Student research opportunities
Designing Signal Processing Techniques in Massive MIMO Systems
Project Code: CECS_1076
This project is available at the following levels:
Engn4200, Masters
Keywords:
Massive MIMO, low-complexity transmission, performance analysis, optimisation, resource allocation, fading channels.
Supervisor:
Dr Nan YangOutline:
Massive (or large-scale) multiple-input multiple-output (MIMO) has been proposed as a new promising paradigm for next generation wireless communication networks. In this paradigm, base station (BS) antenna arrays are equipped with an order of magnitude more elements than what is used in current systems, i.e., a hundred antennas or more. Massive MIMO enjoys all the benefits of conventional MIMO, such as improved data rate, reliability and reduced interference, but at a much larger scale. Therefore, massive MIMO serves an enabler for the development of future broadband networks, which will be energy-efficient, secure, robust, and spectrum efficient. This trend triggers a fundamental question: "How to design signal processing techniques to effectively exploit the large number of spatial degrees of freedom offered by the large-scale antenna arrays?" To address this question, low-cost precoders/beamformers of massive MIMO systems need to be designed and the analysis of the achievable performance needs to be conducted. The outcomes in this field are of urgent and fundamental importance to academic and business communities.
NB: This project may be temporarily unavailable in some semesters.
Goals of this project
1. Design new cost-cautious transmission and reception techniques to fully exploit the large number of spatial degrees of freedom offered by the large-scale antenna arrays in massive MIMO systems.
2. Analyze and optimise the achievable performance of massive MIMO systems, e.g., spectrum efficiency, energy efficiency, and transmission reliability.
3. Mitigate the detrimental effects caused by pilot contamination on the achievable performance of massive MIMO systems.
Requirements/Prerequisites
A high self-motivation, a solid background in wireless communication, a strong grounding in mathematical skills, and a good level of programming in Matlab.
Student Gain
A thorough understanding on the transmission design. performance characterization, and QoS optimization of massive MIMO systems.
Background Literature
[1] H. Q. Ngo, E. G. Larsson, and T. L. Marzetta, “Energy and spectral efficiency of very large multiuser MIMO systems,” IEEE Trans. Commun., vol. 61, no. 4, pp. 1436-1449, Apr. 2013.
[2] E. G. Larsson, O. Edfors, F. Tufvesson, and T. L. Marzetta, “Massive MIMO for next generation wireless systems”, IEEE Comm. Mag., vol. 52, no. 2, pp. 186-195, Feb. 2014.
