WiFiUS: Ubiquitous Video over Dynamic Spectrum

WiFiUS：动态频谱上无处不在的视频

• 批准号: 1759655
• 负责人: Mung Chiang
• 金额: $ 9.96万
• 依托单位: Purdue University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-07-01 至 2018-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1759655&HistoricalAwards=false
• 关键词: WiFiUS; Ubiquitous; Video; over; Dynamic

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.

手机和平板电脑是当今使用最广泛的无线通信设备。视频已经代表了移动流量的大部分，预计在未来几年将大幅增长。尽管有了更新的蜂窝通信技术，但网络运营商已经面临着带宽短缺的问题，无法支持如此巨大的流量。认知无线电网络(CRN)为提高无线通信技术的可用性和效率提供了一种解决方案。在自适应通信协议的支持下，CRN具有感知大范围频谱的能力和动态利用可用资源的灵活性。因此，他们可以回收未使用的频谱(即空白)用于无线通信，同时避免与授权和非授权用户之间的干扰。然而，CRN上的视频传输面临着一些挑战，涉及到信道的高度多变性、行为不端用户的存在以及异质资源的动态可用性。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。这项研究采取了一种灵活的方法，适用于跨越国界的不同法规，并专门针对移动设备。它有助于创造一种认知手机，即具有认知无线电功能的智能手机，以弥合CRN背后的技术和实际应用之间的差距。该项目建立在两个主要研究项目的基础上。首先，它采用频谱人群感知作为一种手段，在多个尺度上对空白的可用性进行建模，并支持长期通信。这种方法使新的解决方案能够准确地描述通道的特征，并执行由通信当局制定的策略。其次，它利用自适应机制作为基础，高效地向最终用户提供视频流。这些机制是通过网络基础设施中的流协议和组件实现的，这些协议和组件为视频内容提供目标质量的体验。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。