Optimizing Information Freshness for Wireless Local Area Networks with Multiple APs

2026-04-26

AI Summary

This work addresses the degradation of information freshness—quantified by Age of Information (AoI)—in multi-AP wireless LANs caused by co-channel and adjacent-channel interference, which induces scheduling coupling among access points. Focusing on a software-defined WLAN architecture, the paper formulates multi-AP cooperative scheduling as an action-dependent combinatorial optimization problem aimed at minimizing network-wide AoI. The key contributions include establishing the first theoretical lower bound on AoI for multi-AP settings, designing a randomized scheduling scheme combined with Lyapunov drift control that achieves a constant approximation ratio, and proving that under submodularity conditions, local search efficiently yields near-optimal solutions. Simulations based on real-world WLAN deployments demonstrate that the proposed approach reduces AoI by approximately 50% compared to distributed single-AP baselines.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization
• Search and Optimization: Combinatorial 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
• Web Mining and Content Analysis: Content-based information diffusion

Abstract

Dense indoor WLANs increasingly rely on multiple access points (APs) operating over partially overlapping spectrum to support latency-sensitive applications. In such deployments, simultaneous transmissions across APs create co-channel and adjacent-channel interference, making scheduling decisions interdependent and directly impacting information freshness. Motivated by emerging software-defined WLAN architectures that enable centralized coordination, we study the problem of minimizing network-wide Age of Information (AoI) in multi-AP WLANs. Unlike classical AoI scheduling that runs at a single AP, each scheduling decision is now coupled across APs due to interference. This leads to a new class of combinatorial AoI control problems with action-dependent time evolution. We first derive a lower bound on the achievable AoI under arbitrary scheduling policies. We then design stationary randomized policies that have constant-factor optimality guarantees relative to this bound. Building on these insights, we develop a Lyapunov drift-based online policy for systems with action-dependent frame lengths, and establish constant-factor guarantees using new ratio-based drift analysis. To enable scalable implementation, we further show that per-frame scheduling admits efficient polynomial-time local-search approximations under a submodularity assumption. Simulations using realistic WLAN layouts demonstrate about 50% AoI reduction over distributed single AP baselines.

Problem

• Age of Information
• multi-AP WLAN
• interference
• scheduling
• information freshness

Innovation

• Age of Information
• multi-AP WLAN
• interference-aware scheduling
• Lyapunov drift
• submodular optimization