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Huansheng Wang - One of the best experts on this subject based on the ideXlab platform.

  • wavelet based ecg data compression system with Linear quality control scheme
    IEEE Transactions on Biomedical Engineering, 2010
    Co-Authors: Kingchu Hung, Huansheng Wang
    Abstract:

    Maintaining reconstructed signals at a desired level of quality is crucial for lossy ECG data compression. Wavelet-based approaches using a recursive decomposition process are unsuitable for real-time ECG signal recoding and commonly obtain a nonLinear compression performance with Distortion sensitive to quantization error. The sensitive response is caused without compromising the influences of word-length-growth (WLG) effect and unfavorable for the reconstruction quality control of ECG data compression. In this paper, the 1-D reversible round-off nonrecursive discrete periodic wavelet transform is applied to overcome the WLG magnification effect in terms of the mechanisms of error propagation resistance and significant normalization of octave coefficients. The two mechanisms enable the design of a multivariable quantization scheme that can obtain a compression performance with the approximate characteristics of Linear Distortion. The quantization scheme can be controlled with a single control variable. Based on the Linear compression performance, a Linear quantization scale prediction model is presented for guaranteeing reconstruction quality. Following the use of the MIT-BIH arrhythmia database, the experimental results show that the proposed system, with lower computational complexity, can obtain much better reconstruction quality control than other wavelet-based methods.

  • a high efficient quality control strategy for wavelet based ecg data compression system
    BioMedical Engineering and Informatics, 2008
    Co-Authors: Kingchu Hung, Huansheng Wang
    Abstract:

    Maintaining retrieved signal with desired quality is crucial for ECG data compression. In this paper, a high efficient quality control strategy is proposed for wavelet-based ECG data compression. The strategy is based on a modified non-Linear quantization scheme that can obtain a Linear Distortion behavior with respective to a control variable. The Linear Distortion characteristic supports the design of a Linear control variable prediction algorithm. By using the MIT-BIH arrhythmia database, the experimental results show that the Linear control variable prediction method can effectively improve the convergence speed than the previous literatures.

Kingchu Hung - One of the best experts on this subject based on the ideXlab platform.

  • ep based wavelet coefficient quantization for Linear Distortion ecg data compression
    Medical Engineering & Physics, 2014
    Co-Authors: Kingchu Hung, Hsiehwei Lee, Tungkuan Liu
    Abstract:

    Reconstruction quality maintenance is of the essence for ECG data compression due to the desire for diagnosis use. Quantization schemes with non-Linear Distortion characteristics usually result in time-consuming quality control that blocks real-time application. In this paper, a new wavelet coefficient quantization scheme based on an evolution program (EP) is proposed for wavelet-based ECG data compression. The EP search can create a stationary relationship among the quantization scales of multi-resolution levels. The stationary property implies that multi-level quantization scales can be controlled with a single variable. This hypothesis can lead to a simple design of Linear Distortion control with 3-D curve fitting technology. In addition, a competitive strategy is applied for alleviating data dependency effect. By using the ECG signals saved in MIT and PTB databases, many experiments were undertaken for the evaluation of compression performance, quality control efficiency, data dependency influence. The experimental results show that the new EP-based quantization scheme can obtain high compression performance and keep Linear Distortion behavior efficiency. This characteristic guarantees fast quality control even for the prediction model mismatching practical Distortion curve.

  • wavelet based ecg data compression system with Linear quality control scheme
    IEEE Transactions on Biomedical Engineering, 2010
    Co-Authors: Kingchu Hung, Huansheng Wang
    Abstract:

    Maintaining reconstructed signals at a desired level of quality is crucial for lossy ECG data compression. Wavelet-based approaches using a recursive decomposition process are unsuitable for real-time ECG signal recoding and commonly obtain a nonLinear compression performance with Distortion sensitive to quantization error. The sensitive response is caused without compromising the influences of word-length-growth (WLG) effect and unfavorable for the reconstruction quality control of ECG data compression. In this paper, the 1-D reversible round-off nonrecursive discrete periodic wavelet transform is applied to overcome the WLG magnification effect in terms of the mechanisms of error propagation resistance and significant normalization of octave coefficients. The two mechanisms enable the design of a multivariable quantization scheme that can obtain a compression performance with the approximate characteristics of Linear Distortion. The quantization scheme can be controlled with a single control variable. Based on the Linear compression performance, a Linear quantization scale prediction model is presented for guaranteeing reconstruction quality. Following the use of the MIT-BIH arrhythmia database, the experimental results show that the proposed system, with lower computational complexity, can obtain much better reconstruction quality control than other wavelet-based methods.

  • a high efficient quality control strategy for wavelet based ecg data compression system
    BioMedical Engineering and Informatics, 2008
    Co-Authors: Kingchu Hung, Huansheng Wang
    Abstract:

    Maintaining retrieved signal with desired quality is crucial for ECG data compression. In this paper, a high efficient quality control strategy is proposed for wavelet-based ECG data compression. The strategy is based on a modified non-Linear quantization scheme that can obtain a Linear Distortion behavior with respective to a control variable. The Linear Distortion characteristic supports the design of a Linear control variable prediction algorithm. By using the MIT-BIH arrhythmia database, the experimental results show that the Linear control variable prediction method can effectively improve the convergence speed than the previous literatures.

