LTE Downlink Channel Estimation Base on DCT

2014 ◽  
Vol 1049-1050 ◽  
pp. 1906-1910
Author(s):  
Yong Wang ◽  
Pan Fei Wu ◽  
Guo Qing Xiong
Keyword(s):  
Channel Estimation ◽  
Estimation Method ◽  
Estimation Algorithm ◽  
Frequency Component ◽  
High Frequency Component ◽  
Spectral Leakage ◽  
High Data ◽  
Rate Transmission ◽  
Better Than

The long term evolution (LTE) system is a high data rate transmission system. And the channel estimation is critical to it. In this paper, a novel channel estimator on the basis of Discrete Cosine Transform (DCT) method is presented for LTE. It can mitigate the aliasing error caused by spectral leakage well and is applicable for non-integer sampled channel because DCT can reduce the high frequency component. Its performance is much better than LS method and close to LMMSE method, and the complexity is much simpler than LMMSE. The simulation results show that the DCT-based method is superior to the traditional channel estimation algorithm in the multi-path Rayleigh fading channel which is a available and effective channel estimation method.

A Modified DFT-Based Channel Estimation Method for OFDM-RoF System

2014 ◽  
Vol 989-994 ◽  
pp. 3521-3525
Author(s):  
Li Qun Huang ◽  
Peng Zhang ◽  
Guang Yang
Keyword(s):  
Channel Estimation ◽  
High Frequency ◽  
Estimation Method ◽  
Frequency Component ◽  
High Frequency Component ◽  
Improved Method ◽  
Frequency Components ◽  
Influence Of Noise ◽  
Changing Rate ◽  
Better Than

In this paper, we present a modified discrete Fourier transform (DFT)-based channel estimation method. The conventional DFT-based method will produce additional high frequency component in the channel impulse response, and degrade the accuracy of channel estimation. The modified algorithm can eliminate additional high frequency components by extending the LS estimate in frequency domain with a symmetric signal of its own, and selects the useful paths by calculating the changing rate of energy. Thus, the proposed algorithm become more accurate. The simulation results show the new algorithm can reduce the influence of noise on channel estimation efficiently, and the performance of the improved method is better than the LS and conventional DFT algorithm.

Research on Uplink Channel Estimation Method in TD-LTE System

2011 ◽  
Vol 135-136 ◽  
pp. 847-851
Author(s):  
Cui Zhen Sun ◽  
Zhao Hua Zeng
Keyword(s):  
Channel Estimation ◽  
Estimation Method ◽  
Data Rate ◽  
Pilot Signal ◽  
High Data ◽  
System A ◽  
Term Evolution ◽  
Simulation Results ◽  
Evolution Scheme

LTE is a long term evolution scheme of 3GPP, as a using extensively communication standards, it has higher data rate and higher quality. Channel estimation plays a quite important role in the LTE system which requires the high data rate and quality. In the article, based on the analysis of the LS and MMSE algorithms of the LTE system, a advised algorithm is adopted. The pilot signal is processed before the channel estimation by reducing noise in time domain. The simulation results demonstrate that the advised algorithm is a preferable choice in estimation performance, simultaneously; the advised has obviously reduced the algorithm complexity.

An Improved Channel Estimation Method for LTE Uplink

2012 ◽  
Vol 433-440 ◽  
pp. 3847-3851
Author(s):  
Zhao Hua Zeng ◽  
Li Jun Xue ◽  
Qian Zhao
Keyword(s):  
Channel Estimation ◽  
Estimation Method ◽  
Estimation Algorithm ◽  
Long Term Evolution ◽  
Evolution System ◽  
Term Evolution ◽  
Air Interface ◽  
Increasing Demand ◽  
3Gpp Long Term Evolution

