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Algorithms 2016, 9(4), 68; doi:10.3390/a9040068

An Overview on the Applications of Matrix Theory in Wireless Communications and Signal Processing

Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX 77843, USA
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Academic Editors: Costas Busch and Bruno Carpentieri
Received: 26 June 2016 / Revised: 8 September 2016 / Accepted: 5 October 2016 / Published: 14 October 2016
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Abstract

This paper overviews the key applications enabled by matrix theory in two major fields of interest in electrical engineering, namely wireless communications and signal processing. The paper focuses on the fundamental role played by matrices in modeling and optimization of wireless communication systems, and in detection, extraction and processing of the information embedded in signals. Among the major applications in wireless communications, the role of matrix representations and decompositions in characterizing multiple-input multiple-output (MIMO) and orthogonal frequency division multiplexing (OFDM) communication systems is described. In addition, this paper points out the important contribution made by matrices in solving signal estimation and detection problems. Special attention is given to the implementation of matrices in sensor array signal processing and the design of adaptive filters. Furthermore, the crucial role played by matrices in representing and processing digital images is depicted by several illustrative applications. This paper concludes with some applications of matrix theory in the area of compressive sensing of signals and by outlining a few open research problems for future study. View Full-Text
Keywords: matrix; signal processing; wireless communications; image processing; compressive sensing matrix; signal processing; wireless communications; image processing; compressive sensing
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Wang, X.; Serpedin, E. An Overview on the Applications of Matrix Theory in Wireless Communications and Signal Processing. Algorithms 2016, 9, 68.

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