A Full-digital Symbol Rate Estimation Method for an On-die ADC-based Asynchronous PAM-4 Link Eye Monitor

Author(s):  
Sungwon Roh ◽  
Jintae Kim
2016 ◽  
Vol 366 ◽  
pp. 200-204 ◽  
Author(s):  
Sheng Cui ◽  
Wenjuan Xia ◽  
Jin Shang ◽  
Changjian Ke ◽  
Songnian Fu ◽  
...  

2014 ◽  
Vol 536-537 ◽  
pp. 43-48
Author(s):  
Wei Wang ◽  
Xiao Yi Zhang ◽  
Xiao Yun Teng ◽  
Yun Peng Hu

In this paper, aiming at the poor performance of the existing symbol rate estimation methods when SNR is low, we proposed a method based on the timing square which can be simply calculated and applied to MASK/MPSK/MQAM modulated signal, improved the performance of signal symbol rate estimation compared with the existing method. Based on the principle of the timing square, the signal modules were squared to calculate the fourier coefficient modulus corresponding to different sampling ratios. Then the characteristic line was searched in the transform spectrum which contains symbol rate information and obtained an estimation of the symbol rate. The impact of the roll-off factor and the carrier wave was analyzed and solution was proposed in this paper. Simulation results show that the performance of symbol rate estimation of the improved method is better than the original method, the wavelet transform method and the cyclostationary method in low SNR and low roll-off factor environment.


2017 ◽  
Vol 137 (3) ◽  
pp. 547-548
Author(s):  
Ryuichi Mitsuhashi ◽  
Ryosuke Hayasaka ◽  
Shin Satori ◽  
Masami Sasaki

2021 ◽  
Vol 11 (15) ◽  
pp. 6701
Author(s):  
Yuta Sueki ◽  
Yoshiyuki Noda

This paper discusses a real-time flow-rate estimation method for a tilting-ladle-type automatic pouring machine used in the casting industry. In most pouring machines, molten metal is poured into a mold by tilting the ladle. Precise pouring is required to improve productivity and ensure a safe pouring process. To achieve precise pouring, it is important to control the flow rate of the liquid outflow from the ladle. However, due to the high temperature of molten metal, directly measuring the flow rate to devise flow-rate feedback control is difficult. To solve this problem, specific flow-rate estimation methods have been developed. In the previous study by present authors, a simplified flow-rate estimation method was proposed, in which Kalman filters were decentralized to motor systems and the pouring process for implementing into the industrial controller of an automatic pouring machine used a complicatedly shaped ladle. The effectiveness of this flow rate estimation was verified in the experiment with the ideal condition. In the present study, the appropriateness of the real-time flow-rate estimation by decentralization of Kalman filters is verified by comparing it with two other types of existing real-time flow-rate estimations, i.e., time derivatives of the weight of the outflow liquid measured by the load cell and the liquid volume in the ladle measured by a visible camera. We especially confirmed the estimation errors of the candidate real-time flow-rate estimations in the experiments with the uncertainty of the model parameters. These flow-rate estimation methods were applied to a laboratory-type automatic pouring machine to verify their performance.


2013 ◽  
Vol 443 ◽  
pp. 392-396
Author(s):  
Peng Zhou ◽  
Chi Sheng Li

In this paper, we proposed a new symbol rate estimation algorithm for phase shift keying (PSK) and qua drawtube amplitude modulation (QAM) signals in AWGN channel First we constructe a delay-multiplied signal, from which we obtaine the modulated information. Then we calculated the instantaneous autocorrelation of the delay-multiplied signal to pick out the phase jump. To eliminate the restriction of frequency resolution in fast Fourier transform, we performed a Chirp-Z transform to find out the exact spectral line which represente the symbol rate of the signal to be analyzed. Compared with the existing algorithms, it is a simple solution that has a better performance and accuracy in low signal-to-noise-ratio channel conditions. Simulation results show that the probability of relative estimating deviation below 0.1% reaches 100% and the average and standard variance of absolute estimation deviation are at the magnitude of 10-2 when SNR is over 2dB.


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