New pilot allocation design schemes for sparse channel estimation in OFDM system

Uwaechia, Anthony Ngozichukwuka; Mahyuddin, Nor Muzlifah

doi:10.1109/icsipa.2017.8120581

Cited by 8 publications

(2 citation statements)

References 19 publications

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“…The basic concept of sparse representation in ECG biometrics is to approximate the original ECG signal employing only a few columns of a dictionary. For instance, sparse representation has realized a better performance in fields of signal processing [54]- [56], computer vision, hybrid precoding [57]- [61], face recognition [62]- [64], and pattern recognition [65]. For standard discriminative sparse representation, the learning-based approach (like K-SVD 2 [66]) and the analytic approach (like wavelet [68]), are the two popularly utilized dictionary construction approaches employed.…”

Section: A Background and Prior Workmentioning

confidence: 99%

A Comprehensive Survey on ECG Signals as New Biometric Modality for Human Authentication: Recent Advances and Future Challenges

Uwaechia

Ramli

2021

IEEE Access

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Electrocardiogram (ECG) has extremely discriminative characteristics in the biometric field and has recently received significant interest as a promising biometric trait. However, ECG signals are susceptible to several types of noises, such as baseline wander, powerline interference, and high/lowfrequency noises, making it challenging to realize biometric identification systems precisely and robustly. Therefore, ECG signal denoising is a major pre-processing step and plays a crucial role in ECG-based biometric human identification. ECG signal analysis for biometric recognition can combine several steps, such as preprocessing, feature extraction, feature selection, feature transformation, and classification which is a very challenging task. Moreover, the selected success measures and proper structure of the ECG signal database play significant roles in biometric system analysis, considering that publicly available databases are essential by the research community to evaluate the performance of their proposed algorithms. In this survey, we review most of the techniques employed for the ECG as biometrics for human authentication. Firstly, we present an overview and discussion on ECG signal preprocessing, feature extraction, feature selection, and feature transformation for ECG-based biometric systems. Secondly, we present a survey of the available ECG databases to evaluate and compare the acquisition protocol, acquisition hardware, and acquisition resolution (bits) for ECG-based biometric systems. Thirdly, we also present a survey on different techniques, including deep learning methods: deep supervised learning, deep semi-supervised learning, and deep unsupervised learning, for ECG signal classification. Lastly, we present the state-of-art approaches of information fusion in multimodal biometric systems.

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Section: A Background and Prior Workmentioning

confidence: 99%

A Comprehensive Survey on ECG Signals as New Biometric Modality for Human Authentication: Recent Advances and Future Challenges

Uwaechia

Ramli

2021

IEEE Access

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“…However, the l 1 -norm approach is often still computationally intensive and challenging to implement in real-time systems. Alternatively, a widely deployed framework for sparse signal recovery is the mutual incoherence property (MIP) presented in [29] and [34]. Using deterministic sensing matrices, if S < 1 2 (1 + 1 µ(A) ) [30], [31], where…”

Section: A Cs and Dcs Theories 1) Cs Theorymentioning

confidence: 99%

Spectrum-Efficient Distributed Compressed Sensing Based Channel Estimation for OFDM Systems Over Doubly Selective Channels

Uwaechia

Mahyuddin

2019

IEEE Access

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In this paper, we deal with channel estimation (CE) for high-mobility orthogonal frequency division multiplexing (OFDM) systems. To make the numerous (unknown) estimation for the high-mobility OFDM systems practicable, the channels are assumed to be time-and frequency-selective−or doubly selective (DS) and approximated by a basis expansion model (BEM). As the DS channel requires the distributed acquisition of multiple correlated signals in the delay-Doppler channel domain, we proceed to estimate jointly sparse BEM coefficient vectors over a DS channel as against numerous channel coefficients. On account of channel time-variation, the resulting channel matrix in the frequency domain exhibits (approximately banded) pseudo-circular structure, which gives rise to a diagonally dominant yet full matrix rather than a diagonal matrix and thus induces inter-channel interference (ICI). On the premise of this observation, we propose a new pilot design scheme that identifies the optimal pilot placement and values for each pilot cluster to combat ICI. Furthermore, to obtain a channel estimator consistent with the jointly sparse delay-Doppler [i.e., two dimensional (2D)] channel model, an algorithm namely, distributed compressed sensing (DCS)-based stage determined matching pursuit (DCS-SdMP), is proposed. Our claims are supported by simulation results, which are obtained considering Jakes' channels with fairly high Doppler spreads, which show the superiority of the proposed schemes over other different methods of CE. INDEX TERMSChannel estimation (CE), doubly selective (DS) channel, orthogonal frequency division multiplexing (OFDM), distributed compressed sensing (DCS), basis expansion model (BEM), pilot design, wireless communication.

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Numerical Modelling and Simulation of Improved Partial Transmit Sequence for PAPR Reduction in OFDM Communication System

Neel¹,

Vyas²

2022

Algorithms for Intelligent Systems

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New pilot allocation design schemes for sparse channel estimation in OFDM system

Cited by 8 publications

References 19 publications

A Comprehensive Survey on ECG Signals as New Biometric Modality for Human Authentication: Recent Advances and Future Challenges

A Comprehensive Survey on ECG Signals as New Biometric Modality for Human Authentication: Recent Advances and Future Challenges

Spectrum-Efficient Distributed Compressed Sensing Based Channel Estimation for OFDM Systems Over Doubly Selective Channels

Numerical Modelling and Simulation of Improved Partial Transmit Sequence for PAPR Reduction in OFDM Communication System

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