Modelling, Analysis and Optimisation of Ultra-Dense Networks in Future Smart Cities

该项目的目标是开发一个基于新的多元统计理论的通用分析框架，可用于研究超密集现代无线通信范例，包括(但不限于)雾范围、大规模分布式天线系统和描述通过网络传播信息的动态系统。按照未来的5G模式，这项研究的重点是一个大规模部署小蜂窝并允许在本地缓存中存储有限内容集的网络。传统上，已经使用了用于分析这种网络的宏观方法，其中用户和/或远程无线电头部被随机部署，通常遵循齐次泊松分布，从而可以应用良好建立的随机几何理论。然而，由于城市物理阻力，例如建筑物、道路或步行人行道模式，更有可能经历空间上不均匀的内容请求生成。因此，我们的工作集中在寻找在空间部署和内容缓存小蜂窝概率模型方面建立的最优网络。作为我们研究的结果，我们将能够增加成功内容交付的概率，节省能源(通过触发某些接入点的空闲状态)，并缓解整个网络的干扰饱和(由于节点的大规模部署)。因此，这项研究是对在未来5G移动网络中大规模部署传输节点的限制的调查，而不是普遍认同的显著增加网络中小蜂窝数量的观点。这项研究将对不同通信技术下的网络伸缩规律提供有价值的见解，并优雅地量化随着网络密度的增加而在分集和干扰之间的权衡。与EPSRC专题领域相关：“射频和微波通信”、“数字信号处理”、“人工智能技术”、“未来智能技术”。

The objective of the project is to develop a generalised analytical framework based on novel multivariate statistical theory that can be used to study ultra-dense modern wireless communication paradigms, including (but not limited to) fog-RAN, large-scale distributed antenna systems and dynamical systems that describe information propagation through networks. Following future 5G paradigms, the study is focused on a network where small-cells are massively deployed and are allowed to store a limited set of contents in a local cache. Traditionally, a macroscopic approach for analysing such networks have been used wherein the users and/or remote radio heads are randomly deployed, often following a homogeneous Poisson distribution such that well established stochastic geometry theory can be applied. However, it is more likely to experience spatially non-homogeneous content requests generation due to urban physical impendence such as building, road or walking pavement pattern. Our work is focused therefore on finding the best network set up in terms spatial deployment and content caching probabilistic model of small-cells. As result of our study, we will be able to both increase the success content delivery probability, saving energy (by triggering an idle state for some access points) and alleviating the interference saturation of the whole network (due to a massive deployment of nodes). The study stands therefore as an investigation of the limits in massively deploying transmitting nodes in future 5G mobile networks, against the generally shared view of remarkably increase the number of small cells across a network. This study will provide valuable insight on the network scaling laws under different communication technologies and elegantly quantify the trade-off between diversity and interference as the network density increases. Relevance to EPSRC thematic areas: "RF and microwave communications", "Digital signal processing", "Artificial intelligence technologies", "Future Intelligent Technologies".