Efficient and Reliable Modulation Classification for MIMO Systems

Mohammad Rida Bahloul; Mohd Zuki Yusoff; Abdel Haleem Abdel-Aty; Mohd Naufal Saad; Anis Laouiti

doi:10.1007/s13369-017-2730-9

Efficient and Reliable Modulation Classification for MIMO Systems

Mohammad Rida Bahloul, Mohd Zuki Yusoff, Abdel Haleem Abdel-Aty, Mohd Naufal Saad, Anis Laouiti

Research output: Contribution to journal › Article › peer-review

Abstract

In this paper, an efficient and reliable feature-fusion-based modulation classification (MC) algorithm for multiple-input multiple-output (MIMO) systems is developed. It uses two higher-order cumulants of the transmitted signal streams to classify a broad set of modulation types with no prior knowledge of the channel state information. We address the problem of the soft-decision fusion for the feature-fusion-based MC algorithms for MIMO systems and introduce an optimal soft-decision fusion scheme to find the classification result. The complexity order of the proposed MC algorithm is studied in detail to demonstrate its low computation cost, and its performance is validated extensively by simulation results to show its practical effectiveness.

Original language	English
Pages (from-to)	5201-5209
Number of pages	9
Journal	Arabian Journal for Science and Engineering
Volume	42
Issue number	12
DOIs	https://doi.org/10.1007/s13369-017-2730-9
Publication status	Published - 1 Dec 2017

Keywords

5G
Higher-order statistics
Modulation classification (MC)
Next-generation communications
Soft-decision fusion
multiple-input multiple-output (MIMO)

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10.1007/s13369-017-2730-9

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title = "Efficient and Reliable Modulation Classification for MIMO Systems",

abstract = "In this paper, an efficient and reliable feature-fusion-based modulation classification (MC) algorithm for multiple-input multiple-output (MIMO) systems is developed. It uses two higher-order cumulants of the transmitted signal streams to classify a broad set of modulation types with no prior knowledge of the channel state information. We address the problem of the soft-decision fusion for the feature-fusion-based MC algorithms for MIMO systems and introduce an optimal soft-decision fusion scheme to find the classification result. The complexity order of the proposed MC algorithm is studied in detail to demonstrate its low computation cost, and its performance is validated extensively by simulation results to show its practical effectiveness.",

keywords = "5G, Higher-order statistics, Modulation classification (MC), Next-generation communications, Soft-decision fusion, multiple-input multiple-output (MIMO)",

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note = "Publisher Copyright: {\textcopyright} 2017, King Fahd University of Petroleum \& Minerals.",

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doi = "10.1007/s13369-017-2730-9",

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AU - Bahloul, Mohammad Rida

AU - Yusoff, Mohd Zuki

AU - Abdel-Aty, Abdel Haleem

AU - Saad, Mohd Naufal

AU - Laouiti, Anis

PY - 2017/12/1

Y1 - 2017/12/1

N2 - In this paper, an efficient and reliable feature-fusion-based modulation classification (MC) algorithm for multiple-input multiple-output (MIMO) systems is developed. It uses two higher-order cumulants of the transmitted signal streams to classify a broad set of modulation types with no prior knowledge of the channel state information. We address the problem of the soft-decision fusion for the feature-fusion-based MC algorithms for MIMO systems and introduce an optimal soft-decision fusion scheme to find the classification result. The complexity order of the proposed MC algorithm is studied in detail to demonstrate its low computation cost, and its performance is validated extensively by simulation results to show its practical effectiveness.

AB - In this paper, an efficient and reliable feature-fusion-based modulation classification (MC) algorithm for multiple-input multiple-output (MIMO) systems is developed. It uses two higher-order cumulants of the transmitted signal streams to classify a broad set of modulation types with no prior knowledge of the channel state information. We address the problem of the soft-decision fusion for the feature-fusion-based MC algorithms for MIMO systems and introduce an optimal soft-decision fusion scheme to find the classification result. The complexity order of the proposed MC algorithm is studied in detail to demonstrate its low computation cost, and its performance is validated extensively by simulation results to show its practical effectiveness.

KW - 5G

KW - Higher-order statistics

KW - Modulation classification (MC)

KW - Next-generation communications

KW - Soft-decision fusion

KW - multiple-input multiple-output (MIMO)

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M3 - Article

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SP - 5201

EP - 5209

JO - Arabian Journal for Science and Engineering

JF - Arabian Journal for Science and Engineering

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Efficient and Reliable Modulation Classification for MIMO Systems

Abstract

Keywords

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