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5G/Massive MIMO Channel / Software/EDA Channel / Industry News

Nutaq announces the 2014 Software Defined Radio academic US contest winner

June 5, 2014
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Georgios Sklivanitis and Emrecan Demirors with the Software Defined Networks (SDN) Lab in the Department of Electrical Engineering of the State University of New York at Buffalo have won Nutaq's 2014 Software Defined Radio Academic US Contest.

The contest, put on with the collaboration of The Mathworks and Xilinx, aims to encourage innovation and support academics in their efforts to develop tomorrow’s wireless technologies.

The SUNY Buffalo SDN Lab team guided by Prof. Dimitris Pados will be using Nutaq's PicoSDR 2x2 MIMO platform, along with a model-based design software tool suite, to study, implement, and demonstrate a new approach for spectral efficiency maximization in future heterogeneous wireless systems. The  researchers will exploit  the agility offered by real-time reconfigurable wireless radio platforms to carry out jointly optimized signal waveform allocation and routing.

Features of the PicoSDR platform which will help the SDN Lab team with their research include support for GNU Radio as well as the PCI Express interface which overcomes the GigE SDR-to-PC interconnection bottleneck which may be present on other SDR platforms. The 2x2-MIMO will be used to prove the proposed concept for efficient space, time, and spectrum utilization.

The model-based design kit (MBDK) tools, which provide a seamless interface between Nutaq's hardware platform, The Mathworks MATLAB and Simulink with Signal Processing Toolbox, and the Xilinx ISE Design Suite and System Generator for DSP, will help the researchers rapidly embed their cross-layer design into the Virtex-6 FPGA of the PicoSDR platform and thus enable higher system performance and throughput.

Additionally, the MBDK's co-simulation features and Real-Time Data Exchange tool will enable full-duplex data transfer between hardware and software on-the-fly. As a result the SDN Lab system will be able to simultaneously drive waveform selection decisions from software to hardware, while collected environmental and received content data are passed from hardware to software in real-time.

To help encourage the sharing of the findings with other researchers, the results of the SDN Lab team will be presented in top-rated international journals and conferences. Moreover, graduate theses will be published from the results of the proposed project and will  be made accessible to the public through the University's e-library archive.

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