Upper-Band MmWave (200-300 GHz) Massive-MIMO Beamforming using Artificial Intelligence for 6G Heterogeneous Networks
Applications are invited for a full time PhD studentship funded by VIAVI Solution Company. The studentship is for a period of 3 years (36 months), to start as soon as possible. The successful applicant will receive an annual stipend of £20,000 plus payment of their full time home/EU tuition fees. International applicants are welcome to apply but be required to self-fund the difference between the published full time international and home/EU tuition fee.
Massive multiple-input multiple-output (MIMO) systems have shown promising features to significantly increase spectral efficiency of cellular communication systems. Future wireless communications such as 6G requires implementation of such systems in extremely high frequency (EHF) range up to 300 GHz for various reasons such as shortage of available spectrum and low attenuation, within 1-2dB/km.
Deployment of massive MIMO systems in EHF band, i.e., millimetre-wave (mmWave) will result in spectral efficiency as well as increased available bandwidth. Nevertheless, the severe attenuation of mmWave signals is a dominant obstacle, and is generally compensated via beamforming techniques that employ the benefit of large antenna arrays in massive MIMO structures often embedded in a tiny dimension in mmWave frequencies. Analog beamforming has shown extensive advantages compared to its traditional counterpart, digital beamforming. Dominant techniques proposed so far for analogue beamforming are often practically challenging. Down-to-earth confrontations are namely the necessity of possessing excellent channel state information (CSI) by the base station (BS) or search complexity. Reduction in search complexity can be achieved by performing high number of iterations between user and BS to exchange information; this leads to inevitable practical overhead. In our research, we plan to propose intelligent beamforming (IB) schemes in contrast. IB is achievable by deployment of artificial intelligence (AI) techniques through design structures that can margin novel context-awareness beamforming to drive 6G. Such implementation will aggregate the advantages of combined massive MIMO and mmWave systems, specifically when designed in upper band EHF such as 200-300GHz, and at the same time intelligently diminishes the complexity and overhead of existing schemes to make it a resourceful option for engineering 6G.
Please contact Professor Hamed Al-Raweshidy at email@example.com or +44(0)1895 265771 for an informal discussion about the project.
Applicants will have or expect to receive a first degree at 2:1 or above in an Engineering or Physical Sciences related discipline. A master’s degree is an advantage but not essential. Applicants with Electronics Engineering background or Computer Science having taken courses in AI are strongly encouraged to apply.
How to apply
Please email your application comprising all of the documents listed below by Noon on Friday 31st January 2020 to firstname.lastname@example.org and email@example.com
- Your up-to-date CV;
- A one A4 page personal statement setting out why you are a suitable candidate (i.e.: your skills and experience);
- Your degree transcripts and/or certificates;
- Evidence of English language skills to IELTS 6.5 (or equivalent), if appropriate;
- Name and contact details for two academic referees.
Interviews will take place early/mid February 2020.