To access an unlicensed channel, Wi-Fi follows the Listen Before Talk (LBT) mechanism, whereas LTE-U (and future New Radio in Unlicensed (NR-U) Patriciello et al., 2020; Lagen et al., 2019) adopts the ON–OFF duty-cycled mechanism to fairly share the channel with Wi-Fi. These different mechanisms result in quite different performance for Wi-Fi and LTE-U/NR-U based on their relative deployment and density in the environment. In this work, we present an analytical model for the characterization of achievable throughputs of Wi-Fi and LTE-U networks in spatially distributed scenarios with downlink-prevalent traffic. The proposed model is used to study how LTE-U and Wi-Fi coexist with each other in spatially distributed scenarios. Our extensive simulation results show that it is a reliable model for estimating the throughput of both Wi-Fi and LTE-U in a spatially distributed deployment. The impact of various network parameters such as energy detection and carrier sense threshold on Wi-Fi and LTE-U coexistence is explored as a byproduct and corroborated via a National Instrument experimental test bed. Our model gives very high accuracy in throughput estimation and the mean normalized error is less than 3% for a 80-node scenario in which 50% of nodes belong to each of Wi-Fi and LTE-U network. The analytical model is also used to conduct coexistence studies of LTE-U and Wi-Fi.

为了访问未经许可的信道，Wi-Fi 遵循先听后听 (LBT) 机制，而 LTE-U（以及未经许可的未来新无线电 (NR-U) Patriciello 等人，2020 年；Lagen 等人，2019 年）采用ON-OFF 占空比机制与 Wi-Fi 公平地共享信道。根据 Wi-Fi 和 LTE-U/NR-U 在环境中的相对部署和密度，这些不同的机制导致它们的性能截然不同。在这项工作中，我们提出了一个分析模型，用于表征具有下行链路流行流量的空间分布式场景中 Wi-Fi 和 LTE-U 网络的可实现吞吐量。所提出的模型用于研究 LTE-U 和 Wi-Fi 在空间分布场景中如何相互共存。我们广泛的仿真结果表明，它是一个可靠的模型，可用于在空间分布式部署中估算 Wi-Fi 和 LTE-U 的吞吐量。各种网络参数（例如能量检测和载波侦听阈值）对 Wi-Fi 和 LTE-U 共存的影响作为副产品进行了探索，并通过 National Instrument 实验测试台得到了证实。我们的模型在吞吐量估计方面提供了非常高的准确度，对于 80 个节点的场景，其中 50% 的节点属于 Wi-Fi 和 LTE-U 网络，平均归一化误差小于 3%。该分析模型还用于进行 LTE-U 和 Wi-Fi 的共存研究。各种网络参数（例如能量检测和载波侦听阈值）对 Wi-Fi 和 LTE-U 共存的影响作为副产品进行了探索，并通过 National Instrument 实验测试台得到了证实。我们的模型在吞吐量估计方面提供了非常高的准确度，对于 80 个节点的场景，其中 50% 的节点属于 Wi-Fi 和 LTE-U 网络，平均归一化误差小于 3%。该分析模型还用于进行 LTE-U 和 Wi-Fi 的共存研究。各种网络参数（例如能量检测和载波侦听阈值）对 Wi-Fi 和 LTE-U 共存的影响作为副产品进行了探索，并通过 National Instrument 实验测试台得到了证实。我们的模型在吞吐量估计方面提供了非常高的准确度，对于 80 个节点的场景，其中 50% 的节点属于 Wi-Fi 和 LTE-U 网络，平均归一化误差小于 3%。该分析模型还用于进行 LTE-U 和 Wi-Fi 的共存研究。