Digital Signal Processing |
Russian |
Digital processing of non-linear signal distortion in a software-defined radio (SDR)
Abstract 2. R. Marsalek, P. Jardin, and G. Baudoin, “From post-distortion to predistortion for power amplifiers linearization,” IEEE Commun. Lett., vol. 7, no. 7, pp. 308–310, Jul. 2003. 3. A. N. D’Andrea, V. Lottici, and R. Reggiannini, “RF power amplifier linearization through amplitude and phase predistortion,” IEEE Trans. Commun., vol. 44, no. 11, pp. 1477–1484, Nov. 1996. 4. D. Lei, R. Raich, and G. T. Zhou, “A Hammerstein predistortion linearization design based on the indirect learning architecture,” in Proc. Int. IEEE ICASSP, May 2002, vol. 3, pp. III-2689–III-2692. 5. G. Baudoin, P. Jardin, and R. Marsalek, “Power amplifier linearisation using predistortion with memory,” in Proc. 13th Int. Czech—Slovak Scientific Conf. RADIOELEKTRONIKA, Brno, Czech Republic, May 6–7, 2003, pp. 193–196. 6. L. Ding, G. T. Zhou, D. R. Morgan, Z. Ma, J. S. Kenney, J. Kim, and C. R. Giardina, “A robust digital baseband predistorter constructed using memory polynomials,” IEEE Trans. Commun., vol. 52, no. 1, pp. 159–165, Jan. 2004. 7. A. Zhu and T. J. Brasil, “An adaptive Volterra predistorter for the linearization of RF high power amplifiers,” in Proc. Conf. IEEE MTT, 2002, pp. 461–464. 8. Y. Ding, H. Ohmori, and A. Sano, “Adaptive predistortion for high power amplifier with linear dynamics,” in Proc. IEEE Int. MidWest Symp. Circuits and Syst., Hiroshima, Japan, Jul. 2004, pp. 121–124. 9. V. Y. Tikhonov and Y. S. Shinakov, "COMPENSATION OF NONLINEAR DISTORTION IN INERTIAL DEVICES," 2018Systems of Signal Synchronization, Generating and Processing in Telecommunications (SYNCHROINFO), Minsk, 2018, pp. 1-4. 10. A. G. Timoshenko, N. K. Osipenko, A. A. Bakhtin and E. A. Volkova, "5G Communication Systems Signal Processing PAPR Reduction Technique," 2018Systems of Signal Synchronization, Generating and Processing in Telecommunications (SYNCHROINFO), Minsk, 2018, pp. 1-4. 11. NI USRP-2943 Software Defined Radio Reconfigurable Device, https://www.ni.com/pdf/manuals/374193d.pdf
Efficiency of the non-threshold spread spectrum signal searching procedure in case of quantization of the incoming observations
Keywords: n-bit quantization, quantization noise, spread spectrum signal searching, correct searching probability, cross-correlation function. References 2. Sistemy svyazi s shumopodobnymi signalami (Communication systems with noise-like signals) / L.E.Varakin. M.: Radio i svyaz'. 1985. 384 p. 3. GLONASS. Printsipy postroeniya i funktsionirovaniya (GLONASS. Design Principles and Functioning) / Ed. by A.I. Perov, V.N. Kharisov. Ì.: Radiotekhnika. 2010. 800 p. 4. Springer Handbook of Global Navigation Satellite Systems / Eds. P.J.G. Teunissen, O. Montenbruck. Springer International Publishing. 2017. 1327 p. 5. Statisticheskaya teoriya priema slozhnykh signalov (Statistical theory of complex signals receiving) / G.I. Tuzov. M.: Sov. Radio. 1977. 400 p. 6. Cifrovaja obrabotka signalov: ucheb. posobie. 2-e izd. pererab. i dop. (Digital signal pro-cessing: textbook. 2nd ed. rev. and add.) / A.S. Glinchenko. Krasnojarsk: IPC KGTU. 2005. 482 p. 7. Daigle J.N., Xiang N. A specialized fast cross-correlation for acoustical measurements using coded sequences // J. Acoust. Soc. Am. V. 119. no 1, January 2006. pp. 330–335. 8. Cifrovaja obrabotka signalov (Digital signal processing) / A.B. Sergienko. SPb.: Piter. 