SINR‐based adaptive MIMO FBMC/OQAM transmission with automatic modulation classification

Haring, L.

doi:10.1002/ett.3541

Cited by 7 publications

(3 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The Segment‐Selected Mapping (SSLM) was suggested in this paper 14 for reducing the peak‐to‐average power ratio FBMC signal in satellite communications. Since FBMC is having overlapping nature, it could not be applied openly to FBMC signal in this Standard Selected Mapping (SLM) scheme 15 …”

Section: Related Workmentioning

confidence: 99%

Estimation of carrier frequency offset for FBMC/OQAM by using modified Kalman filtering

Rani¹,

Sridevi²

2020

Int J Communication

View full text Add to dashboard Cite

Filter bank multicarrier (FBMC) based on offset quadrature amplitude modulation (OQAM) is regarded as the prospective system for mobile communication. To utilize the potential of the system, the issues like carrier frequency offset have to be investigated extensively. The modulations in the multicarrier system draw a great interest among researchers and engineers in the telecommunication field. Despite the OFDM advantages, significant disadvantages in the system enable researches to approach into efficiently evolved FBMC system. In this paper, the detrimental effects caused by carrier frequency offset on the received signal is considered. Carrier Frequency Offset (CFO) compensation has been effectively undertaken by modified Kalman filtering. The compensation technique not only depends on the specific FBMC modification but also influenced by the selected receiver. A comprehensive analysis of the frequency offset response under three conditions (without offset, with offset, and the compensated samples) has been performed in the proposed system with performance measures as bit error rate (BER) and signal-to-noise ratio. 9 CFO compensation is analyzed by varying the channel characteristics (additive white Gaussian noise [AWGN] and Rayleigh Fading) and subcarrier filtering (prototype filter, Gaussian filter, and root-raised coefficients). From the overall analysis, it is observed that the BER varies from 0.1 to 0.001.

show abstract

Section: Related Workmentioning

confidence: 99%

Estimation of carrier frequency offset for FBMC/OQAM by using modified Kalman filtering

Rani¹,

Sridevi²

2020

Int J Communication

View full text Add to dashboard Cite

show abstract

“…Due to the increasingly growing demand for wireless radio spectrum bandwidth, better approaches for utilization of the radio spectrum are essential 1 . The automatic modulation classification (AMC) is one of the most common techniques for identifying frequency spectra, spectrum management, electronic warfare, cognitive radio networks, interference detection, 2 radar signal recognition, 3 software‐defined radio, and network traffic control 4 . Without prior knowledge of the modulation parameters and transmitted data, such as frequency offset, signal power, phase offset, carrier frequency, and timing error, recognizing the modulation scheme is a difficult task.…”

Section: Introductionmentioning

confidence: 99%

An efficient modulation classification method using signal constellation diagrams with convolutional neural networks, Gabor filtering, and thresholding

Abdel‐Moneim

Al‐Makhlasawy

Bauomy

et al. 2022

Trans Emerging Tel Tech

View full text Add to dashboard Cite

Recently, automatic modulation classification (AMC) has extensively and commonly been utilized in several modern wireless communication systems as a significant tool of signal detection for civilian and military applications and cognitive radio systems. Although several methods have been established to identify the modulation scheme of a received signal, they show a difficulty of learning radio characteristics for most conventional machine learning algorithms. This article focuses on the deep learning (DL) classification technique to solve these problems. To improve the classification accuracy of a communication signal modulation type, we apply a new model that combines Gabor filtering and thresholding with the help of convolution filters implemented in DL. A basic convolutional neural network, AlexNet, and a residual neural network are used for being compatible with constellation diagrams in order to achieve a superior classification performance. Moreover, the Gabor filter can effectively extract spatial information, including edges and textures. In terms of classification accuracy, the proposed AMC system improves the signal modulation classification accuracy significantly, and achieves competitive results. We use seven modulation types over the range of signal-noise ratio (SNR) values from −10 to 30 dB. The performed experiments reveal that the proposal guarantees a remarkable classification accuracy of approximately 100% at a 10 dB SNR over AWGN and Rayleigh fading channels. Therefore, to prove the functional viability of our proposed method, it can be applied in adaptive modulators that can be used in many devices in applications such as Internet-of-Things (IoT). INTRODUCTIONDue to the increasingly growing demand for wireless radio spectrum bandwidth, better approaches for utilization of the radio spectrum are essential. 1 The automatic modulation classification (AMC) is one of the most common techniques for identifying frequency spectra, spectrum management, electronic warfare, cognitive radio networks, interference

