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  Next Generation SDR Techniques for Millimetre Wave Systems

   Department of Electronic & Electrical Engineering

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  Mr Eddie Ball  Applications accepted all year round  Self-Funded PhD Students Only

About the Project

Applications are invited for PhD candidates on the themes described below, as part of The University of Sheffield’s Communications Research Group and EPSRC National Millimetre Wave Measurement Laboratory.


The concept of Software Defined Radio (SDR) is now relatively mature, having been applied to commercial radio system design and integrated circuit design tasks for several years. The move to an ‘all-digital’ transceiver, where the antenna terminates in an Analogue to Digital Converter (ADC) or Digital to Analogue Converter (DAC), with the whole of the radio function being performed using digital electronics and DSP, is seen as the ultimate technological goal. This is particularly true for radios requiring an extremely high degree of reconfigurability or low manufacturing cost. However, hybrid RF analogue & SDR systems remain vital for very high-performance RF applications, especially for millimetre wave (mmWave) and sub-THz radio systems.

The application of Artificial Intelligence and Machine Learning techniques in wireless communications systems is growing. One exciting area is in the use of such techniques applied directly to the signals at the radio’s hardware or physical layer. This could allow next generation radio systems to identify and ultimately demodulate a signal directly, regardless of channel response or impairments.

The purpose of this research project is to investigate present state-of-the-art aspects of next generation SDR for mmWave and then choose an area for further research that is interesting to the candidate and complements the Group’s activity. The research topic will be chosen from one or more of (but not limited to) the following themes, as relevant to the ongoing Group’s research activity:-

·       RF Sampling transceiver architectures

·       Application of AI / Machine Learning to physical layer signals and waveforms

·       Efficient techniques for all–digital up-conversion / down-conversion

·       Linearisation strategies for full RX / TX chains (with efficient use of DSP)

·       DSP algorithms associated with RX signal detection & TX signal generation

·       Cognitive Radio hardware architectures and algorithms

·       SDR system architectures for future mmWave transceivers (fixed and mobile)

Researchers can expect to become involved in designing (where relevant) novel hardware and related DSP or control software for their proposed system(s) and then trialling and enhancing them for optimal operation in the Lab and in field trials. The project will be part of an ongoing activity in 5G & 6G next generation mmWave systems, also involving a wide range of industry partners. The Communications Research Group is working on multiple areas of wireless communications technology including mmWave, sub-THz communications, propagation measurement and IoT systems. The technology emerging from the researcher's project will contribute to these research themes.

For further information and informal enquiries contact Mr Eddie Ball at [Email Address Removed]

To formally apply for this post, please use the graduate application webpage:

Engineering (12)

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 About the Project