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“Digital
Signal Processing” No. 1-2018 |
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Hyperphase Modulation- the optimal method of message transmission
N.A. Bykhovskiy
PhD, Professor at MTUSI, e-mail: bykhmark@gmail.com
Keywords: A new Method for Digital Modulation- Hyperphase Mod.
Abstract
Author proposes a new method of message transmission by using Hyperphase Modulation. In HPM, all signal points (SP) of the corresponding signal ensemble (SE) are located on the surface of N-dimensional sphere and the distance (d) between the closest SPs with the increase in N dimension is measured according to the formula d≈√N. Such SE, as was shown by Shannon in 1959, is optimal given large enough value of N and allows to ensure the transmission of signals in the telecommunication channel with a limited frequency band with a set speed of transmission and maximum possible noise immunity.
The article explores dependence of the speed of message transmission with the use of HPM on minimal phase distance between SPs in this multidimensional SE. It is shown that by applying HPM method it is possible to achieve a substantial net energy gain as compared with other two-dimensional SEs, such as QAM. Such gain grows with the increase of N and can be quite significant.
The author develops an effective, from a calculation standpoint, coding algorithm of the transmitted message – by using the transmitted message number (m) to calculate phase coordinates of signals’ SPs. The values of those coordinates are then used for formation of transmitted signals with HPM. The major difference of this coding method from those that are used in modern telecommunication systems is that that method, while improving noise immunity, it does not contribute additional (excessive) symbols into a sequence of informational symbols of a transmitted message.
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Recurrent neural networks as behavioral models of nonlinear dynamic systems
E.B. Solovyeva , e-mail: selenab@hotbox.ru
Saint-Petersburg Electrotechnical University “LETI”, Russia, St. Petersburg
Keywords: : neural networks, recurrent, models of nonlinear dynamical systems, classification of neural networks, model characteristics.
Abstract
The classification of recurrent neural networks used as the mathematical models of nonlinear dynamic systems described by the input-output ratio is proposed. Neural networks have found application in many subjects of technology, where they are used to solve numerous problems including the identification, modelling and synthesis of non-linear dynamic systems. These problems can be set in the approximation formulation, when it is required to construct the mathematical model of a non-linear dynamic system operator, that uniquely maps the set of input signals into the set of output signals. Neural networks are expedient under circumstances when there is slowly decreasing the operator approximation error on increasing degree of polynomial operator model. Thanks to feedback, one can accumulate information and use it when processing signals. The recurrent neural network can contain lower number of parameters in comparison with the multilayer perceptron network carrying out the same task.
Depending on the feedback location affecting the neurons interaction, two classes of recurrent neural networks are distinguished. The first class is globally recurrent networks, in which feedback is allowed between the neurons of the same layer or different layers. Basically, four kinds of networks can be distinguished: fully recurrent networks, partially recurrent networks (the Elman structure, the Jordan structure, the recurrent multi-layer perceptron), state-space networks and cellular neural networks. The second class is locally recurrent networks, which contain feedback inside neurons and have the following structures: the networks consisting of static feedforward and, so-called, dynamic neurons, as well as the block-oriented neural networks of Wiener, Hammerstein, Wiener-Hammerstein, etc.
The structures, properties, advantages and disadvantages of different types of recurrent networks are considered. The presented analysis is useful for choosing the mathematical model of a nonlinear dynamical system a priori, when it is necessary to evaluate which of the known neural network structures meets the requirements for model characteristics, such as accuracy, computational complexity, robustness, hardware implementation, more than others do.
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Optimization of non-recursive rejection filters
with partly adaptation
D.I. Popov, e-mail: adop@mail.ru
The Ryazan State Radio Engineering University (RSREU), Russia, Ryazan
Keywords: adaptation, Doppler phase, training sample set, optimization, clutter, minimax principle, rejector filters, rejection efficiency.
Abstract
The optimization method and the principles of the construction of rejector filters (RF) with partial adaptation are considered only to the Doppler phase of the clutter. The proposed method for optimizing RF characteristics with partial adaptation is based on the application of the minimax principle to the efficiency criterion in question and makes it possible in the a priori range of the spectral-correlation clutter parameters to increase the efficiency of its rejection with minimal losses in comparison with the marginal efficiency corresponding to full adaptation. System functions and structural schemes are given for cascade and canonical forms of RF implementation. The analysis of the RF with partial adaptation establishes the relationship between the efficiency of the RF and the volume of the training sample, depending on the order and structure of the RF and the clutter parameters. It is shown that the losses in RF efficiency are insignificantly dependent on the clutter parameters.
References
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Integration of ground complex for reception, processing and dissemination of information from space systems "Electro" and "Arctica-M" with unified territorialy distributed system of earth remote sensing
Pasternak V.I., Kozinin E.A., Kubishkin A.P., Chervatyuk I.V., Efimov E.A., e-mail: npol@laspace.ru
NPO Lavochkin
Keywords: Earth remote sensing; ground complex of acquisition, processing and distribution of information; Unified territorially distributed system; geostationary hydrometeorological space system; highly elliptical orbital space system.
