Automatic Modulation Classification for D-STBC Cooperative Relaying Networks

Tayakout, Hakim; Dayoub, Iyad; Ghanem, Khalida; Bousbia-Salah, H.

doi:10.1109/lwc.2018.2824813

Cited by 39 publications

(18 citation statements)

References 11 publications

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“…As low computational complexity features and widely employed in digital modulation identification (DMI), higherorder statistics (HOS), i.e., higher-order moments (HOM) and higher-order cumulants (HOC), have always exhibited a good identification performance [1]- [8]. Employed HOS in that context are estimated from noisy observations.…”

Section: Introductionmentioning

confidence: 99%

“…Estimated HOC are insensitive to noise [9], unlike the estimated HOM. As such, most of HOS-based DMI algorithms rely on HOC as features [1], [5], [7], [8]. However, many other HOSbased DMI algorithms attempt to improve the identification performance by including a set of HOM [2]- [4], [6].…”

Section: Introductionmentioning

confidence: 99%

“…Also, within the framework of this paper, we consider multiple-input-multipleoutput (MIMO) systems as an essential part of state-of-theart wireless systems. Moreover, multi-antenna systems are amply involved in the subject of DMI [2]- [6], [8], [10]- [13]. As far as we know, there is no yet attempt on offsetting noise in HOM in the blind DMI context.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Denoising Higher-Order Moments for Blind Digital Modulation Identification in Multiple-Antenna Systems

Kharbech

Simon

Belazi

et al. 2020

IEEE Wireless Commun. Lett.

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The paper proposes a new technique that substantially improves blind digital modulation identification (DMI) algorithms that are based on higher-order statistics (HOS). The proposed technique takes advantage of noise power estimation to make an offset on higher-order moments (HOM), thus getting an estimate of noise-free HOM. When tested for multipleantenna systems, the proposed method outperforms other DMI algorithms, in terms of identification accuracy, that are based only on cumulants or do not consider HOM denoising, even for a receiver with impairments. The improvement is achieved with the same order of complexity of the common HOS-based DMI algorithms in the same context.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Denoising Higher-Order Moments for Blind Digital Modulation Identification in Multiple-Antenna Systems

Kharbech

Simon

Belazi

et al. 2020

IEEE Wireless Commun. Lett.

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“…According to the authors, the benefit of channel-type identification for the link adaption in 802.11ac systems is demonstrated, with up to 1.6 dB gain achieved at high SNR and classification accuracy of more than 94%. In [10], is proposed an AMC method based on a new on a simplified distributed space-time block coding scheme for a cooperative network with single antenna source and relay nodes. The results reported revealed that, relative to k-NN, the proposed solution enjoys better precision and robustness, and allows achieving higher objective performance.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Bayesian Approach Applied in Link Adaptation Problem for Fifth Generation Network

Nascimento¹,

Cavalcanti²,

Almeida³

et al. 2020

Anais De XXXVIII Simpósio Brasileiro De Telecomunicações E Processamento De Sinais

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With technological development, wireless communication has been one of the fastest growing fields of Computing and Engineering in recent years. This fact requires that new approaches be developed to ensure better performance and reliability in wireless communication. In this paper a new approach has been proposed as a solution to the problem of adaptive modulation and coding (AMC), through the development of an extension of the method naive Bayesian classifier, known as dynamic naive Bayesian classifier, to maximize spectral efficiency. The proposed approach exhibits a better performance than k-nearest neighbours algorithm and the traditional Look-Up table solution, with average classification error 2.85%, which represents approximately 10% with respect to the most similar method.

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“…Transmit diversity has been applied for mitigating the effect of multi-path fading, as it can improve the performance without adding additional bandwidth and increasing transmit power. A space-time block code (STBC) is most widely used to provide transmit diversity [1][2][3][4][5][6][7][8][9]. The orthogonal STBC (O-STBC) was introduced to achieve full diversity and a full transmission rate for two transmit antennas [1].…”

Section: Introductionmentioning

confidence: 99%

A Minimum Mean-Square-Error (MMSE) Decoder for Quasi-Orthogonal Space–Time Block Code

Jeong

2019

Electronics

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The quasi-orthogonal space–time block code (QO-STBC) was introduced to achieve a full transmission rate for the four antennas system. In this paper, a decoding method for the QO-STBC is proposed to improve the bit-error-rate (BER) and to solve a rank-deficient problem. The proposed algorithm is based on the minimum mean-square-error (MMSE) technique. To overcome the implementation problem from the MMSE, an estimation method of the noise variance is developed in this paper. The proposed algorithm is implemented without matrix inversion, therefore, the proposed algorithm achieves a better BER than the conventional algorithms, as it has a low computational complexity. The simulation results show the low BER of the proposed algorithm in a Rayleigh fading channel.

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Automatic Modulation Classification for D-STBC Cooperative Relaying Networks

Cited by 39 publications

References 11 publications

Denoising Higher-Order Moments for Blind Digital Modulation Identification in Multiple-Antenna Systems

Denoising Higher-Order Moments for Blind Digital Modulation Identification in Multiple-Antenna Systems

Dynamic Bayesian Approach Applied in Link Adaptation Problem for Fifth Generation Network

A Minimum Mean-Square-Error (MMSE) Decoder for Quasi-Orthogonal Space–Time Block Code

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