Coded Caching and Interference Management for Future Wireless Networks

物联网(IOT)将把现实世界的数据转化为数字内容和服务，将所有可以连接的东西连接在一起，演变为万物互联。汽车、红绿灯、停车计时器、无人机、游戏机、家用电器、传感器等比人多得多。虽然以人为中心的网络的“指数”增长必然会在与世界人口成正比的水平上饱和，即数十亿，但5G网络中的节点数量将增长超过万亿。物联网设备的数量已经超过了世界人口，并将在2020年初达到地球人口的20倍。S说。这种令人眼花缭乱的增长伴随着相当大的挑战和机遇。虽然物体密度的增加会造成巨大的干扰，但在小范围内使用许多设备可以通过协作通信实现资源共享。在智能设备存储容量快速增长的情况下，协作缓存可以提供高质量的数据传输，而不会对回程容量或移动设备的功率提出过高的要求。智能设备可以使用设备到设备(D2D)通信共享存储的流行内容，而无需通过基础设施进行路由。将对象分为内容帮助者(CH)和内容请求者(CR)，两者之间的关系可以看作是一个二部匹配问题，并利用匹配理论进行求解。由于具有移动性和不同的优先级，CH可能并不总是准备好帮助给定的CR。使用擦除校正码可以避免由于CH不可用而导致的内容丢失。在协作缓存中，主要的限制是：速率、存储和复杂性。我们将找到三者之间的最佳折衷，并针对各种计算限制开发速率内存折衷方案。我们还将开发使用无码率代码的新的健壮缓存方案，以实现高效的内容放置和恢复。D2D业务的快速增长将使频谱饱和，因此需要使用非正交多址(NOMA)。我们将开发新的码域NOMA多址接入、编码和干扰消除方案。大多数智能设备都配备了可用于形成多个波束的多个天线。这允许使用干扰对齐(IA)来增加5G中D2D通信的容量。通过使用博弈论的方法，我们将为D2D应用程序开发新的IA方案。在5G中使用超密集网络(UDN)将导致严重的小区间干扰，将需要复杂的干扰消除技术。为了降低设备复杂性，可在连接到云的基带单元(BBU)执行复杂功能的情况下使用云无线电接入网络(C-RAN)。BBU上的内容缓存可以减少回程前程流量。我们的研究将包括：用于D2D通信的协作编码缓存，用于5G网络的协作NOMA，用于D2D通信的IA，以及用于C-RAN的内容缓存。

Transforming physical world data into digital content and services, Internet of Things (IOT) will connect together all things that can be connected evolving into the Internet of Everything. There are far more cars, traffic lights, parking meters, drones, game consoles, appliances, sensors etc. than people. While the "exponential" growth of human-centric networks is bound to saturate at a level proportional to the world population, i.e., several billions the number of nodes in 5G networks will grow beyond trillions. The number of IOT devices has already exceeded world population and will reach 20 times earth's population in early 2020's. This dizzying growth comes with considerable challenges and opportunities. While the increase in objects' density causes huge interference, the availability of many devices in a small area allows resource sharing through cooperative communications. Given the rapid growth of storage capacity of smart devices, cooperative caching can provide high quality data transmission without undue demand on the backhaul capacity or mobile device's power. Smart devices can share stored popular contents using Device to Device (D2D) communications without routing through the infra-structure. The objects will be divided into Content Helpers (CH) and Content Requesters (CR) whose relationship can be viewed as a bi-partite matching problem and solved using matching theory. Being mobile and having different priorities, a CH may not be always ready to help a given CR. Content loss due to CH unavailability may be avoided using erasure correcting codes. In cooperative caching the main constraints are: rate, storage and complexity. We will find the best trade-off between the three and develop rate-memory trade-offs for various computational constraints. We will also develop novel robust caching schemes using rateless codes for efficient content placement and recovery. The rapid growth of the D2D traffic will saturate the spectrum necessitating the use of non-orthogonal multiple access (NOMA). We will develop novel multiple access, coding and interference cancellation schemes for code domain NOMA. Most smart devices are equipped with multiple antennas that can be used for forming a multitude of beams. This allows the use of Interference Alignment (IA) for increasing the capacity of D2D communication in 5G.  Using a game theoretic approach, we will develop novel IA schemes for D2D applications. Use of Ultra Dense Networks (UDNs) in 5G will result in drastic inter-cell interference and complex interference cancellation techniques will be needed. To reduce device complexity, Cloud Radio Access Network (C-RAN) can be used where complex functions are performed at Baseband Units (BBUs) connected to the cloud. Content caching at BBUs can reduce the back-haul-front-haul traffic. Our research will include: Cooperative coded caching for D2D Communications, Cooperative NOMA for 5G Networks, IA for D2D communications, and content caching for C-RAN.