基于随机线性网络编码的双向通道V2V网络中的高效通信。

IF 2.1 3区 物理与天体物理 Q2 PHYSICS, MULTIDISCIPLINARY Entropy Pub Date : 2023-10-17 DOI:10.3390/e25101454
Yiqian Zhang, Tiantian Zhu, Congduan Li
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引用次数: 0

摘要

车对车(V2V)通信在智能交通系统领域得到了极大的关注。在本文中,我们关注的是车辆在同一方向和相反方向上行驶的通信场景。具体而言,我们将V2V网络建模为具有双向通道的动态多源单汇网络。为了解决网络拓扑的快速变化,我们采用了随机线性网络编码(RLNC),这消除了对网络拓扑知识的需求。我们从推导生成概率的下限开始。通过仿真,我们分析了在不同丢包率和批量大小下延迟的概率分布和累积概率分布。我们的结果表明,与非编码情况相比,即使在具有挑战性的信道条件下,我们的RLNC方案也显著降低了通信延迟。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Efficient Communications in V2V Networks with Two-Way Lanes Based on Random Linear Network Coding.
Vehicle-to-vehicle (V2V) communication has gained significant attention in the field of intelligent transportation systems. In this paper, we focus on communication scenarios involving vehicles moving in the same and opposite directions. Specifically, we model a V2V network as a dynamic multi-source single-sink network with two-way lanes. To address rapid changes in network topology, we employ random linear network coding (RLNC), which eliminates the need for knowledge of the network topology. We begin by deriving the lower bound for the generation probability. Through simulations, we analyzed the probability distribution and cumulative probability distribution of latency under varying packet loss rates and batch sizes. Our results demonstrated that our RLNC scheme significantly reduced the communication latency, even under challenging channel conditions, when compared to the non-coding case.
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来源期刊
Entropy
Entropy PHYSICS, MULTIDISCIPLINARY-
CiteScore
4.90
自引率
11.10%
发文量
1580
审稿时长
21.05 days
期刊介绍: Entropy (ISSN 1099-4300), an international and interdisciplinary journal of entropy and information studies, publishes reviews, regular research papers and short notes. Our aim is to encourage scientists to publish as much as possible their theoretical and experimental details. There is no restriction on the length of the papers. If there are computation and the experiment, the details must be provided so that the results can be reproduced.
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