Throughput Characterization of Wireless CSMA Networks With Arbitrary Sensing and Interference Topologies

2026-04-14

AI Summary

Existing approaches struggle to accurately characterize the throughput of wireless CSMA networks under arbitrary sensing and interference topologies, particularly lacking effective analytical tools when strong coupling exists among links. This work proposes a novel framework that leverages the clique structure of the sensing graph to transform the original network into an equivalent multi-channel system. By modeling its dynamics through a discrete-time Markov renewal process, the framework yields, for the first time, an explicit analytical expression for the throughput of CSMA networks with arbitrary topologies—without relying on the zero propagation delay assumption. The method significantly improves throughput estimation accuracy in densely deployed and strongly coupled scenarios, outperforming existing techniques and providing a more reliable theoretical foundation for access parameter optimization.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization
• Search and Optimization: Evaluation and Analysis

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Social Networks and Social Media: Social media analysis through the lenses of networks
• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization

Abstract

The performance analysis of wireless CSMA networks is notoriously difficult due to the intricate sensing and interference relationships among links. Even the fundamental problem of throughput characterization remains open when sensing and interference topologies are both arbitrary. In this paper, we develop a new analytical framework for throughput characterization in wireless CSMA networks with arbitrary sensing and interference topologies. The proposed framework yields explicit throughput expressions without relying on the commonly adopted zero-propagation-delay assumption. The key idea is to exploit the clique structure of the sensing graph to transform the original CSMA network into an equivalent multi-channel network, and then model its dynamics through a discrete-time Markov renewal process. In this way, the framework explicitly captures global coupling among links and enables analytical evaluation of how access parameters affect network performance. The proposed analysis is applied to several representative CSMA scenarios, including networks with multi-BSS IEEE 802.11 networks with universal frequency reuse, and ad-hoc topologies exhibiting hidden-terminal, exposed-terminal, and flow-in-the-middle effects. Simulation results show that, in dense deployments and in scenarios with strong coupling among link behaviors, the proposed model significantly outperforms existing analytical approaches in throughput estimation and enables more accurate determination of access parameters.

Problem

• throughput characterization
• CSMA networks
• arbitrary sensing topology
• arbitrary interference topology
• wireless networks

Innovation

• CSMA
• throughput characterization
• arbitrary topology
• clique decomposition
• Markov renewal process