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Fady Alajaji, P. Eng.

Professor, Mathematics and Engineering

Department of Mathematics and Statistics
Queen's University at Kingston
Kingston, Ontario, Canada, K7L 3N6
Phone: (613) 533-2423; Fax: (613) 533-2964
E-mail: fady@mast.queensu.ca

Research group: Communications (Applied Mathematics)

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Research Interests

Keywords : Information theory, joint source-channel coding, digital communications, error-control coding, data compression, applied probability.

My research interests belong to the general area of information and communication theory. More specifically, I am interested in the coding of information-bearing signals for transmission over noisy communication channels. This problem is addressed at two levels: One objective is to understand and investigate the Shannon theoretic aspect of this problem -- i.e., to determine the fundamental limits of how efficiently one can encode information and still be able to recover it with negligible loss. Another vital objective is to develop new techniques that are appropriate for current and near-term developing technologies -- e.g., achieving reliable transmission of multimedia signals over wireless networks for the establishment of mobile communication systems. Current research activities can be divided into two areas:

  1. Information Theory: Properties of information measures and their operational characterizations for systems with memory; information spectrum techniques; Shannon coding theorems, source and channel coding; error probability, cutoff rates and reliability function; capacity and capacity-cost function; feedback capacity of channels with memory; two-way networks; information hiding; analysis and modeling of channels with memory, burst-noise channels, finite-state channels, contagion-based channels, modeling of correlated fading channels; bounds on the probability of a union and applications to the error analysis of communication systems; stochastic analysis of network epidemics.

  2. Joint Source-Channel Coding: Channel optimized vector quantization; bandwidth efficient source-optimized channel codes; applications to wireless communications and sensor networks; source-channel signal mapping and modulation; maximum a posteriori joint source-channel decoding; Turbo codes, low-density parity-check codes and iterative decoding; hybrid digital-analog signaling and source-channel coding; multiple-input multiple-output channels and space-time coding; compressive sensing; applications to multimedia processing and communications.

Research Publications



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