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.

翻译：无线CSMA网络的性能分析因链路间复杂的感知与干扰关系而异常困难。当感知拓扑与干扰拓扑均为任意结构时，即使最基本的吞吐量特征问题也尚未解决。本文提出了一种新的分析框架，用于表征具有任意感知与干扰拓扑的无线CSMA网络吞吐量。该框架无需依赖广泛采用的零传播延迟假设，即可导出显式吞吐量表达式。核心思想在于利用感知图的团结构将原始CSMA网络转化为等效多信道网络，并通过离散时间马尔可夫更新过程对其动态建模。由此，该框架明确捕捉了链路间的全局耦合，并实现了接入参数对网络性能影响的解析评估。将所提分析方法应用于多个典型CSMA场景，包括采用通用频率复用的多基本服务集IEEE 802.11网络，以及呈现隐藏终端、暴露终端和流中效应特性的自组织拓扑。仿真结果表明，在密集部署及链路行为强耦合场景下，所提模型在吞吐量估计方面显著优于现有分析方法，并能更精确地确定接入参数。