Age-optimal Scheduling over Hybrid Channels

TL;DR

This paper studies optimal scheduling strategies to minimize the age of information in a system with two heterogeneous channels, one unreliable and fast, the other reliable but slower, using Markov decision processes and threshold policies.

Contribution

It introduces a novel threshold-based scheduling policy for age minimization over hybrid channels and provides a low-complexity algorithm to compute optimal thresholds.

Findings

Threshold-type policies are optimal for the age minimization problem.

The proposed bisection algorithm efficiently finds optimal scheduling thresholds.

Numerical results demonstrate the effectiveness of the threshold policies.

Abstract

We consider the problem of minimizing the age of information when a source can transmit status updates over two heterogeneous channels. Our work is motivated by recent developments in 5G mmWave technology, where transmissions may occur over an unreliable but fast (e.g., mmWave) channel or a slow reliable (e.g., sub-6GHz) channel. The unreliable channel is modeled as a time-correlated Gilbert-Elliot channel at a high rate when the channel is in the 'ON' state. The reliable channel provides a deterministic but lower data rate. The scheduling strategy determines the channel to be used for transmission in each time slot, aiming to minimize the time-average age of information (AoI). The optimal scheduling problem is formulated as a Markov Decision Process (MDP), which is challenging to solve because super-modularity does not hold in a part of the state space. We address this challenge and show that a multi-dimensional threshold-type scheduling policy is optimal for minimizing the age. By exploiting the structure of the MDP and analyzing the discrete-time Markov chains (DTMCs) of the threshold-type policy, we devise a low-complexity bisection algorithm to compute the optimal thresholds. We compare different scheduling policies using numerical simulations.