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arXiv 2502.09313cs.NI
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智能机器网络中短数据包的延迟性能分析

Delay Performance Analysis with Short Packets in Intelligent Machine Network

Wenyan Xu, Zhiqing Wei, Zhiqun Song, Yixin Zhang, Haotian Liu, Ying Zhou, Xiaoyu Yang, Yashan Pang

AI总结:

针对智能机器(IM)网络时延分析不足的问题,本文结合排队论与随机几何构建模型,推导传输成功概率等三个时延指标并采用有限块长容量刻画短包传输,仿真验证短包及低IM密度对性能的提升作用,为IM网络优化提供理论基础。

摘要:

随着工业制造、车联网和智能物流中时延敏感型业务的快速发展,智能机器(IM)网络面临更严格的时延要求。短数据包传输在IM网络中被广泛采用以降低时延,但IM网络的延迟性能尚未得到充分分析。本文分别应用排队论和随机几何构建下行通信的网络模型和传输模型,提出并推导了三个指标:以时延为阈值的传输成功概率、期望时延和时延抖动。为准确刻画短数据包的传输时延,采用有限块长容量来衡量信道传输速率。仿真结果表明,数据包长度和IM密度的增加会显著恶化这三个指标;短数据包有助于改善这三个指标,尤其是在高IM密度场景下。本文成果为IM网络的优化设计和性能提升提供了重要理论基础。

英文摘要:

With the rapid development of delay-sensitive services happened in industrial manufacturing, Internet of Vehicles, and smart logistics, more stringent delay requirements are put forward for the intelligent machine (IM) network. Short packet transmissions are widely adopted to reduce delay in IM networks. However, the delay performance of an IM network has not been sufficiently analyzed. This paper applies queuing theory and stochastic geometry to construct network model and transmission model for downlink communication, respectively, proposes and derives the following three metrics, e.g., the transmission success probability (with delay as the threshold), expected delay, and delay jitter. To accurately characterize the transmission delay with short packets, the finite blocklength capacity is used to measure the channel transmission rate. Simulation results show that the increase of packet length and IM density significantly deteriorates the three metrics. Short packets are needed to improve the three metrics, especially in high IM density scenarios. The outcomes of this paper provide an important theoretical basis for the optimization design and performance improvement of IM networks.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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