As users of the increasing demand for multimedia services, 3GPP long term evolution system proposed the Long Term Evolution, LTE. LTE is the most important improvements with a new air interface technology to provide users with higher peak rates. Accurate channel estimation is to ensure the transmission quality of LTE system and the key to its advantages. In pursuit of lower bit error rate (BER), this paper based on pilot signals TDD LTE system on the uplink channel estimation algorithm. Use LS algorithm, MMSE algorithm and svd algorithm. Based on these three improved svd algorithm, it gave the simulation results.

scholarly journals Changes in Heart Rate Variability of Depressed Patients after Electroconvulsive Therapy

2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
Erica B. Royster ◽  
Lisa M. Trimble ◽  
George Cotsonis ◽  
Brian Schmotzer ◽  
Amita Manatunga ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Depressive Symptoms ◽  
Electroconvulsive Therapy ◽  
Low Frequency ◽  
Frequency Component ◽  
High Frequency Component ◽  
Acute Changes ◽  
The Impact

Objective. As few, small studies have examined the impact of electroconvulsive therapy (ECT) upon the heart rate variability of patients with major depressive disorder (MDD), we sought to confirm whether ECT-associated improvement in depressive symptoms would be associated with increases in HRV linear and nonlinear parameters. Methods. After providing consent, depressed study participants (n=21) completed the Beck Depression Index (BDI), and 15-minute Holter monitor recordings, prior to their 1st and 6th ECT treatments. Holter recordings were analyzed for certain HRV indices: root mean square of successive differences (RMSSD), low-frequency component (LF)/high-frequency component (HF) and short-(SD1) versus long-term (SD2) HRV ratios. Results. There were no significant differences in the HRV indices of RMSDD, LF/HF, and SD1/SD2 between the patients who responded, and those who did not, to ECT. Conclusion. In the short term, there appear to be no significant improvement in HRV in ECT-treated patients whose depressive symptoms respond versus those who do not. Future studies will reveal whether diminished depressive symptoms with ECT are reliably associated with improved sympathetic/parasympathetic balance over the long-term, and whether acute changes in sympathetic/parasympathetic balance predict improved mental- and cardiac-related outcomes.

Frequency-Offset Estimation of Satellite-Based AIS Signals

2013 ◽  
Vol 765-767 ◽  
pp. 2732-2735 ◽  
Author(s):  
Xiao Juan Liu ◽  
She Xiang Ma ◽  
Xin Meng
Keyword(s):  
Carrier Frequency Offset ◽  
Estimation Method ◽  
Estimation Algorithm ◽  
Frequency Offset ◽  
Smoothing Function ◽  
Automatic Identification ◽  
Identification System ◽  
Frequency Offset Estimation ◽  
Carrier Frequency Offset Estimation ◽  
Better Than

Aiming at satellite-based Automatic Identification System (AIS) signals, a blind carrier frequency-offset estimation method was investigated on AWGN channels. Estimation algorithm that is based on the autocorrelation function and a suitable smoothing function was deduced to estimate the frequency-offset. Simulation results show that its accuracy is better than the earlier methods and reduced the computational complexity.

Nocturnal Heart Rate Variability Following Supramaximal Intermittent Exercise

2009 ◽  
Vol 4 (4) ◽  
pp. 435-447 ◽  
Author(s):  
Al Haddad Hani ◽  
Paul B. Laursen ◽  
Ahmaidi Said ◽  
Buchheit Martin
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
High Efficiency ◽  
Slow Wave Sleep ◽  
Intermittent Exercise ◽  
Frequency Component ◽  
High Frequency Component ◽  
Exercise Heart Rate ◽  
Supramaximal Exercise

