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，并转向更多地使用基于规则的无许可证策略。 在这种情况下，人们正在关注认知无线电，它在机会主义的基础上使用频谱。研究人员研究了通过认知无线电信道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带的主要用户的信号造成多大的干扰。 调查涉及到设计特定的压缩算法，视频传输在一个机会性使用的信道，并确定端到端的性能方面的视频quality.The认知无线电的目标是增加频谱分配的频谱频带的频谱效率，机会性地利用频谱是暂时免费的流量。 这是通过感测信道并适配发射波形的参数（诸如调制格式、功率、带宽、频率位置和码率）来实现的。 本研究采用跨层的方法，涉及物理层波形设计、接收机设计和信道状态信息，以及应用层考虑，如可伸缩视频编码、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，延迟约束需要在诸如交织器大小和源编码器输出缓冲器大小的系统组件之间进行权衡。研究的主要课题是：（a）自适应接收机的设计和性能分析的认知无线电移动的信道上的视频传输，（B）可扩展的视频编码的认知无线电环境的优化设计，和（c）最佳的延迟预算分配。

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.