Video Coding for Cognitive Radio

为了实现更有效的频谱利用，FCC一直在重新审视传统的基于许可证的政策，并转向更多地使用无许可证、基于规则的策略。在这种情况下，人们关注的是认知无线电，它在机会主义的基础上使用频谱。研究人员研究了在认知无线电信道上传输实时视频的算法的设计和性能评估。由于这项技术涉及共享公共频谱，一个关键问题是，它的部署将对占用该频段的主要用户信号施加多大的干扰。调查涉及设计特定的压缩算法视频传输在一个机会使用的通道，并确定端到端性能的视频质量。认知无线电的目标是通过机会性地利用暂时无业务的频谱来提高分配频谱的频谱效率。这是通过感知信道，并适应发射波形的参数，如调制格式、功率、带宽、频率位置和码率来实现的。本研究采用跨层方法，涉及物理层波形设计、接收器设计和信道状态信息，以及应用层考虑，如可扩展视频编码、多帧预测和端到端失真测量。系统组件消耗带宽和延迟，研究涉及到跨层分配固定的比特预算和/或延迟预算。例如，延迟约束需要在系统组件（如交织器大小和源编码器输出缓冲区大小）之间进行权衡。研究的主要课题有：(a)认知无线电移动信道视频传输的自适应接收机设计和性能分析；(b)认知无线电环境下可扩展视频编码的优化设计；(c)延迟预算的优化分配。

To achieve more efficient spectrum utilization, the FCC has been revisiting traditional license-based policies and moving toward the increased use of unlicensed, rule-based, strategies. In this scenario, attention is being given to cognitive radio, which uses spectrum on an opportunistic basis. The investigators study the design and performance evaluation of algorithms for the transmission of real-time video over cognitive radio channels. Since this technology involves sharing common spectrum, one key question is how much interference its deployment will impose upon the primary users' signals occupying the band. The investigation involves designing specific compression algorithms for video transmission over an opportunistically-used channel, and determining end-to-end performance in terms of video quality.The goal of a cognitive radio is to increase the spectral efficiency of allocated spectral bands by opportunistically making use of spectrum that is temporarily free of traffic. This is accomplished by sensing the channel, and adapting parameters of the transmit waveform such as modulation format, power, bandwidth, frequency location, and code rate. This research takes a cross layer approach, involving physical layer waveform design, receiver design, and channel state information, and application layer considerations, such as scalable video coding, multiple frame prediction, and end-to-end distortion measures.System components consume bandwidth and delay, and the research involves allocating a fixed bit budget and/or delay budget across layers. For example, a delay constraint necessitates tradeoffs between system components such as interleaver size and source encoder output buffer size. The main topics investigated are: (a) Adaptive receiver design and performance analysis for video transmission over cognitive radio mobile channels, (b) Optimal design of scalable video encoding for a cognitive radio environment, and (c) Optimal delay budget allocation.