Efficient Signal Processing and Radio Resource Management for High-Throughput and Low-Latency Massive MIMO Cellular Systems – Year two

Future cellular systems must accommodate increasing demand for very high throughput and low latency data services. Massive multiple-input multiple-output (MIMO) approach involving base stations equipped with much larger numbers of antennas than the numbers of users served promises to significantly increase network capacity, while nonorthogonal multi-carrier transmission is expected to dramatically reduce the latency. Integration of these techniques will require novel efficient transceiver signal processing and radio resource management solutions, such as reducedcomplexity precoding and user scheduling algorithms. These algorithms will need to be robust to typical imperfections, such as antenna coupling in large arrays of limited physical size and also possible non-reciprocity of uplink and downlink hardware chains, resulting in inaccurate channel state information at transmitters and reduced capacity. 3D beamforming in massive MIMO will also be investigated. TELUS Communications has expressed great interest in the proposed work and will support it in the amount of $30k per year.

Faculty Supervisor:

Witold Antoni Krzymien

Student:

Mahmood Mazrouei Sebdani

Partner:

Telus

Discipline:

Engineering - computer / electrical

Sector:

Information and communications technologies

University:

University of Alberta