Dr. Hongbin Li of the Department of Electrical and Computer Engineering was awarded the Jack Neubauer Memorial Award at the 2013 IEEE 78th Vehicular Technology Conference held in Las Vegas, Nevada. The award, which is sponsored by Panasonic, granted by the IEEE Foundation and administrated by the IEEE Vehicular Technology Society, acknowledges the best paper of the year published by the Society on the subject of Vehicular Technology Systems and recognizes the valuable contribution of the work to the furtherance of the Society's interests in mobile communications, automotive, and land transportation electronics technology. Dr. Li, along with a group of postdoctoral and graduate students that includes Pu Wang, Jun Fan and Ning Han, were honored for their paper titled "Multiantenna-Assisted Spectrum Sensing for Cognitive Radio," published in IEEE Transactions on Vehicular Technology, vol. 59, no. 4, pp. 1791-1800, May 2010. The award-winning paper describes the use of multiple antennas to detect a primary user in a cognitive radio network.
“With mobile internet usage poised to overtake wired connections by 2014, billions of dollars in commercial interests are dependent on sufficient allocation of wireless spectrum,” says Dr. Michael Bruno, Dean of the Charles V. Schaefer, Jr. School of Engineering and Science. “More flexible and efficient management of the spectrum has become an urgent research initiative, and this award recognizes Dr. Li’s leadership at the forefront of efforts to develop this critical national resource.”
Wireless networks have evolved dramatically in recent years driven by increasing needs of consumers. Mobile devices, television, radio, and GPS depend on access to dedicated radio frequency, and users of each can operate only on a certain portion of the wireless spectrum. This has made the wireless spectrum increasingly scarce and precious, although only a small portion of it is used in the U.S. at any given time/location. Researchers have therefore devised the concept of opportunistic spectrum access to allow secondary users to share spectrum with licensed (primary) users without causing harmful interference. An implementation of this idea called cognitive radio (CR) scans wireless spectrum dynamically for the clearest bands and switches seamlessly, establishing intelligent and efficient utilization of radio spectrum while deterring abuse and malicious attacks.
The researchers considered the problem of rapid detection of a moving primary user in a cognitive radio network by employing multiple antennas at the cognitive receiver. In vehicular applications, cognitive radios will move through areas with differing densities of primary users. In such cases, high-speed detection based on a small number of samples is particularly advantageous. It can be difficult, however, to distinguish a node without information about the environment. Multiple-antenna observation allows the specification of a threshold for making that distinction more reliably. Dr. Li and his researchers developed a generalized likelihood ratio test (GLRT) to detect the presence/absence of a primary user and compared their test to existing methods, such as the energy detector (ED) and several “eigenvalue”-based methods. They were able to demonstrate that GLRT performs better than other existing techniques, particularly when the number of samples is small.
According to Dr. Yu-Dong Yao, Director of the Department of Electrical and Computer Engineering, “Dr. Li’s work promises to significantly advance spectrum sensing for cognitive radio in vehicular applications. This well merited recognition by the IEEE is indicative of the implications of their work in the greater effort to establish cognitive radio technologies that are expected to have significant economic and social impact.”
Dr. Hongbin Li’s research encompasses the fields of Signal Processing and Wireless Communications and Networking. He has received an NSF grant titled “Data-Driven Adaptive Quantization for Distributed Inference,” addresses a fundamental challenge of quantization for distributed inference in a sensor network environment, where the optimum quantizer generally cannot be implemented due to its dependence on unknown parameters associated with the random events being monitored by the sensor network. The research being conducted by Dr. Li has the potential to solve several important distributed inference problems with bandwidth and power constraints, further advancing research and development of wireless sensor networks.
About Electrical and Computer Engineering
Stevens Department of Electrical and Computer Engineering is home to a distinguished faculty conducting research on cutting edge hardware and software, supporting new horizons in wireless and multimedia networking, cognitive radio, and signal processing. Complementary instructional and hands-on lab facilities facilitate thorough theoretical and applied learning experiences at both the undergraduate and graduate levels. Funded research on campus and active partnerships between departments and regional institutions provide students with rich opportunities to explore problems on the horizon in electronic and data technologies.
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