Svilen Dimitrov - One of the best experts on this subject based on the ideXlab platform.

  • non Linear Distortion cancellation and symbol based equalization in satellite forward links
    IEEE Transactions on Wireless Communications, 2017
    Co-Authors: Svilen Dimitrov
    Abstract:

    In this paper, a low-complexity symbol-based equalizer that performs non-Linear Distortion cancellation is proposed for application at the user terminal in the DVB-S2X satellite forward link. The channel is comprehensively modeled, including the non-Linear travelling wave tube amplifier characteristics, the input-multiplexing and output-multiplexing filter responses at the satellite transponder, and the phase noise at the user terminal, according to the very-small aperture terminal reference scenario. Two detectors in the cancellation loop are considered, comparing the packet-error rate (PER) performance of simple maximum likelihood demodulation with hard decision to soft information exchange with low-density parity-check decoder, and showing only marginal improvement with the latter solution. The PER performance is compared against a number of pre-Distortion techniques at the transmitter, such as dynamic data pre-Distortion, successive data pre-Distortion, and static data pre-Distortion. The novel receiver demonstrates superior performance even with one iteration of Distortion cancellation, while the joint application of successive data pre-Distortion and iterative symbol-based equalization shows up to 4.95-dB energy efficiency gain for 32-level amplitude and phase-shift keying (32-APSK). The computational complexity is also evaluated. The improved receiver is particularly suitable for application with higher order modulation, a wide-band carrier, and low roll-off factors.

  • iterative cancellation of non Linear Distortion noise in digital communication systems
    IEEE Transactions on Communications, 2015
    Co-Authors: Svilen Dimitrov
    Abstract:

    In this paper, an iterative receiver that performs non-Linear Distortion noise cancellation is presented. The performance is assessed for time division multiple access (TDMA), orthogonal frequency division multiple access (OFDMA) and single-carrier frequency division multiple access (SC-FDMA) waveforms. Even though a return link setup is considered, the receiver is equally applicable in the forward link, taking into account the differences in the data multiplexing and the channel. Analytical modeling of the received electrical signal-to-noise ratio (SNR) is carried out for OFDMA with one iteration of non-Linear Distortion noise cancellation. The performance is assessed in terms of power efficiency and spectral efficiency, where the total degradation (TD) of the received SNR in a non-Linear channel is minimized. The modulation formats of the DVB-RCS2 satellite return link standard and a respective non-Linear channel have been used. OFDMA shows the highest power efficiency gain of 1.1–2.5 dB with 2 iterations of non-Linear noise cancellation across the different modulation orders. In SC-FDMA, the gain is in the range of 0.3–1.1 dB, while gains of 0.1–0.8 dB and 0.2–1.9 dB are presented in TDMA with 20% roll-off and 5% roll-off, respectively.

Ottersten Björn - One of the best experts on this subject based on the ideXlab platform.

  • A Worst-Case Performance Optimization Based Design Approach to Robust Symbol-Level Precoding for Downlink MU-MIMO
    2020
    Co-Authors: Haqiqatnejad Alireza, Shahbazpanahi Shahram, Ottersten Björn
    Abstract:

    This paper addresses the optimization problem of symbol-level precoding (SLP) in the downlink of a multiuser multiple-input multiple-output (MU-MIMO) wireless system while the precoder's output is subject to partially-known Distortions. In particular, we assume a Linear Distortion model with bounded additive noise. The original signal-to-interference- plus-noise ratio (SINR) -constrained SLP problem minimizing the total transmit power is first reformulated as a penalized unconstrained problem, which is referred to as the relaxed robust formulation. We then adopt a worst-case design approach to protect the users' intended symbols and the targeted constructive interference with a desired level of confidence. Due to the non-convexity of the relaxed robust formulation, we propose an iterative algorithm based on the block coordinate ascent-descent method. We show through simulation results that the proposed robust design is flexible in the sense that the CI constraints can be relaxed so as to keep a desirable balance between achievable rate and power consumption. Remarkably, the new formulation yields more energy-efficient solutions for appropriate choices of the relaxation parameter, compared to the original problem

  • A Worst-Case Performance Optimization Based Design Approach to Robust Symbol-Level Precoding for Downlink MU-MIMO
    2019
    Co-Authors: Haqiqatnejad Alireza, Shahbazpanahi Shahram, Ottersten Björn
    Abstract:

    This paper addresses the optimization problem of symbol-level precoding (SLP) in the downlink of a multiuser multiple-input multiple-output (MU-MIMO) wireless system while the precoder's output is subject to partially-known Distortions. In particular, we assume a Linear Distortion model with bounded additive noise. The original signal-to-interference-plus-noise ratio (SINR) -constrained SLP problem minimizing the total transmit power is first reformulated as a penalized unconstrained problem, which is referred to as the relaxed robust formulation. We then adopt a worst-case design approach to protect the users' intended symbols and the targeted constructive interference with a desired level of confidence. Due to the non-convexity of the relaxed robust formulation, we propose an iterative algorithm based on the block coordinate ascent-descent method. We show through simulation results that the proposed robust design is flexible in the sense that the CI constraints can be relaxed so as to keep a desirable balance between achievable rate and power consumption. Remarkably, the new formulation yields more energy-efficient solutions for appropriate choices of the penalty parameter, compared to the original problem.Comment: 10 pages, 2 figures, IEEE GlobalSIP 2019 (Accepted

