Project outline

Since the introduction of multiple antennas as a solution for throughput problems in wireless networks, the advanced signal processing inherent to MIMO (Multiple Inputs Multiple Outputs) technology has helped solve many technical problems. Until recently, expected gains from these technologies were limited by different types of interference – for example, obstacles in the physical environment or competing signals – resulting in reduced performance and range and even in loss of connectivity.

MIMO transmitters can send multiple signals using the same frequency band; MIMO receivers use the multiplicity of waves to reconstitute the original message even if the signal is degraded. MIMO receivers can reassemble the information using algorithms that put packets back correctly.

Multiple antennas also entail multiple efforts to reconstitute signals, whose complexity increases as the square (2) of the number of antennas. If three transmitters send the same signal to three receivers, the latter receive the signal nine times – and so on for each added antenna. As a result of this exponential growth, data-processing devices require increasing processing power.

Currently, the team headed by Leszek Szczecinski is developing a microelectronic application for a range of algorithms designed to reduce the complexity and power needed for signal reception and processing in MIMO systems.

Expected results

• Solutions for signal transmission resulting from modulation and adaptive coding
• Iterative signal-processing algorithms for signal reception

Our partners

• FQRNT (Fond Québécois pour la recherche sur la nature et les technologies) (Quebec fund for research on nature and technology)
• Institut national de recherche scientifique (Quebec science research institute)
• Concordia University

Team members

Professors: Leszek Szczecinski, François Gagnon and Ali Grayeb
Student: Safa Saadaoui

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