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

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:

Partner:

TELUS (Ottawa, ON)

Discipline:

Computer science

Sector:

Information and cultural industries

University:

University of Alberta

Program: