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.
