Probabilities of False Alarm and Detection for the First-Order Cyclostationarity Test: Application to Modulation Classification

Serbes, Ahmet; Cukur, Huseyin; Qaraqe, Khalid

doi:10.1109/lcomm.2019.2947043

Cited by 11 publications

(4 citation statements)

References 12 publications

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“…Digital modulator SC-FDMA symbol generation STBC mapping az (1) X (1) c (1,0) Binary sequence c (1,2) User 0 User 1…”

Section: Binary Sequencementioning

confidence: 99%

“…This analysis is generally referred to as signal identification with military and civilian implications. This has long been used in military applications such as signal interception, radio surveillance, interference detection and mitigation, jamming detection, and electronic warfare [1], [2]. The advent of intelligent radios, reconfigurable transceivers having the ability to alter their transmission settings such as modulation format [3]- [6] and channel coding rate [7]- [11], has heightened interest in signal identification systems in the context of recent civilian applications such as cellular mobile systems and WiFi networks [12], [13].…”

Section: Introductionmentioning

confidence: 99%

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STBC Identification for Multi-User Uplink SC-FDMA Asynchronous Transmissions Exploiting Iterative Soft Information Feedback of Error Correcting Codes

Marey

Mostafa

2022

IEEE Access

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With the advancement and widespread implementation of multiple-input multipleoutput (MIMO) wireless communication systems over the last decade, space-time block coding (STBC) identification has become a critical task for intelligent radios. Previous examinations of STBC identification were focused on single-user transmissions over single-carrier and multicarrier systems in combination with uncoded broadcasts. Practical systems, on the other hand, contain many users and employ error-correcting codes. For the first time in literature, this work explores the problem of STBC identification for multi-user uplink transmissions in singlecarrier frequency division multiple access (SC-FDMA) systems. We take another step closer to real systems by addressing asynchronous transmissions and by conducting multi-user channel estimation. We also exploit the outputs of the channel decoder, which is usually used in many practical systems, to improve the identification and estimation processes. The mathematical analysis demonstrates that the maximum-likelihood (ML) solution of STBC identification, channel estimation, and synchronization can be executed by an iterative approach. The space-alternating generalized expectation-maximization (SAGE) algorithm is used to separate the overlaid signals arriving at the base-station (BS). The parameters under consideration for each user are then updated using an expectation-maximization (EM) processor. Simulation results show that the proposed architecture outperforms other identification methods published in the literature while maintaining a reasonable level of computational complexity.

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“…Digital modulator SC-FDMA symbol generation STBC mapping az (1) X (1) c (1,0) Binary sequence c (1,2) User 0 User 1…”

Section: Binary Sequencementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

STBC Identification for Multi-User Uplink SC-FDMA Asynchronous Transmissions Exploiting Iterative Soft Information Feedback of Error Correcting Codes

Marey

Mostafa

2022

IEEE Access

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“…The cyclostationary (CS) feature based method has considerable potential to solve the above problem [11], [12]. In a short observation time, both signal and fading channel can be modeled as cyclostationary process.…”

Section: Introductionmentioning

confidence: 99%

Cyclostationary Feature Based Modulation Classification With Convolutional Neural Network in Multipath Fading Channels

Yin,

Xiang,

Liang

2023

IEEE Access

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Modulation classification has been widely studied in recent years. However, few studies focus on the performance degradation in multipath fading channels, whose impact is non-negligible. In this paper, a convolutional neural network (CNN) employing cyclostationary (CS) feature, which maintain the essential characteristics in fading channels, is proposed for robust modulation classification. Our method can be implemented in two approaches, referred as CASE1 and CASE2. In CASE1, a single-structured CNN is designed for learning hybrid CS features to perform classification. And in CASE2, we present a CNN model based on a hierarchical structure to perform two-stage classification. Specifically, the coarse classification is performed by learning the second-order CS features with the first-level CNN. Next, another CNN can be selectively activated to learn from high-order CS features for fine classification within the subclass. In this way, our method uses CS features to provide favorable guidance for the learning process of CNN, thus improving the classification performance in fading channels. The experimental results demonstrate the advantages of the proposed method in terms of classification accuracy and computational complexity.

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“…Even though LB AMA techniques reach the highest level of precision, they are computationally intensive and may be prohibitively costly in reality. To compensate for this limitation, FB AMA techniques exploit signal characteristics, such as higher order statistics and cyclostationarity to discriminate between modulation types [ 11 , 12 , 13 , 14 ].…”

Section: Introductionmentioning

confidence: 99%

Modulation Awareness Method for Dual-Hop Cooperative Transmissions over Frequency-Selective Channels

Marey

Mostafa

2022

Sensors

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Modulation awareness and cooperative transmissions have individually received a significant amount of research in the scholarly literature. However, a limited number of works are principally concerned with the combination of the two topics, and they are restricted to frequency-flat wireless channels. In this study, we propose a new modulation awareness method applicable to dual-hop amplify-and-forward cooperative broadcasts. The suggested method is built on the creation of theoretical representations of cross-correlation functions of the received signals. We conceptually prove that a family of modulation types generates spikes for certain cross-correlation functions, while others do not. We create a numerous layer hypothesis evaluation for the purpose of making judgments centered on this attribute. The suggested method has a number of benefits, such as the ability to operate on both frequency-flat and frequency-selective channels, as well as the absence of the necessity of channel awareness or noise power. Computer simulations analyze the performance of the proposed method, which delivers adequate awareness performance in a variety of operational scenarios.

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Probabilities of False Alarm and Detection for the First-Order Cyclostationarity Test: Application to Modulation Classification

Cited by 11 publications

References 12 publications

STBC Identification for Multi-User Uplink SC-FDMA Asynchronous Transmissions Exploiting Iterative Soft Information Feedback of Error Correcting Codes

STBC Identification for Multi-User Uplink SC-FDMA Asynchronous Transmissions Exploiting Iterative Soft Information Feedback of Error Correcting Codes

Cyclostationary Feature Based Modulation Classification With Convolutional Neural Network in Multipath Fading Channels

Modulation Awareness Method for Dual-Hop Cooperative Transmissions over Frequency-Selective Channels

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