Virginia Tech researchers have made great strides in the development of more reliable and efficient spectrum sensing techniques that will be needed to meet the ever-expanding demand for wireless technologies. They are developing cognitive radio technologies (algorithms) that are an integral part of a holistic bandwidth management strategy.
During the first phase of the study, “by exploiting location-dependent signal propagation characteristics, we have developed efficient sensing algorithms that enable a set of devices to work together to determine spectrum opportunities”, said William Headley, of Ringgold, Va., one of the Ph.D. students working on this project.
For the second year of the study, the focus is changing to the design of spectrum sensing algorithms that are robust to both man-made noise and severe multipath fading. “The vast majority of sensing algorithms were developed for channels in which the noise is a Gaussian process,” said Gautham Chavali, of Blacksburg, Va., the second Ph.D. student working on this project. “However, experimental studies have shown that the noise that appears in most radio channels is highly non-Gaussian,” Chavali added.
“Man-made noise, which arises from incidental radiation of a wide range of electrical devices, for example, is partially responsible for this occurrence,” Chavali said. In addition, the algorithms to be designed will not rely on the common, but impractical, assumption of perfect synchronization and equalization by the radio front-end, which is an important concern when dealing with realistic multipath fading channels, such as indoor environments.
InterDigital develops advanced wireless technologies that are at the core of mobile devices, networks, and services worldwide. Using a holistic approach to addressing the bandwidth crunch, the company is developing innovations in spectrum optimization, cross-network connectivity and mobility, and intelligent data.
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