2003. 604 p. 9. Kuzmin E.V., Zograf F.G. Povyshenie verojatnosti pravil'nogo poiska shumopodobnogo signala po vremeni zapazdyvanija na fone tonal'noj pomehi (Enhancement of the probability of spread-spectrum signal correct searching in case of narrow-band interference) // Uspekhi sov-remennoi radioelektroniki (Achievements of Modern Radioelectronics). 2016. no 11. pp. 137–140. 10. A statistical theory for GNSS signal acquisition. PhD thesis / D. Borio. Politecnico di Torino. Marzo. 2008. 291 p. 11. Understanding GPS: principles and applications / Eds. E. Kaplan, C. Hegarty. 2nd ed. ARTECH HOUSE. 2006. 703 p. Using Zadov - Chu sequences for synchronization along the correlation curve of the cyclic prefix OFDM-symbols LTE technology
Abstract Initial synchronization of the database with the user includes standard steps:
In this paper, we study ways to improve synchronization efficiency along the correlation curve of the cyclic prefix. This is the first stage of synchronization, which allows you to get a temporary binding to the borders of the OFDM symbol and the beginning of the slot. When passing a communication channel with Rayleigh fades, the information data during the duration of the OFDM symbol, especially with "fast" fades, may change so much that the CP and the final interval of the symbol from which the information was copied when transmitting the frame, do not form an explicit peak of the mutual correlation function (VCF). The author suggests using as cyclic prefixes OFDM symbols located in the Central frequency band and not involved in information exchange with other subscribers, short sequences of ZC that are not used in the group of standards allocated in the 36th series of 3GPP technical specifications. To test the assumption of increasing the efficiency of the synchronization process along the CP correlation curve when using short ZC sequences instead of CP bit data, simulations were performed in the MATLAB operating environment for characters with CP from complex sequences ZC(5,9), ZC(9,19), ZC(15,31), ZC (25,37) and random complex bit sequences with the same number of n elements. As a result, the energy gain values are obtained when using ZC(u,n) to form the CP of the OFDM symbol within (1.67...2.94) dB for sequences with the number of elements 9,19,31,37, considered in this paper.
2. Helgor A. L., Popov E. A -. LTE mobile data technology: a tutorial. SPb.: Polytechnic University press, 2011. 204 s 3. Sesia S., Toufik I., Baker M. - LTE – The UMTS Long Term Evolution: From Theory to Practice. — Torquay, UK: John Wiley & Sons, 2009. 4. ETSI TS 136 211 V10.0.0 (2011-01). Technical Specification. - European Telecommunications Standards Institute, 2011- 104ñ. - LTE; Evolved Universal Terrestrial Radio Access (E-UTRA); Physical channels and modulation (3GPP TS 36.211 version 10.0.0 Release 10) 5. The physical layer of LTE [Electronic resource]. - Access mode: http://www.russianelectronics.ru/leader-r/review/2187/doc/53411/ (accessed 19.12.2019). 6. Bykov V. V., al-Mershahi S. M. improvement of synchronization of OFDM signals in DVB-T2 system / / T-Comm: telecommunications and transport. - 2016. - Volume 10. - No. 6. Pp. 21-26. 7. Kiseleva T. P.-Investigation of the properties of the cyclic autocorrelation function of the Zadov – Chu sequence depending on the quantization characteristics of the sequence elements.- Digital signal processing, No. 4,2018. 40-44C.
