Optimizing Information Freshness for Wireless Local Area Networks with Multiple APs
Ananth Ram Rajagopalan, Jiahui Ni, Vishrant Tripathi

TL;DR
This paper addresses minimizing Age of Information in multi-AP WLANs by developing centralized scheduling policies that account for interference, achieving significant AoI reductions in dense indoor networks.
Contribution
It introduces a novel AoI control framework for multi-AP WLANs, including lower bounds, approximation algorithms, and online policies with theoretical guarantees.
Findings
Achieved about 50% AoI reduction in simulations.
Developed polynomial-time local search algorithms for scalable implementation.
Provided constant-factor optimality guarantees for proposed policies.
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…
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