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Cache-Aided Non-Orthogonal Multiple Access for 5G-Enabled Vehicular Networks

机译：支持5G的车载网络的缓存辅助非正交多路访问

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摘要

The increasing demand for rich multimedia services and the emergence of the Internet of Things (IoT) pose challenging requirements for the next-generation vehicular networks. Such challenges are largely related to high spectral efficiency and low latency requirements in the context of massive content delivery and increased connectivity. In this respect, caching and non-orthogonal multiple access (NOMA) paradigms have been recently proposed as potential solutions to effectively address some of these key challenges. In this paper, we introduce cache-aided NOMA as an enabling technology for vehicular networks. In this context, we first consider the full file caching case, where each vehicle caches and requests entire files using the NOMA principle. Without loss of generality, we consider a two-user vehicular network communication scenario under double Nakagami-m fading conditions and propose an optimum power allocation policy. To this end, an optimization problem that maximizes the overall probability of successful decoding of files at each vehicle is formulated and solved. Furthermore, we consider the case of split file caching, where each file is divided into two parts. A joint power allocation optimization problem is formulated, where power allocation across vehicles and cached split files is investigated. The offered analytic results are corroborated by extensive results from computer simulations and interesting insights are developed. Indicatively, it is shown that the proposed caching-aided NOMA outperforms the conventional NOMA technique.
机译：对丰富多媒体服务的需求不断增长，以及物联网（IoT）的出现，对下一代车载网络提出了严峻的要求。在大规模内容交付和增强连接性的背景下，此类挑战很大程度上与高频谱效率和低延迟要求有关。在这方面，最近已经提出了缓存和非正交多址访问（NOMA）范例作为有效解决其中一些关键挑战的潜在解决方案。在本文中，我们介绍了高速缓存辅助的NOMA作为车载网络的启用技术。在这种情况下，我们首先考虑完整文件缓存的情况，其中每辆车都使用NOMA原理缓存并请求整个文件。在不失一般性的前提下，我们考虑了中加倍m衰落条件下的两用户车载网络通信情况，并提出了一种最佳的功率分配策略。为此，提出并解决了使每个车辆上的文件成功解码的总体概率最大化的优化问题。此外，我们考虑了拆分文件缓存的情况，其中每个文件分为两部分。提出了一个联合的功率分配优化问题，其中研究了跨车辆和缓存的拆分文件的功率分配。所提供的分析结果得到了计算机模拟的广泛结果的佐证，并且开发了有趣的见解。指示性地表明，所提出的高速缓存辅助的NOMA优于常规的NOMA技术。

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