Project 3-2: Robust Wireless Communications in Complex Environments

Principal Investigators: Arogyaswami Paulraj and George Papanicolaou (Stanford University)
(project duration: 2007-2008)

Effective military wireless communications require robust networks that can operate in complex environments. Links must be reliable, rapid, and multimedia-capable, connecting large, dynamic, mobile networks of users. Such networks must resist hostile jamming and signal “spoofing” while minimizing consumption of electrical power. Designing such communications systems requires the rapid, high-throughput resources provided by high performance computing.

AHPCRC researchers are developing high performance computer simulations for studying time reversal techniques, which can minimize co-channel interference to friendly users. Computer simulations also reduce the time and expense of designing smart antennas that reduce battery drain by transmitting radio energy only in the required direction, while making it more difficult for hostile forces to intercept or transmit unauthorized radio signals.

Technological innovations and knowledge of wireless communications networks gained through this project could be used to advance geolocation, imaging, radar, sonar, and lidar.

In a related effort, AHPCRC sensor technology researchers are developing in-network data aggregation and processing capabilities, with the intention of giving end users rapid access to relevant, applicable data. They have developed an algorithm to locate changes in the sensor environment by adjusting the probing strength of the signals sent by sensors, coupled with a selection of the sensors that have the most relevant information. They are studying small sensor arrays to increase the efficiency of through-wall detection in the microwave regime. High performance computing resources are being developed to provide the demanding numerical simulations needed to validate this application.

Passive microwave sensor networks that extract background information from random noisy sources can be deployed in urban environments. These sensors, which use only the wireless communication traffic as sources, estimate the properties of the background medium and use this information to detect and track changes in the environment.

Compressed sensing relies on the concept that only a small fraction of the available data is needed to recover information such as a localized disturbance in an environment. This concept has the potential to reduce significantly the volume of data needed for effective monitoring using very large sensor networks.

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