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

到2016年，移动连接速度将增长9倍，智能手机总流量将是现在的50倍，移动视频将增长25倍（思科全球移动数据流量预测）。因此，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泛的覆盖范围。无线连接的瓶颈是频谱，这是一种稀缺的自然资源，除了价格不断上涨外，它还受到自然的严格限制。以国家层面为例，2014年1月，加拿大举行了68兆赫特高频（UHF）频谱的拍卖，总价值为52.7亿美元。问题是，不管多少钱，整个可用的频谱都已经被开发了，而且在大部分地区都过于拥挤。很明显，在无线发展的这个阶段，唯一可行的选择是基于使用更小的蜂窝，这些蜂窝协同工作，实现一个蜂窝的频率重用，而不会对彼此造成太多干扰。为了跟上实施许多这样的小蜂窝的成本，“云无线接入网络（CRAN）”被追求作为一种共享资源的机制。在传统的同构网络中，每个基站直接为其附近的客户提供服务。为了增加容量和覆盖范围，未来的无线网络将采用异构架构，在这种架构中，一个高功率的宏基站及其小区中的一些低功率节点，特别是带有远程无线电头的分布式天线系统，共同为客户服务。这是无线网络在未来许多年将遵循的路径。然而，要实现具有成本效益的解决方案，需要解决许多问题。其中一个主要的瓶颈是无线电头到中心节点的连接。研究CRAN实现中实际权衡的唯一可能方法是在真实用户的负载网络上实现一个现实的平台。所要求的可编程网络基础设施安装在uWaterloo网络之上，将提供一个真实的环境来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外情况。

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.