Coordination in distributed networks via coded actions with application to power control

TL;DR

This paper introduces a novel approach called coded power control for distributed agents, enabling better coordination in power control tasks by embedding information into power levels, with theoretical characterization and practical benefits demonstrated.

Contribution

It provides a theoretical characterization of feasible payoffs in asymmetric observation scenarios and introduces coded power control for improved distributed power management.

Findings

Coded power control outperforms traditional policies in simulations.

Theoretical characterization of feasible payoffs under iid system states.

A simple example of a power control code demonstrates practical benefits.

Abstract

This paper investigates the problem of coordinating several agents through their actions. Although the methodology applies to general scenarios, the present work focuses on a situation with an asymmetric observation structure that only involves two agents. More precisely, one of the agents knows the past, present, and future realizations of a state (the system state) that affects the common payoff function of the agents; in contrast, the second agent is assumed either to know the past realizations of the system state or to have no knowledge of it. In both cases, the second agent has access to some strictly causal observations of the first agent's actions, which enables the two agents to coordinate. These scenarios are applied to the problem of distributed power control; the key idea is that a transmitter may embed information about the wireless channel state into its transmit power levels so that an observation of these levels, e.g. the signal-to-interference plus noise ratio, allows the other transmitter to coordinate its power levels. The main contributions of this paper are twofold. First, we provide a characterization of the set of feasible average payoffs when the agents repeatedly take long sequences of actions and the realizations of the system state are \acs{iid}. Second, we exploit these results in the context of distributed power control and introduce the concept of coded power control. We carry out an extensive numerical analysis of the benefits of coded power control over alternative power control policies, and highlight a simple yet non-trivial example of a power control code.