Optimal Update in Energy Harvesting Aided Terahertz Communications with Random Blocking

TL;DR

This paper develops an optimal updating policy for energy-harvesting terahertz communication systems with random blocking, minimizing age of information and energy costs using a Markov decision process.

Contribution

It introduces a threshold-based optimal policy for energy-efficient updates in terahertz channels with random blocking and energy harvesting, supported by a new algorithm.

Findings

Optimal policy outperforms baseline strategies

Threshold structure simplifies policy computation

Energy and AoI are effectively balanced

Abstract

In this paper, we consider an information update system where wireless sensor sends timely updates to the destination over a random blocking terahertz channel with the supply of harvested energy and reliable energy backup. The paper aims to find the optimal information updating policy that minimize the time-average weighted sum of the Age of information(AoI) and the reliable energy costs by formulating an infinite state Markov decision process(MDP). With the derivation of the monotonicity of value function on each component, the optimal information updating policy is proved to have a threshold structure. Based on this special structure, an algorithm for efficiently computing the optimal policy is proposed. Numerical results show that the optimal updating policy proposed outperforms baseline policies.