  • Energy-Efficient Multi-Cell Multigroup Multicasting with Joint Beamforming and Antenna Selection
    'Institute of Electrical and Electronics Engineers (IEEE)', 2018
    Co-Authors: Tervo Oskari, Tran Le-nam, Pennanen Harri, Chatzinotas Symeon, Ottersten Björn, Juntti Markku
    Abstract:

    This paper studies the energy efficiency and sum rate trade-off for coordinated beamforming in multi-cell multi-user multigroup multicast multiple-input single-output systems. We first consider a conventional network energy efficiency maximization (EEmax) problem by jointly optimizing the transmit beamformers and antennas selected to be used in transmission. We also account for per-antenna maximum power constraints to avoid non-Linear Distortion in power amplifiers and user-specific minimum rate constraints to guarantee certain service levels and fairness. To be energy-efficient, transmit antenna selection is employed. It eventually leads to a mixed-Boolean fractional program. We then propose two different approaches to solve this difficult problem. The first solution is based on a novel modeling technique that produces a tight continuous relaxation. The second approach is based on sparsity-inducing method, which does not require the introduction of any Boolean variable. We also investigate the trade-off between the energy efficiency and sum rate by proposing two different formulations. In the first formulation, we propose a new metric that is the ratio of the sum rate and the so-called weighted power. Specifically, this metric reduces to EEmax when the weight is 1, and to sum rate maximization when the weight is 0. In the other method, we treat the trade-off problem as a multi-objective optimization for which a scalarization approach is adopted. Numerical results illustrate significant achievable energy efficiency gains over the method where the antenna selection is not employed. The effect of antenna selection on the energy efficiency and sum rate trade-off is also demonstrated.Comment: Accepted for publication in the IEEE Transactions on Signal Processing (17 pages, 14 figures

  • Energy-Efficient Coordinated Multi-Cell Multigroup Multicast Beamforming with Antenna Selection
    'Institute of Electrical and Electronics Engineers (IEEE)', 2017
    Co-Authors: Tervo Oskari, Tran Le-nam, Pennanen Harri, Chatzinotas Symeon, Juntti Markku, Ottersten Björn
    Abstract:

    This paper studies energy-efficient coordinated beamforming in multi-cell multi-user multigroup multicast multiple-input single-output systems. We aim at maximizing the network energy efficiency by taking into account the fact that some of the radio frequency chains can be switched off in order to save power. We consider the antenna specific maximum power constraints to avoid non-Linear Distortion in power amplifiers and user-specific quality of service (QoS) constraints to guarantee a certain QoS levels. We first introduce binary antenna selection variables and use the perspective formulation to model the relation between them and the beamformers. Subsequently, we propose a new formulation which reduces the feasible set of the continuous relaxation, resulting in better performance compared to the original perspective formulation based problem. However, the resulting optimization problem is a mixed-Boolean non-convex fractional program, which is difficult to solve. We follow the standard continuous relaxation of the binary antenna selection variables, and then reformulate the problem such that it is amendable to successive convex approximation. Thereby, solving the continuous relaxation mostly results in near-binary solution. To recover the binary variables from the continuous relaxation, we switch off all the antennas for which the continuous values are smaller than a small threshold. Numerical results illustrate the superior convergence result and significant achievable gains in terms of energy efficiency with the proposed algorithm.Comment: 6 pages, 5 figures, accepted to IEEE ICC 2017 - International Workshop on 5G RAN Desig

Mohse Guizani - One of the best experts on this subject based on the ideXlab platform.

  • Impact of Non-Linear High-Power Amplifiers on Cooperative Relaying Systems
    IEEE Transactions on Communications, 2017
    Co-Authors: Elyes Alti, Mohse Guizani
    Abstract:

    In this paper, we investigate the impact of the high-power amplifier non-Linear Distortion on multiple relay systems by introducing the soft envelope limiter, traveling wave tube amplifier, and solid-state power amplifier to the relays. The system employs amplify-and-forward either fixed or variable gain relaying and uses the opportunistic relay selection with outdated channel state information to select the best relay. The results show that the performance loss is small at low rates; however, it is significant for high rates. In particular, the outage probability and the bit error rate are saturated by an irreducible floor at high rates. The same analysis is pursued for the capacity and shows that it is saturated by a detrimental ceiling as the average signal-to-noise ratio becomes higher. This result contrasts the case of the ideal hardware where the capacity grows indefinitely. Moreover, the results show that the capacity ceiling is proportional to the impairment's parameter and for some special cases the impaired systems practically operate in acceptable conditions. Closed-forms and high SNR asymptotes of the outage probability, the bit error rate, and the capacity are derived. Finally, analytical expressions are validated by the Monte Carlo simulation.