WiFiUS: Ubiquitous Video over Dynamic Spectrum

手机和平板电脑是当今使用最广泛的无线通信设备。视频已经占据了移动流量的大部分，预计在未来几年将显着增长。尽管有更新的蜂窝通信技术，但网络运营商已经面临带宽短缺的问题，无法支持如此庞大的流量。认知无线电网络（CRN）提供了一种提高无线通信技术的可用性和效率的解决方案。在自适应通信协议的支持下，CRN 能够感知大范围的频谱，并且能够灵活地动态利用可用资源。因此，他们可以回收未使用的频谱（即空白空间）用于无线通信，同时避免授权用户和未授权用户之间的干扰。然而，通过 CRN 进行视频传输带来了一些挑战，这些挑战涉及信道的高度变化性质、行为不端的用户的存在以及异构资源的动态可用性。该项目解决了这些挑战，并使 CRN 适合作为提供无处不在的无线视频的平台。该研究采用灵活的方法，适用于跨国界的各种法规，并且专门针对移动设备。它有助于创建认知电话，即具有认知无线电功能的智能手机，以弥合 CRN 背后的技术与实际应用之间的差距。该项目建立在两个主要研究方向之上。首先，它采用频谱人群感知作为对多个尺度的空白可用性进行建模并支持长期通信的手段。这种方法使新颖的解决方案能够准确地表征信道并执行通信当局制定的策略。其次，它利用自适应机制作为基础，有效地将视频流传输给最终用户。这些机制是通过网络基础设施中的流协议和组件来实现的，这些协议和组件提供具有目标体验质量的视频内容。该项目还整合了美国和芬兰在教育、行业合作和创业方面的协同活动。

Mobile phones and tablets are the most widely-used wireless communication devices nowadays. Video already represents the majority of mobile traffic and is expected to grow significantly in the coming years. Network operators are already facing shortage of bandwidth to support such a huge amount of traffic, despite the availability of newer cellular communication technologies. A solution to increase the availability and the efficiency of wireless communication technologies is given by cognitive radio networks (CRNs). Enabled by adaptive communication protocols, CRNs have the capability to sense a wide range of the spectrum and the agility to make use of the available resources dynamically. Accordingly, they can reclaim unused spectrum (i.e., whitespace) for wireless communications while avoiding interferences with between licensed and unlicensed users. However, video delivery over CRNs presents several challenges related to the highly-varying nature of the channel, the presence of misbehaving users, and the dynamic availability of heterogeneous resources.This project addresses such challenges and makes CRNs suitable as a platform to provide ubiquitous wireless video. The research takes a flexible approach that is applicable to diverse regulations across national boundaries and specifically targets mobile devices. It helps create a cognitive phone, i.e., a smartphone with cognitive radio capabilities, to bridge the gap between the technologies behind CRNs and real applications. The project builds on two major research thrusts. First, it adopts spectrum crowd-sensing as a means to model the availability of whitespace at multiple scales and support long-lived communications. Such an approach enables novel solutions to accurately characterize the channel and enforce the policies established by the communication authorities. Second, it leverages adaptive mechanisms as foundations to efficiently deliver video streams to end users. These mechanisms are implemented through streaming protocols and components in the network infrastructure that provide video content with a target quality of experience. The project also integrates synergistic activities between the United States and Finland in education, industry collaboration, and entrepreneurship.