VANET传输序列重构与分配

Li Cai, Zhexin Xu, Yi Wu, Xiao Lin
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引用次数: 1

摘要

本文研究了车载自组网(VANET)中无反馈寻址媒体访问控制(MAC)的重构和分配传输序列。基于全球导航卫星系统(GNSS)的代码分配是一个很好的解决方案。它将要覆盖的地理区域镶嵌成正六边形量化单元。所有用户都可以通过GNSS在标记的时间实例访问他们的位置信息。传输序列预先分配给定位单元,然后动态分配给用户。它还提出了类似于频率重用的序列重用的概念。基于gnss的代码分配的缺点是平均用户吞吐量(AUT)相对较低。提出了基于gnss编码分配的传输序列重构与分配(TSRA)方法。首先,在每个超帧T中,每个用户根据第一周期基于gnss的机制获取用户不可抑制性(UI)序列,以获取同一小区簇中邻居的信息;不同方向的用户分别使用超框架T的一半。其次,用户根据同一单元簇中邻居的数量重构一组UI序列。然后,根据用户在第一个周期内第一次成功“1”的顺序,获得重构序列。将TSRA的性能与ns-2基于gnss的代码分配进行了比较,并利用城市交通仿真(SUMO)的车辆移动数据进行了比较。仿真结果表明,在相对稀疏的分布式网络中,TSRA的自动码分配优于基于gnss的自动码分配。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Transmission sequence reconstruction and allocation for VANET
In this paper, reconstruction and allocation transmission sequences are investigated for addressing media access control (MAC) without feedback in Vehicular Ad-hoc Network (VANET). Global Navigation Satellite Systems (GNSS) based code allocation is a great solution. It tessellates the geographic region to be covered into regular hexagonal quantization cell. All users access to their location information at marked time instances through GNSS. The transmission sequences are pre-assigned to the location cells and then dynamically assigned to the users. It also proposed a concept of sequence reuse that is akin to frequency reuse. A drawback of GNSS-based code allocation is the average user throughput (AUT) is relatively low. Transmission sequence reconstruction and allocation (TSRA) based on GNSS-based code allocation is proposed. Firstly, in each superframe T, each user acquires user irrepressibility (UI) sequence according to GNSS-based mechanism in the first period to obtain the information of neighbors in the same cell cluster; users in different direction use half of the superframe T respectively. Secondly, users reconstruct a set of UI sequences according to the number of neighbors in the same cell cluster. Then, users acquire a reconstructed sequence according to the order of the users' first successful “1” in the first period. The performance of TSRA is compared with GNSS-based code allocation by ns-2 with the vehicle mobility data from the Simulation of Urban Mobility (SUMO). The simulation results show that the AUT of TSRA is better than GNSS-based code allocation in a relatively sparser distributed network.
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