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Telecommunications and Radio Engineering
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ISSN 印刷: 0040-2508
ISSN オンライン: 1943-6009

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Telecommunications and Radio Engineering

DOI: 10.1615/TelecomRadEng.v78.i15.30
pages 1333-1344

A NOVEL IMPLEMENTATION OF SNR ESTIMATION BASED ON LARGE SCALE PROGRAMMABLE LOGIC CIRCUITS

W. Wang
Qingdao University, 308 Ningxia Road, Qingdao, Shangdong, P.R. of China, 266071
H. Zhang
Qingdao University, 308 Ningxia Road, Qingdao, Shangdong, P.R. of China, 266071
Zh. Shen
Qingdao University, 308 Ningxia Road, Qingdao, Shangdong, P.R. of China, 266071
P. Wang
Qingdao University, 308 Ningxia Road, Qingdao, Shangdong, P.R. of China, 266071
G. Ren
Qingdao University, 308 Ningxia Road, Qingdao, Shangdong, P.R. of China, 266071
S. Wang
Qingdao University, 308 Ningxia Road, Qingdao, Shangdong, P.R. of China, 266071
Yu. Zheng
Qingdao University, 308 Ningxia Road, Qingdao, Shangdong, P.R. of China, 266071
S. N. Shulga
V. Karazin National University of Kharkiv, 4 Svobody Sq., Kharkiv 61022, Ukraine

要約

The signal-to-noise ratio (SNR) is a major technical parameter to value the quality of communication system. The research of SNR estimator is still staggering in algorithm improvement and software implementation. In this paper, we proposed an effective method to implement SNR estimator based on hardware logic circuit by calculating the mean and variance of the demodulated envelope signal. The proposed SNR can reflect the channel status in real time, because calculation of data streams and reading/writing buffer can be execute without time intervals via alternating periods of time control. The testing results show that the SNR estimator has a good response to the channel condition under the interference of different noise power. According to the results, it can be found that the approach we proposed can be applied to the physical layer of the communication system, and the method has the significant merits for many modulation schemes and channel models.

参考

  1. Alvarez-Diaz, M. and Lopea-Valcarce, R., (2010) SNR Estimation for Multilevel Constellations Using Higher-Order Moments, IEEE Transactions on Signal Processing: A publication of the IEEE Signal Processing Society, 58, pp. 1515-1526, 10.1109/TSP.2009.2036069.

  2. Moazzeni, T., Amei, A., and Ma, J., (2012) On a New Approach to SNR Estimation of BPSK Signals, International Journal of Electronics and Telecommunications, 58, pp. 273-278, 10.2478/v10177-012-0038-y.

  3. Hao, M.J., Tsai, W.L., and Tsai, Y.C., (2013) Squared envelope-based SNR estimation, Journal of the Chinese Institute of Engineers, 36, pp. 810-818, 10.1080/02533839.2012.740594.

  4. Muhammad, A.R. and Arshad, H., (2016) Maximum Likelihood SNR Estimation of Hyper Cubic Signals Over Gaussian Channel, IEEE Communications Letters, 20, pp. 45-48, 10.1109/LTOMM.2015.2498146.

  5. Krishnamurthy, S.D. and Sabat, S.L., (2016) Blind SNR estimation for M-ARY Frequency Shift Keying Signal using Covariance Technique, AEU-International Journal of Electronic and Communication, 70, pp. 1388-1394, 10.1016/j.aeue.2016.07.012.

  6. Moazzeni, T., Tao, J.Y., and Ding, C.T., (2016) Data-classification-based SNR estimation for linearly modulated signals, Computers and Electrical Engineering, 56, pp. 85-95, 10.1016/j.compeleceng.2016.09.017.

  7. Hu, L.X., Jun, L.A., Fei, P.X., and Guang, W., (2015) EM-based SNR estimator for faster-than- Nyquist signaling system, Electronics Letters, 51, pp. 2051-2053, 10.1049/el.2015.1517.

  8. Singh, I., Kalyani, S., and Giridhar, K., (2015) A Practical Compressed Sensing Approach for Channel Estimation in OFDM Systems, IEEE Communications Letters, 19, pp. 2146-2149, 101109/LCOMM.2015.2487265.

  9. Lin, D.W., (2018) An Analysis of the Performance of ML Blind OFDM Symbol Timing Estimation, IEEE Transactions on Signal Processing, 66, pp. 5324-5337, 10.1109/TSP.2018.2868043.

  10. Hansen, T.L., Jorgensen, P.B., Badiu, M., and Fleury, B.H., (2018) An Iterative Receiver for OFDM With Scarcity-Based Parametric Channel Estimation, IEEE Transactions on Signal Processing, 66, pp. 5454-5469, 10.1109/TSP.2018.2868314.

  11. Ziabakhsh, S., Gagnon, G., and Roberts, G.W., (2018) The Peak-SNR Performances of Voltage-Mode versus Time-Mode Circuits, IEEE Transactions on Circuits and Systems II-Express Briefs, 65, pp. 1869-1873, 10.1109/TCSII.2018.2817504.


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