A Gaussianization-based performance enhancement approach for coded digital PCM/FM

A Gaussianization-based performance enhancement approach for coded digital PCM/FM

Xinglai Wang Xiaoqian Chen  Yan Wang  Guojiang Xia 

College of Aerospace Science and Engineering, National University of Defense Technology, Changsha 410073, China

Beijing Institute of Astronautical Systems Engineering, Beijing 100076, China

Corresponding Author Email: 
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The BER performance of the coded digital PCM/FM telemetry system is dependent on the accuracy of the input likelihood metrics, which are greatly influenced by the click noise. This paper presents a Gaussianization approach to lessen the influence of the click noise. The outputs of the limiter/discriminator are first modeled by a Gaussian mixture model, whose parameters are estimated by the expectation maximization algorithm, and then the amplitudes are adjusted by a proposed Gaussianization filter so that they become more accurate through likelihood metrics. When (64, 57)2 TPC is applied, simulation results show the coding gain is 0.8dB at 10-4 BER level.


PCM/FM, Limiter/Discriminator, Gaussianization, Turbo Product Codes, LDPC

1. Introduction
2. Review of Coded Digital PCM/FM System
3. Gaussianization Approach
4. The Proposed Gaussianzation Scheme
5. Simulation Results
6. Conclusions

[1] Pawula R.F. (1999). Improved performance of coded digital FM, IEEE Transactions on Communications, Vol. 47, No. 11, pp. 1701-1708. DOI: 10.1109/26.803505

[2] David T. (2003). PCM/FM performance enhancement using reed Solomon channel coding, IEEE Aerospace Conference Proceedings 2003, Big Sky, pp. 1337-1346.

[3] Geoghegon M. (2003). Experimental results for PCM/FM, Tier 1 SOQPSK and Tier 2 multi-h CPM with turbo-product codes, Proceedings of International Telemetry Conference 2003, Las Vegas, pp. 465-468.

[4] Wang L. (2004). Using LDPC codes to enhance the performance of FM-DCSK, the 47th IEEE International Midwest Symposium on Circuits and Systems 2004, pp. I-401-I-404.

[5] Rice S.O. (1963). Noise in FM receiver, Time Series Analysis, M. Rosenblatt, Ed. Wiley, New York, pp. 395-422.

[6] Kouwenhoven L. (1997). A new simple design model for FM demodulators using soft-limiters for click noise suppression, IEEE International Symposium on Circuits and Systems 1997, pp. 265-268. DOI: 10.1109/ISCAS.1997.608696

[7] Zhao Y.X. (1995). Gaussian mixture density modelling of non-Gaussian source for autoregressive process, IEEE Transactions on Signal processing, Vol. 43, No. 4, pp. 894-903.

[8] Verbout M. (1998). Parameter estimation for autoregressive Gaussian-mixture processes: the EMAX algorithm, IEEE Transactions on Signal processing, Vol. 46, No. 10, pp. 2744-2756. DOI: 10.1109/ICASSP.1997.604632

[9] Wang P.B. (2010). G-Filter's Gaussianization function for interference background, 2010 International Conference on Signal Acquisition and Processing, pp. 76-79.

[10] Pyndiah R.M. (1998). Near-optimum decoding of product codes: block turbo codes, IEEE Transactions on Communications, Vol. 46, No. 8, pp. 1003-1010. DOI: 10.1109/GLOCOM.1994.513494

[11] Low Density Parity Check Codes for Use in Near-Earth and Deep Space Applications (2007). CCSDS.