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Transmit antenna number identification for MIMO cognitive radio systems in the presence of Alpha-Stable noise

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Zhang, Junlin, Zhao, Nan, Liu, Mingqian, Chen, Yunfei, Gong, Fengkui, Yang, Qinghai and Yu, F. Richard (2022) Transmit antenna number identification for MIMO cognitive radio systems in the presence of Alpha-Stable noise. IEEE Transactions on Vehicular Technology, 71 (3). pp. 2798-2808. doi:10.1109/TVT.2021.3137627 ISSN 0018-9545.

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Official URL: https://doi.org/10.1109/TVT.2021.3137627

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Abstract

Identification of communication parameters, a major task of intelligent receivers, has important applications in intelligent systems, especially cognitive radio systems. Multiple antennas make the identification problem more challenging. In this paper, we focus on the problem of detecting the number of transmit antennas in multiple-input multiple-output (MIMO) cognitive radio systems. A novel identification algorithm is proposed to determine the number of transmit antennas for MIMO systems in the presence of alpha-stable noise. We first introduce the correlation matrix based on the fractional lower order statistics (FLOS) and provide a particular structure of FLOS-based correlation matrix. Then, the eigenvalues of the FLOS-based correlation matrix are employed to construct a test statistic and the central limit theorem is exploited to obtain the decision threshold. Finally, the transmit-antenna number is detected using a serial binary hypothesis test. Simulation results are demonstrated to evaluate the effectiveness of the proposed transmit-antenna number detection algorithm for MIMO systems in the presence of alpha-stable noise.

Item Type: Journal Article
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Science, Engineering and Medicine > Engineering > Engineering
Library of Congress Subject Headings (LCSH): MIMO systems, Wireless communication systems, Parametric amplifiers, Noise
Journal or Publication Title: IEEE Transactions on Vehicular Technology
Publisher: IEEE
ISSN: 0018-9545
Official Date: March 2022
Dates:
DateEvent
March 2022Published
29 December 2021Available
8 December 2021Accepted
Volume: 71
Number: 3
Page Range: pp. 2798-2808
DOI: 10.1109/TVT.2021.3137627
Status: Peer Reviewed
Publication Status: Published
Reuse Statement (publisher, data, author rights): © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Access rights to Published version: Restricted or Subscription Access
Date of first compliant deposit: 21 December 2021
Date of first compliant Open Access: 4 January 2022
RIOXX Funder/Project Grant:
Project/Grant IDRIOXX Funder NameFunder ID
62071364[NSFC] National Natural Science Foundation of Chinahttp://dx.doi.org/10.13039/501100001809
2020Z073081001Aeronautical Science Foundation of Chinahttp://dx.doi.org/10.13039/501100004750
JB210104Fundamental Research Funds for the Central Universitieshttp://dx.doi.org/10.13039/501100012226
B08038Higher Education Discipline Innovation Projecthttp://dx.doi.org/10.13039/501100013314
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