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School of Electronic Engineering and Computer Science

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Software-defined radio for machine-to-machine spectrum challenge

Supervisor: Dr Frank Gao

Research group(s): Antennas and Electromagnetics

Spectrum for wireless communicants has become exponentially scarce, especially for the next generation system such as machine-to-machine and 5G. Dynamic spectrum access has been well studied theoretically, but very limited real world implementations. Both the UK regulator, Ofcom, and the US regulator, FCC, have initialised signifiant amount of efforts to enable the UHF TV bands as a starting point for the dynamic spectrum access. In this project, we would like to have a candidate who are interested in soft-defined radio platform such as NI USRP, and take our exiting compressive spectrum sensing algorithms and Geo-Location database model into the software defined radio platform, and participant in part of the Ofcom white space device study in the UK.
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