Software Defined Radio Platform for Cross RF/PHY/Network/Application Layer Study in Cloud Random Access Networks

到2016年，移动连接速度将提高9倍，智能手机总流量将是目前的50倍，移动视频将增加25倍[思科全球移动数据流量预测]。作为回应，无线网络一直在不断发展，以更低的成本支持更高的数据速率和更广的覆盖范围。无线连接的瓶颈是频谱，这是一种稀缺的自然资源，除了价格上涨外，还受到自然的硬限制。例如，在国家一级，2014年1月，加拿大拍卖了68兆赫的超高频(UHF)频谱，产生的总价值为52.7亿美元。问题是，无论金额多少，整个可用的频谱都已经被利用，而且在大多数地区都过于拥挤。在无线演进的这个阶段，清楚的是，唯一可行的选择是基于使用较小的小区，这些小区协同工作并实现一个频率的重复使用，而不会引起彼此太多干扰。为了跟上实施许多这样的小型蜂窝的成本，“云无线电接入网络(CRAN)”被用作共享资源的机制。在传统的同构网络中，每个基站直接服务于其附近的客户。为了增加容量和覆盖范围，未来的无线网络将具有不同的体系结构，其中高功率宏基站和小区中的一些低功率节点，特别是带有远程无线电头部的分布式天线系统，共同为客户服务。这是无线网络在未来许多年将遵循的道路。然而，要实现具有成本效益的解决方案，需要解决一些问题。其中一个主要的瓶颈是无线头部与中心节点的连接。要研究CRAN实施中的实际权衡，唯一可能的方法是在现实生活中用户的负载网络上实施一个现实的平台。所要求的可编程网络基础设施安装在UWaterloo网络的顶部，将提供一个现实的环境，以研究和优化实际负载下的CRAN性能。这反过来又可以避免在昂贵的部署之后出现意想不到的意外。

By 2016, mobile connection speeds will increase 9-fold, aggregated smartphone traffic will be 50 times greater than it is today, and mobile video will increase 25-fold [Cisco Global Mobile Data Traffic Forecast]. In response, wireless networks have been constantly evolving to support higher data rates and wider coverage, at a lower cost. The bottleneck in wireless connectivity is the spectrum, a scarce natural resource that in addition to its rising price, has a hard limit imposed by nature. As an example at the national level, in January 2014, an auction for 68 MHz of Ultra High Frequency (UHF) spectrum was held in Canada, generating a total value of $5.27b. The problem is that, regardless of the dollar amount, the entire usable spectrum is already exploited and in most parts is overcrowded. It is clear at this stage of the wireless evolution that the only viable option is based on using smaller cells, which act cooperatively and realize a frequency reuse of one without causing too much interference to each other. To keep up with the cost of implementing many such small cells, 'Cloud Radio Access Networks (CRAN)' are pursued as a mechanism to share resources. In conventional homogeneous networks, each base-station directly serves the clients in its neighborhood. To increase capacity and coverage, future wireless networks will have a heterogeneous architecture, in which a high power macro base-station along with some low-power nodes across its cell, in particular distributed-antenna-systems with remote radio heads, collectively serve clients. This is the path wireless networks will follow for many years to come. However, to realize cost effective solution, a number of issues need to be addressed. One of the main bottlenecks is the connection of radio head to central node. The only possible way to study the actual tradeoffs in the implementation of CRAN is a realistic platform implemented on top of a loaded network of real-life users. The requested programmable network infrastructure, installed on top of the uWaterloo network, will provide a realistic environment to study and optimize CRAN performance under realistic loads. This in turn will allow avoiding unexpected surprises after costly deployments.