In an airborne network there may only be a limited window of opportunity for a fighter jet or even a soldier on the ground to participate in a communication network. Any loss of connection during this limited transmission window due channel fluxuations is therefore extremely costly. In this project we propose a multi-resolution system base on superposition coding that will avoid these communication outages without having to sacrifice link capacity. The idea is to set different levels of priorities for different frames of data, and exploit multi-resolution coding/modulation techniques to protect these different pieces at different levels. When the channel conditions deteriorate only the highest priority data is transmitted successfully, while if the channel conditions improve other lower priority information is also received. We consider the important case of no feedback on the channel conditions to the transmitter, hence we do not adopt solutions based on adaptive coding/modulation schemes. This proposed multi-resolution coding scheme creates new challenges for higher layer networking protocols. Since the physical layer itself will offer multiple levels of service. An additional goal of this research is to develop and modify higher layer networking protocols to best utilize an underlying physical layer with multiple levels of service.
Benefit: Leaf Networks has been delivering commercial award-winning software products for the last two years. Our software has received recognition from PC Magazine, Network World and PC World and sold several networking and multimedia products, including its patent pending virtual network software and its high-definition video conferencing product. The company and its founders have a history commercializing university research into products. Prior to Leaf Networks, in 1999 the founders launch Aligo, raised $24 M from Silicon Valley venture capitalists to commercialize their wireless research. The technology was transitioned into enterprise products and generated over $4 M annually and was licensed by Sun Micro Systems and Motorola. Currently, the founders of Leaf Networks have taken more recent patent pending ideas and converted it into consumer products which have been licensed by NETGEAR. Leaf Networks is run by Dr. Jeffrey Capone who was a former professor of Electrical Engineering as Arizona State University. Dr. Capone has a history of commercializing university research though understanding commercial potential, forming companies and raising capital. Leaf Networks sees many military and commercial application of the proposed technology. Some examples include airborne networks where a fighter jet may fly past the network and want to quickly upload or download large amounts of tactical data. Commercial applications include emergency response applications where high definition imagery can be requested over low bandwidth wide area wireless networks and downloaded or uploaded when connected to a pocket of high bandwidth. These pockets of high bandwidth may be available in a traffic intersection or on locations on highways. In either case, there is only a window of opportunity to download time critical data and any loss of connectivity due to varying SNR is extremely costly. The benefits of this technology include more reliable military communications in such settings as airborne networks, new networks for requesting and receiving data for emergency response systems and even consumer-oriented entertainment applications for downloading large quantities of data during limited connection to pockets of high bandwidth. Our goal for Phase I is to prove out these concepts and verify services provided by this technology through simulation models that will be carried out using OPNET simulation tool. These models will help us develop a firm understanding of the technologies and it capabilities for certain environments. Using this information, we would plan on apply for Phase II research grants and in parallel look for private funding to develop the commercial side of the technology.
Keywords: Airborne Networks, Cliff-Effect, Mimo, Multi-Resolution Coding/Modulation, Superposition Signaling, Superposition Coding, Diffserv
