Modelling, Analysis, and Design of Ultra-Dense Cellular Networks

无线通信技术使我们能够无缝地访问许多多媒体服务，例如，存储的多媒体（例如，视频点播），直播流（例如，互联网直播体育网络、互联网广播电台）和实时交互流媒体（例如，在线游戏、视频会议、电子教育）等。因此，无线通信技术已经迅速地获得了至关重要的作用并且成为生活的重要方面。有一个强有力的，可信的证据表明，移动的网络运营商正面临着许多艰巨的任务，但令人兴奋的努力领域。最令人关注的是不断增长的无线/移动的设备的增加以及与此相关联的数据速率的巨大需求。据预测，到2019年，移动连接设备数量将超过115亿台（人均近1.5台移动的设备），这对无处不在的通信提出了巨大的流量需求。一方面，预计到2030年，无线数据流量将增长10000倍，仅英国的无线数据流量预计将在2012 - 2030年期间增长23倍至297倍。未来的5G蜂窝网络预计将达到目前4G网络的1000倍数据速率。一方面，到2020年将有多达500亿台设备连接到互联网，要求无缝连接和移动性。数据速率预计每五年将增加十倍，并且随着新兴的物联网（IoT）预计将无线连接地球仪上的数万亿设备，如果没有新的方法，未来的移动的网络（5G）将陷入停顿，除非创造更多的容量。最有吸引力的解决方案之一是实现由宏小区和小小区组合构成的超密集网络，并利用毫米波（mm波）频带、大规模天线阵列等新兴技术。但是，虽然这些使能技术构成了最有吸引力的方法之一，即，在超密集蜂窝网络中，为了提高无线系统的容量和覆盖范围，"超密集"方面提出了根本性的挑战，迫切需要解决方案，最重要的是，系统级性能评估和优化工具对于电信服务提供商来说是非常必要的。然而，它通常是依靠数值模拟来进行的，这在5G超密集网络的背景下通常是耗时的，甚至是极其困难的。目前，还没有一个合理但必要的数学方法来设计超密集异构蜂窝网络的实际通信协议和传输技术。由于缺乏易于处理的解决方案，本研究项目提出了一个数学模型，以考虑5G超密集网络的实际方面，即，高密度分布、动态随机拓扑和异构干扰。该项目的独特之处在于增强了超密集蜂窝网络中基站和移动的设备所涉及的数学、随机过程和信号处理理论的最新进展，以恢复传输的语音、数据、视频、这允许我们集成大小小区之间的干扰管理以及大量发射/接收天线和以mm为单位的更高传输带宽，沿着。波频带这些包括新的理论框架的发展，这是由一个实际的系统，目前没有考虑在当前的蜂窝系统的“极其密集的网络”的背景下的限制通知。

Wireless communications technology enables us to seamlessly access many multimedia services, e.g., stored multimedia (e.g., video on-demand), live streaming (e.g., Internet live sport networks, Internet radio stations), and realtime interactive streaming (e.g., online games, video conference, e-education), etc. As such, wireless communications technology has rapidly gained a crucial role and become an important aspect of life. There is a strong, credible body of evidence, suggesting that mobile network operators are facing many formidable tasks but exciting areas of endeavour. Of most concern is the increase in ever-growing wireless/mobile devices and the huge demand in data rates associated with this. It is predicted that the number of mobile-connected devices will exceed 11.5 billion by 2019 (nearly 1.5 mobile devices per capita), which poses a huge traffic demand for ubiquitous communications. On the one hand, it is anticipated that we will witness an up to 10000- fold growth in wireless data traffic by the year 2030, and that of the UK alone is projected to increase between 23-fold and 297-fold over the period 2012-2030. The future 5G cellular network is expected to achieve as much as 1000 times data rate relative to its current 4G counterpart. On the one hand, as many as 50 billion devices will be connected to the Internet by 2020 request seamless connectivity and mobility. Data rates are projected to increase by a factor of ten every five years, and with the emerging Internet of Things (IoT) predicted to wirelessly connect trillions of devices across the globe, without novel approaches, future mobile networks (5G) will grind to a halt unless more capacity is created. One of the most attractive solutions is the implementation of ultra-dense networks constituted by the combination of macro-cells and small-cells and exploited the emerging technologies of millimetre wave (mm-wave) frequency bands, large-scale antennas arrays. But while these enabling technologies constitute one of the most attractive approaches, i.e., ultra-dense cellular networks, to improving the capacity and coverage of wireless systems, the "ultra-dense" aspect poses fundamental challenges, which urgently require solutions.Most importantly, the tool of system-level performance evaluation and optimization is very essential for telecommunication service providers. However, it is usually conducted by relying on numerical simulations, which are often time-consuming and even extremely difficult in the context of 5G ultra-dense networks. At present, no sound but essential mathematical methodologies towards the design of practical communication protocols and transmission techniques for ultra-dense heterogeneous cellular networks are available.Motivated by this lack of tractable solution, this research project proposes a mathematical model to take into account the practical aspects of 5G ultra-dense networks, i.e., highly dense distribution, dynamic random topologies, and heterogeneous interference. The unique feature of the project is to augment the recent advances in mathematics, random process, and signal processing theory involved by both base stations and mobile devices in ultra-dense cellular networks for recovering the transmitted voice, data, video, etc. This allows us to integrate interference management between large and small cells along with a large number of transmit/receive antennas and higher transmission bandwidth in mm-wave frequency bands. These include the development of new theoretical framework that is informed by the limitations of a practical system not currently considered in the context of "extremely dense networks" of current cellular systems.