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型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式，包括（但不限于）fog-RAN，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。根据未来的5G模式，该研究的重点是大规模部署小基站的网络，并允许在本地缓存中存储有限的内容集。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/或远程无线电头端被随机部署，通常遵循齐次泊松分布，使得可以应用完善的随机几何理论。然而，由于城市物理阻抗（例如建筑物、道路或步行路面模式），更有可能经历空间非均匀的内容请求生成。因此，我们的工作集中在寻找最佳的网络设置方面的空间部署和内容缓存的概率模型的小细胞。作为我们研究的结果，我们将能够增加成功的内容交付概率，节省能源（通过触发一些接入点的空闲状态）和减轻整个网络的干扰饱和（由于节点的大规模部署）。因此，这项研究是对未来5G移动的网络中大规模部署传输节点的限制的调查，而不是普遍认为的在整个网络中显着增加小小区数量的观点。这项研究将提供有价值的洞察网络的缩放规律在不同的通信技术和优雅的量化之间的权衡多样性和干扰的网络密度的增加。与EPSRC专题领域的相关性：“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".