scholarly journals Effects of Rounding and Truncating Methods of Quantization Error and SQNR for Sine Signal

2020 ◽  
Vol 1 (1) ◽  
pp. 08-12
Author(s):  
Alaaldin Hasso ◽  
Karwan Jacksi

Within the Analog to Digital Conversion (ADC), quantization noise is a duplicate of a Quantization Error (QE) which is introduced by quantization. In signal processing and telecommunication systems, the noise is non-linear and depends on the signal type. During the analog, Sine signal converts to the digital (ADC) process, the two methods are used Rounding and Truncating in-order to eliminate the error produced in the digitization process. The rounding method quantize assigns each sample of sine signal to the nearest quantization level. However, making the Truncating would have assigned each sample of sine signal to the quantization level below it. This paper compares the rounding and truncating methods of QE for sine signal, signal to quantization noise ratio, correlation coefficient, and regression equation of a line for both methods. Then, it calculates the residual sum of squares and compares it to the regression equations of the lines.

2010 ◽  
Vol 7 (3-4) ◽  
Author(s):  
О. Давлетьянц ◽  
О. Борейчук ◽  
О. Василенко ◽  
О. Євсеєв ◽  
В. Кривоус

Author(s):  
S. R. Heister ◽  
V. V. Kirichenko

Introduction. The digital representation of received radar signals has provided a wide range of opportunities for their processing. However, the used hardware and software impose some limits on the number of bits and sampling rate of the signal at all conversion and processing stages. These limitations lead to a decrease in the signal-to-interference ratio due to quantization noise introduced by powerful components comprising the received signal (interfering reflections; active noise interference), as well as the attenuation of a low-power reflected signal represented by a limited number of bits. In practice, the amplitude of interfering reflections can exceed that of the signal reflected from the target by a factor of thousands.Aim. In this connection, it is essential to take into account the effect of quantization noise on the signal-tointerference ratio.Materials and methods. The article presents expressions for calculating the power and power spectral density (PSD) of quantization noise, which take into account the value of the least significant bit of an analog-to-digital converter (ADC) and the signal sampling rate. These expressions are verified by simulating 4-, 8- and 16-bit ADCs in the Mathcad environment.Results. Expressions are derived for calculating the quantization noise PSD of interfering reflections, which allows the PSD to be taken into account in the signal-to-interference ratio at the output of the processing chain. In addition, a comparison of decimation options (by discarding and averaging samples) is performed drawing on the estimates of the noise PSD and the signal-to-noise ratio.Conclusion. Recommendations regarding the ADC bit depth and sampling rate for the radar receiver are presented.


Author(s):  
Neha Jain ◽  
Nir Shlezinger ◽  
Yonina C. Eldar ◽  
Anubha Gupta ◽  
Vivek Ashok Bohara

2021 ◽  
Vol 32 (3) ◽  
Author(s):  
Ruo-Shi Dong ◽  
Lei Zhao ◽  
Jia-Jun Qin ◽  
Wen-Tao Zhong ◽  
Yi-Chun Fan ◽  
...  

1993 ◽  
Vol 7 (4) ◽  
pp. 408 ◽  
Author(s):  
James R. Matey ◽  
M.J. Lauterbach

2017 ◽  
Author(s):  
Evgenii S. Kolodeznyi ◽  
Innokenty I. Novikov ◽  
Andrey V. Babichev ◽  
Alexander S. Kurochkin ◽  
Andrey G. Gladyshev ◽  
...  

2021 ◽  
pp. 127440
Author(s):  
Hao Chi ◽  
Qiulin Zhang ◽  
Shuna Yang ◽  
Bo Yang ◽  
Yanrong Zhai ◽  
...  

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