a governmental agency). Nevertheless, the literature of Common Pool Resources (CPRs) shows that other governance mechanisms are possible, which include collaboration with a private, thirdparty regulator or the complete absence of central institutions, as in self-enforcement solutions. These alternatives have been developed around well-known CPRs such as fisheries, forests, etc. As argued by Weiss et al [50], and other researchers, spectrum can indeed be considered to be a CPR. In this work we study the two extremes of governance systems that could be applied to spectrum sharing scenarios. Initially, we study the classical centralized scheme of command and control, where governmental institutions are in charge of rule-definition and enforcement. Subsequently, we explore a government-less environment, i.e., a distributed enforcement approach. In this anarchy situation (i.e., lack of a formal government intervention as defined by Leeson [29]), rules and enforcement mechanisms are solely the product of repeated interactions among the intervening agents. For our analysis, we have selected the spectrum sharing framework of the 1695-1710MHz band. We also use the definitions presented by Bhattarai et al. [9], [10] as well as Altamimi [3] for managing the size of the coordination and exclusion zones. In addition, we utilize Agent-Based Modelling (ABM) to analyze the applicability of these governance mechanisms. ABM simulation allows us to explore how macro phenomena can emerge from micro-level interactions of independent agents.
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