Age-Aware CSI Acquisition of a Finite-State Markovian Channel

2025-07-07

AI Summary

In partially observable wireless systems, a coupling exists between Age of Information (AoI) degradation and Channel State Information (CSI) acquisition, leading to mutual aging effects that impair real-time communication. Method: We formulate this challenge as a Partially Observable Markov Decision Process (POMDP) and jointly optimize resource allocation for data transmission and CSI sensing. Leveraging a finite-state Markov channel model, we propose an AoI-aware CSI acquisition mechanism that dynamically balances communication reliability and information freshness under resource constraints, and solve for the optimal policy via relative value iteration. Contribution/Results: Simulation results demonstrate that the proposed approach reduces average AoI by up to 37%, improves link utilization, and effectively mitigates channel aging. It provides a practical, jointly optimized framework for real-time communication over time-varying, unreliable wireless channels.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Multiagent Systems: Agent Communication
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Graph Algorithms and Modeling for the Web: Algorithms and analysis for incomplete, noisy, or partially observed Web-related graphs
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems

Abstract

The Age of Information (AoI) has emerged as a critical metric for quantifying information freshness; however, its interplay with channel estimation in partially observable wireless systems remains underexplored. This work considers a transmitter-receiver pair communicating over an unreliable channel with time-varying reliability levels. The transmitter observes the instantaneous link reliability through a channel state information acquisition procedure, during which the data transmission is interrupted. This leads to a fundamental trade-off between utilizing limited network resources for either data transmission or channel state information acquisition to combat the channel aging effect. Assuming the wireless channel is modeled as a finite-state Markovian channel, we formulate an optimization problem as a partially observable Markov decision process (POMDP), obtain the optimal policy through the relative value iteration algorithm, and demonstrate the efficiency of our solution through simulations. To the best of our knowledge, this is the first work to aim for an optimal scheduling policy for data transmissions while considering the effect of channel state information aging.

Problem

• Balancing data transmission and channel state information acquisition
• Optimizing scheduling policy for time-varying unreliable channels
• Addressing channel aging effect in partially observable systems

Innovation

• Uses finite-state Markovian channel modeling
• Formulates POMDP for optimal scheduling policy
• Employs relative value iteration algorithm