Abstract Thus, the proposed theoretical research method makes it possible to obtain analytical formulas that determine the dependence of the reliability of receiving messages in satellite communication systems on their system parameters (on the modulation parameters of the transmitted signals, the type and parameters of the codes used in the SCS). The next part of the article presents the results of a study of the possibilities of using optimal multidimensional surface-spherical signal ensembles. These results showed that systems in which multidimensional signals are used to transmit messages in their characteristics are significantly superior to systems created in accordance with the standard DVB-S2. References 2. U. Reimers, A. Morello, DVB-S2, the second generation standard for satellite broadcasting and unicasting, Int. J. Satell. Commun. Networks, 2004; V. 22. 3. Mustafa Eroz, Feng-Wen Sun and Lin-Nan Lee. DVB-S2 low density parity check codes with near Shannon limit performance. Int. J. Satell. Commun. Network, 2004; V. 22 4. EBU Tech 3348 r4, Frequency and network planning aspects of DVB-T2, version 4.1.1. Geneva, October, 2014. 5. Shannon C. Probability of error for optimal codes in Gaussian channel. Bell System Techn. J., May, 1959. 6. Vlastimil Benovsky, Eurovision. DVB-S extension higher spectral efficiency. WBU-ISOG Forum Los Angeles, May, 2013
Abstract The detection of correlated signals against the uncorrelated random processes using discrete samples of finite volume arises in many technical applications. A method of correlation detection of received signals is known, when two samples of observations received at two carrier frequencies are multiplied, their product is accumulated and the module of the accumulated product is compared with a fixed threshold [1]. The resulting estimate of the envelope of the inter-frequency correlation coefficient is compared with the threshold, on the basis of which a decision is made about the presence of the received correlated signals. Although this method allows effective detection of correlated signals, however, this method has a disadvantage, which is in the lack of stabilization of false alarms when the noise level changes, against which the detection is performed. In order to ensure the stabilization of false alarms in correlation detection, a method is proposed that includes forming an estimate of the correlation coefficient module based on samples of observations taken at two carrier frequencies and comparing this estimate with a threshold that is made adaptive in order to stabilize false alarms when the noise level changes, formed as the product of a coefficient that determines the probability of a false alarm on the total noise power estimate at two carrier frequencies. As a rule, their analysis of the effectiveness of such devices was performed using statistical modeling, since the nonlinear multiplication operation leads to a change in the type of distributions at the output of these devices and significantly complicates their analysis using analytical calculations, especially for small observation samples and low probability of false alarms. That is why numerical study in the first of time is presented analytically for false alarm probability. A correlator with an adaptive threshold was compared with a correlator with a fixed threshold by calculating the characteristics of detecting a fluctuating correlated signal. This was done using simulations in the MATLAB system. The results show that the efficiency in the threshold signal for the probability of correct detection is 0.5 and the probability of false alarm of 0.1 and 0.0001 slightly higher in correlator without stabilization false alarm. This is a kind of payment for the invariant properties of the adaptive correlator to changes in noise power, providing stabilization of the probability of a false alarm at the output. References 2. Bartenev V. G., Bartenev M. V. Method for finding probabilistic characteristics at the output of nonlinear systems / / Digital signal processing. 2013. No. 4.pp. 42-44 3. Potemkin V. G. " Matlab reference Guide” Data analysis and processing. http://matlab.exponenta.ru/ml/book2/chapter8/
Acoustic and language modeling in end-to-end speech recognition systems
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Watanabe S., Hori T., Karita S. at al. ESPnet: End-to-End Speech Processing Toolkit // arXiv:1804.00015v1 [cs.CL] 2018, URL: www.arxiv.org/pdf/1804.0001.pdf. 19. Miao Y., Gowayyed M., Metze F. at al. EESEN: End-to-End Speech Recognition using Deep RNN Models and WFST-based Decoding // arXiv:1507.08240v3 [cs.CL], 2015. URL: www.arxiv.org/pdf/1507.08240.pdf. 20. Graves A., Mohamed A.-R. and Hinton G. Speech Recognition with Deep Recurrent Neural Networks // arXiv:1303.5778v1 [cs.NE], 2013. URL: www.arxiv.org/pdf/1303.5778.pdf. 21. Dong L., Zhou S.,. Chen W., Xu B. Extending Recurrent Neural Aligner for Streaming End-to-End Speech. Recognition in Mandarin // arXiv:1806.06342v2 [cs.SD] 2019, URL: www.arxiv.org/pdf/1806.06342.pdf. 22. Zeghidour N., Xu Q., Liptchinsky V. , at al. Fully Convolutional Speech Recognition // arXiv:1812.06864v2 [cs.CL] 2019, URL: www.arxiv.org/pdf/1812.06864.pdf. 23. Pratap V., Hannun A., Xu Q. 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The accuracy of the method was verified by sequential enumeration of all possible angles of a data cloud rotation in a given coordinate system.
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