Risk-Informed Interference Assessment : A Quantitative Basis for Spectrum Allocation Decisions

The impact of a new radio service allocation on incumbents is traditionally estimated using deterministic, single-value calculations, often of the worst-case. This is no longer tenable given increasing demand for spectrum rights, since it leads to over-conservative allocations that limit the social benefits of new services while giving incumbents more protection than they need.This paper describes an alternative: the use of quantitative risk assessment (QRA) to analyze the harm that may be caused by changes in radio service rules. QRA considers both the likelihood and the consequences for multiple hazard scenarios. In contrast, worst-case analysis considers just the most severe consequence, regardless of likelihood. This paper lays out four elements of risk-informed interference analysis: (1) make an inventory of all significant harmful interference hazard modes; (2) define a consequence metric to characterize the severity of hazards; (3) assess the likelihood and consequence of each hazard mode; and (4) aggregate them into a basis for decision making. The method is illustrated the results of a case study — the protection of weather satellite earth stations from co-channel cellular mobiles — and examples from the spectrum literature that show that the data and methods required to do a quantitative risk assessment are already common practice. In order to reap the benefits of risk-informed interference assessment, the paper recommends that regulators (1) develop know-how through a variety of educational initiatives; (2) use quantitative risk assessment in their analysis of harmful interference, and publish the results; and (3) pilot this approach in proceedings with limited scope, like selected site-specific license waiver proceedings. It also provides recommendations for legislators: (1) require risk-informed assessments in spectrum oversight; (2) when presented with politically charged claims of harmful interference, use risk assessment rather worst-case; and (3) support and encourage regulators that use risk-informed interference assessment