Purpose:To assess the effect of supramaximal intermittent exercise on long-term cardiac autonomic activity, inferred from heart rate variability (HRV).Methods:Eleven healthy males performed a series of two consecutive intermittent 15-s runs at 95% VIFT (i.e., speed reached at the end of the 30-15 Intermittent Fitness Test) interspersed with 15 s of active recovery at 45% VIFT until exhaustion. Beat-to-beat intervals were recorded during two consecutive nights (habituation night and 1st night) before, 10 min before and immediately after exercise, as well as 12 h (2nd night) and 36 h (3rd night) after supramaximal intermittent exercise. The HRV indices were calculated from the last 5 min of resting and recovery periods, and the first 10 min of the first estimated slow wave sleep period.Results:Immediate post-supramaximal exercise vagal-related HRV indices were significantly lower than immediate pre-supramaximal exercise values (P < .001). Most vagal-related indices were lower during the 2nd night compared with the 1st night (eg, mean RR intervals, P = .03). Compared with the 2nd night, vagal-related HRV indices were significantly higher during the 3rd night. Variables were not different between the 1st and 3rd nights; however, we noted a tendency (adjusted effect size, aES) for an increased normalized high-frequency component (P = .06 and aES = 0.70) and a tendency toward a decreased low-frequency component (P = .06 and aES = 0.74).Conclusion:Results confirm the strong influence of exercise intensity on short- and long-term post exercise heart rate variability recovery and might help explain the high efficiency of supramaximal training for enhancing indices of cardiorespiratory fitness.

Improved Algorithm Based on the DFT Transform Channel Estimation and Threshold Filtering

2013 ◽  
Vol 391 ◽  
pp. 536-539
Author(s):  
Chao Ma ◽  
Chun Xian Xiao ◽  
Jiang Zhu
Keyword(s):  
Channel Estimation ◽  
Impulse Response ◽  
Time Domain ◽  
Estimation Algorithm ◽  
Cyclic Prefix ◽  
Noise Variance ◽  
Traditional Algorithm ◽  
The Impact ◽  
Better Than ◽  
Improved Algorithm

In channel estimation, the complexity of the DFT-based channel estimation algorithm is lower than the MMSE algorithm, and the DFT-based algorithm performs better than the LS algorithm. However, due to that the traditional algorithms simply considered all the samples to be useful channel impulse response, ignoried the effect of noise. Therefore, the algorithm could be improved. This paper presents an improved algorithm based on twice noise estimation theory. The algorithm uses the sequence of points other than the cyclic prefix length to estimate the noise variance firstly, and then use the estimated noise variance to distinguish the noise samples within the cyclic prefix length. The computation of the new noise variance and noise mean through the new noise points as a threshold filters the impulse response of the channel in time domain and eliminates the impact of noise on the system further. The simulation result shows that the improved algorithm performs better than the traditional algorithm.

scholarly journals Assessment of autonomic function by long-term heart rate variability: beyond the classical framework of LF and HF measurements

2021 ◽  
Vol 40 (1) ◽  
Author(s):  
Junichiro Hayano ◽  
Emi Yuda
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Autonomic Function ◽  
Low Frequency ◽  
Frequency Component ◽  
High Frequency Component ◽  
Short Term ◽  
Heart Rate Turbulence ◽  
Free Running

AbstractIn the assessment of autonomic function by heart rate variability (HRV), the framework that the power of high-frequency component or its surrogate indices reflects parasympathetic activity, while the power of low-frequency component or LF/HF reflects sympathetic activity has been used as the theoretical basis for the interpretation of HRV. Although this classical framework has contributed greatly to the widespread use of HRV for the assessment of autonomic function, it was obtained from studies of short-term HRV (typically 5‑10 min) under tightly controlled conditions. If it is applied to long-term HRV (typically 24 h) under free-running conditions in daily life, erroneous conclusions could be drawn. Also, long-term HRV could contain untapped useful information that is not revealed in the classical framework. In this review, we discuss the limitations of the classical framework and present studies that extracted autonomic function indicators and other useful biomedical information from long-term HRV using novel approaches beyond the classical framework. Those methods include non-Gaussianity index, HRV sleep index, heart rate turbulence, and the frequency and amplitude of cyclic variation of heart rate.

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