Browsing by Author "Hung, Ying-Che"

Now showing 1 - 5 of 5

A Real-Time Maximum-Likelihood Heart-Rate Estimator for Wearable Textile Sensors
(2008)
Cheng, Mu-Huo
;
Chen, Li-Chung
;
Hung, Ying-Che
;
Yang, Chang Ming
;
電控工程研究所
This paper presents a real-time maximum-likelihood heart-rate estimator for ECG data measured via wearable textile sensors. The ECG signals measured from wearable dry electrodes are notorious for its susceptibility to interference from the respiration or the motion of wearing person such that the signal quality may degrade dramatically. To overcome these obstacles, in the proposed heart-rate estimator we first employ the subspace approach to remove the wandering baseline, then use a simple nonlinear absolute operation to reduce the high-frequency noise contamination, and finally apply the maximum likelihood estimation technique for estimating the interval or R-R peaks. A parameter derived from the byproduct of maximum likelihood estimation is also proposed as an indicator for signal quality. To achieve the goal of real-time, we develop a simple adaptive algorithm from the numerical power method to realize the subspace filter and apply the fast-Fourier transform (FFT) technique for realization of the correlation technique such that the whole estimator can be implemented in an FPGA system. Experiments are performed to demonstrate the viability of the proposed system.
A Vital Wearing System with Wireless Capability
(2008)
Cheng, Mu-Huo
;
Chen, Li-Chung
;
Hung, Ying-Che
;
Chen, Chien-Nan
;
Yang, Chang Ming
A system with wearable sensors for detecting and sensing vital and physical motion signals such as the ECG, respiration, temperature, sweatiness, three-axis accelerations, and the motions of both knee ankles and elbows is presented. The system is also equipped with a bluetooth transceiver such that the obtained sensor signals can be transmitted to mobile phones or remote computers for either monitoring or post signal processing to extract knowledges or information. The presented system is embedded with signal processing algorithms such as the heart rate, the respiratory period, the body temperature, the degree of sweatiness, and the posture of wearing person are demonstrated. The heart rate and heart rate variation from the measured ECG data are estimated using an adaptive ESPRIT algorithm. This system is highly suitable for applications of remote healthcare and wellness.
Carrier Frequency Offset Estimation Algorithm for OFDM-Based Multi-cell Systems
(2014)
Hung, Ying-Che
;
Peng, Sheng-Yuan
;
Tsai, Shang-Ho (Lawrence)
;
電機工程學系
;
Department of Electrical and Computer Engineering
In this paper, we propose an algorithm for estimating the carrier frequency offset (CFO) in OFDM-based multi cell networks. In 3GPP-LTE single-cell systems, the CFO can be estimated by applying the Schmidt algorithm. However, multi cell interference (MCI) is induced in multi-cell environments; as a result the MCI degrades estimate accuracy. One solution to mitigate MCI may be via properly designing the training sequences. In this paper, we propose a method for generating training sequences with good orthogonality in both time and frequency domain. Therefore, MCI can be effectively suppressed and CFO estimation algorithms designed for single-user or single cell environments can be slightly modified, and applied in multi cell environments. An example is given for showing how to modify the estimation algorithms. Consequently, the computational complexity can be dramatically reduced. Moreover, the training sequences can be applied for detecting cell identity (ID) thanks to its good orthogonality. Simulation results show that the proposed sequences and the CFO estimation algorithms outperform conventional schemes in multi-cell environments.
PAPR Analysis and Mitigation Algorithms for Beamforming MIMO OFDM Systems
(2014-05-01)
Hung, Ying-Che
;
Tsai, Shang-Ho (Lawrence)
;
電機工程學系
;
Department of Electrical and Computer Engineering
Beamforming (or precoding) techniques have been widely adopted in modern MIMO OFDM systems. Using beamforming can significantly improve the receive SNR of OFDM systems. However, the combination of transmit signals after beamforming deteriorates the peak-to-average power ratio (PAPR), which has long been considered a major issue of OFDM systems. High PAPR not only complicates the design of the power amplifier, but also increases power consumption. In this paper, we theoretically analyze the PAPR performance of MIMO OFDM systems that adopt either one of the two popular beamforming schemes, i.e. MRT (maximum ratio transmission) and EGT (equal gain transmission). The analysis considers different numbers of channel taps after sampling. The results may provide important reference for practical designs when evaluating the required power amplifiers and power consumption. Moreover, the theoretical results show that MRT OFDM systems generally perform much worse than EGT OFDM systems in terms of PAPR. Furthermore, motivated from the derived results, PAPR reduction algorithms are proposed for both MRT OFDM and EGT OFDM systems. It is worth to mention that for MRT OFDM systems, the proposed algorithm can improve both PAPR and bit error rate; for EGT OFDM systems, the proposed algorithm improves PAPR while it only slightly degrades bit error rate.
Sequence Designs for Interference Mitigation in Multi-Cell Networks
(2014-01-01)
Hung, Ying-Che
;
Peng, Sheng-Yuan
;
Tsai, Shang-Ho (Lawrence)
;
電機工程學系
;
Department of Electrical and Computer Engineering
We propose a training sequence that can be used at the handshaking stage for multi-cell networks. The proposed sequence is theoretically proved to enjoy several nice properties including constant amplitude, zero autocorrelation, and orthogonality in multipath channels. Moreover, the analytical results show that the proposed sequence can greatly reduce the multi-cell interference (MCI) induced by carrier frequency offset (CFO) to a negligible level. Therefore, the CFO estimation algorithms designed for single-user or single-cell environments can be slightly modified, and applied in multi-cell environments; an example is given for showing how to modify the estimation algorithms. Consequently, the computational complexity can be dramatically reduced. Simulation results show that the proposed sequences and the CFO estimation algorithms outperform conventional schemes in multi-cell environments.