show abstract

“…However, in scenarios with high selectivity, it becomes necessary a two‐stage decision feedback equalizer to improve performance at the cost of computational complexity increasing. In the work of Häring, an adaptive signaling strategy at the transmitter side is elaborated and applied to MIMO‐FBMC systems. In particular, the impact of intrinsic interference inherent to the FBMC‐OQAM is taken into account but at the transmitter side.…”

Section: Introductionmentioning

confidence: 99%

Efficient multitap equalization for FBMC‐OQAM systems

Guerra

Abrão

2019

Trans Emerging Tel Tech

View full text Add to dashboard Cite

This work provides a simple yet efficient multitap equalization structure for filter bank multicarrier systems, which is a candidate waveform for the next generation (5G) of mobile communication systems. More specifically, we analyze the system performance under medium-to high-frequency selective channels. In this scenario, the single-tap equalizer is not enough to compensate the channel effects, and then, a multitap equalizer need to be deployed. In the literature, the available equalization structures that are more efficient in aggressive scenarios are generally quite complex, whereas the less complex alternatives do not perform satisfactorily in such conditions. In this context, we propose a new multitap equalization approach in the frequency domain, aiming at reducing the computational complexity while improving the system robustness against high-frequency selectivity conditions. For a wide range of number of taps and antennas, the proposed minimum mean square error-based frequency domain equalizer presents a much reduced computational complexity, ie, less than 1% of the conventional minimum mean square error-based time domain complexity.The operation, advantages, performance, and the main differences between multitap equalization schemes against the simple one-tap equalizer for filter bank multicarrier systems are comprehensively discussed.One of the main topologies used in the fourth-generation systems has been the orthogonal frequency division multiplexing (OFDM), which has various commercial applications such as wireless networks (Wi-Fi 802.11), multiple-input-multiple-output (MIMO) systems, cellular systems (LTE), and digital television digital video broadcasting-terrestrial. 1 Moreover, OFDM system has many advantages, eg, ability to operate in frequency selective channels, robustness against multipath fading effect, easy implementation with fast Fourier transform algorithms, and trivial equalization due the favorable channel condition on each subcarrier. Because of its features, OFDM is still a candidate for the 5G. However, the OFDM system has some well-known issues that may hinder its use in 5G, such as sensibility with the frequency synchronization, 2 high levels of peak-to-average power ratio (PAPR), which require high linearity amplifiers to avoid signal saturation, and consequently, the signal distortion. 3 Therefore, new advancing research works are necessary, aiming at proposing alternatives to attend the 5G requirements. 4 An alternative method for multiplexing data via multiple carriers, similar to the OFDM, is the filter bank multicarrier (FBMC). In the FBMC scheme, multiple filters are used to transmit data in parallel, using one filter per carrier. In practice, Abbreviations: FBMC, filter bank multicarrier; OQAM, offset quadrature amplitude modulation; MTE, multitap equalization; OFDM, orthogonal frequency division multiplexing. Equally contributing authors.Trans Emerging Tel Tech. 2019;30:e3775.wileyonlinelibrary.com/journal/ett

show abstract

SINR‐based adaptive MIMO FBMC/OQAM transmission with automatic modulation classification

Cited by 7 publications

References 33 publications

Estimation of carrier frequency offset for FBMC/OQAM by using modified Kalman filtering

Estimation of carrier frequency offset for FBMC/OQAM by using modified Kalman filtering

An efficient modulation classification method using signal constellation diagrams with convolutional neural networks, Gabor filtering, and thresholding

Efficient multitap equalization for FBMC‐OQAM systems

Contact Info

Product

Resources

About