Risk-averse decisions improve reliability across multiple outage levels
Risk-Averse Decision Making with Multi-Level Reliability Guarantees
Information TheoryMachine Learning
Summary
Sometimes, engineers need to design systems that work reliably under different risk levels, like avoiding outages in wireless networks. The authors study how to make decisions that balance these different risk targets at the same time, even when the true system state is uncertain. They connect this problem to a method called 'conformal prediction' and create a new way to optimize decisions across different reliability goals. Their tests show the trade-offs and costs involved when using one policy to meet multiple risk levels.
What this means in practice
- •For wireless network engineers: Design transmission policies that ensure multiple reliability guarantees under uncertain channel conditions.
- •For systems reliability teams: Balance competing levels of performance guarantees in safety-critical system design with unknown states.
Authors
Amirmohammad Farzaneh, Osvaldo Simeone
Abstract
Many applications in engineering, including wireless broadcasting, require designs that provide performance certificates at different target outage levels. This paper studies the problem of maximizing the weighted average of such certificates in the presence of uncertainty about the true system state. The problem is shown to be equivalent to an optimization over nested prediction sets, connecting to the literature on conformal prediction and extending prior art on single-level risk-averse decision making. Furthermore, we derive a dual formulation that decouples optimization across input values. Numerical experiments on a diversity-based wireless transmission system illustrate the cost of enforcing multi-level certificates with a single shared policy and trace the Pareto trade-off between multiple reliability levels.