车载支持蜂窝网络中的部署规划

Nadav Lavi, Eliran Sherzer, H. Levy
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引用次数: 0

摘要

我们考虑一个独特的蜂窝模型的规划问题,其中停放的车辆,称为车辆中继节点(VeRNs),通过向用户和从用户中继数据来协助网络。vn可以降低蜂窝网络负载,并为数据需求的爆炸性增长提供可扩展的解决方案。VeRN模型提出了一种新的范例,与目前仅基于固定基础设施的蜂窝部署有很大不同。因此,已知的部署规划方法不适用。复杂性来自于车辆的使用,它将随机资源变量添加到随机数据需求变量中,以及部署结构/拓扑和固定资源,随机资源和用户需求之间的成本权衡。我们为这个独特的部署计划问题提供了一个整体的解决方案。我们的解决方案基于三种方法的结合,这使我们能够建立问题的凸性,从而建立问题的贪婪属性。这允许将分析集中在推导边际值上,而不是对整个系统进行分析。我们进一步提出了一种近似有效状态空间边界支持的边缘值的方法。数值结果表明,该方法是有效的,并能处理各种分布设置。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Deployment Planning in Vehicular Supported Cellular Networks
We consider the planning problem of a unique cellular model in which parked vehicles, termed Vehicular Relay Nodes (VeRNs), assist the network by relaying data to and from users. VeRNs can lower cellular network load and provide a scalable solution to the explosive growth in data demand. The VeRN model presents a new paradigm that significantly differs from toady's cellular deployments that are based solely on fixed infrastructure. Consequently, known deployment planning methods are inapplicable. The complexity arises from utilizing vehicles which adds stochastic resource variables to the stochastic data demand variables, as well as from the deployment structure/topology and the cost trade-offs between fixed resources, stochastic resources, and user demand. We present a holistic solution for this unique deployment planning problem. Our solution is based on the combination of three methodologies, which enables us establishing the convexity, and thus greediness properties of the problem. This allows focusing the analysis on deriving marginal values, instead of full system analysis. We further propose an approach to approximate the marginal values supported by effective state space bounds. Numerical results show that the method is efficient, and addresses various distribution settings.
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