Abstract
Components and purpose of ground segments of space systems "Electro" and "Arctica-M" and their future integration with Unified territorialy distributed system of Earth remote sensing which being created by State space corporation "Roscosmos" are presented in the article.
References
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Two-channel universal algorithm to demodulate spectral-efficient radio signals with controlled coupling between in-phase and quadrature components
P.S. Pokrovskiy, e-mail: paulps@list.ru
The Ryazan State Radio Engineering University (RSREU), Russia, Ryazan
Keywords: synthesis of demodulation device, universal shaper of radio signals, spectral efficient modulations, FQPSK, GMSK, T-OQPSK.
Abstract
TThe article deals development of a universal demodulation algorithm for radio signals with such bandwidth-efficient modulations as T-OQPSK, FQPSK, and GMSK. For this task, the bandwidth-efficient radio signals are represented as radio signals with controlled coupling between in-phase and quadrature components, for which two demodulation algorithms are designed. The first algorithm uses common Viterbi’s procedure, i.e. includes a unit of handling metrics for all possible transitions. It leads to significant computational expense.
The second algorithm is based on independent handling in-phase and quadrature components of described signal type by means of a filter which impulse response matched with “average” elementary impulse. This approach needs low computational costs but it has a low level of noise immunity.
To combine features of two described approach in this article a handling algorithm for bandwidth-efficient radio signal is offered. The algorithm uses the Viterbi’s procedure too, but a unit of handling metrics is replaced with a filter module. This algorithm is obtained as result of using in receiver as a reference signal a signal without components that provides controlled coupling between in-phase and quadrature components. This assumption made possible to create two circuits of quasi optimal demodulator that used two- and three-channel filtration of an in-phase and quadrature components.
Conducted research showed that the proposed algorithm has a maximum loss in noise immunity less 0.3 dB as compared with optimal algorithm based on common Viterbi’s procedure at BER = 1e-4. At the same time, the proposed algorithm provides to reduce necessary computational costs by to four times. A gain in noise immunity as compared with one-channel algorithm that uses filtration achieves 2.6 dB at same conditional.
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Development of combined speech quality measure for speaker identification accuracy estimation in additive noise environments
Tupitsin G.S., e-mail: genichyar@genichyar.com
Topnikov A.I., e-mail: topartgroup@gmail.com
Priorov A.L., e-mail: andcat@yandex.ru
Yaroslavl 'Demidov' State University
Keywords: additive noise, speaker identification accuracy, denoising, speech quality.
Abstract
The traditional approach of using the real speaker identification system and an extensive database of test speech signals requires large computational resources. The paper is dedicated to the development of an alternative way to the speaker identification accuracy estimation in additive noise environments. In this paper an indirect speaker identification accuracy estimation technique using some objective speech quality measures and combined measure was proposed. It was shown the proposed combined speech quality measure could be used in the problem of speaker identification accuracy estimation in additive noise environments.
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Comparative characteristics of the algorithms of detection steady state visually evoked potentials of the brain on an electroencephalogram
Ya.A. Turovsky, e-mail: yaroslav_turovsk@mail.ru
Voronezh State University
Keywords: brain computer interface, simulation, SSVEP.
Abstract
The results of comparison of algorithms for analysis of evoked potentials of the brain used in the design of brain-computer interfaces are presented. For carrying out computational experiments, the Fourier transform algorithm was used; the Multivariate Synchronization Index (MSI) algorithm in various modifications: analysis of the original signal, analysis of the accumulated event relation potential and the spectrum of the accumulated event relation potential; linear correlation with analysis from the reference sample of the signal received from the "user", different variants of wavelet filtration. In this case, model signals were used, representing the addition of white noise and a harmonic oscillation simulating a steady state visually evoked potentials. The most stable results (with a number of errors <10%) for the 3-second analysis period were demonstrated by the MSI of the original signal, the MSI of the Fourier transform results, MSI where the standard was the result of wavelet coherent accumulation, the linear correlation coefficient and MSI where the standard was reconstructed after the wavelet- transformation of the ERP.
References
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3. Wang Yu., Wang Yi., Cheng Ch., Jung T. Developing Stimulus Presentation on Mobile Devices for a Truly Portable SSVEP-based BCI. http://ieeexplore.ieee.org/document/6610738/?section=abstract.
4. Volosyak I. SSVEP based Bremen-BCI boosting information transfer rates // Journ. Neural Eng. – 2011. – V. 8(3). – P. 036020. DOI: 10.1088/1741-2560/8/3/036020.
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8. High frequency SSVEPs for BCI applications G. Garcia // http://hmi.ewi.utwente.nl/chi2008/chi2008_files/garcia.pdf
9. Multivariate synchronization index for frequency recognition of SSVEP-based brain-computer interface / Ya. Zhang, P. Xu, K. Cheng, D. Yao // Journal of Neuroscience Methods. – 2014. – 221. – P. 32– 40.
10. Comparison of the influence of stimuli color on Steady-State Visual Evoked Potentials / R. Tello, S. Muller, A. Ferreira, T. Freire // Bastos Res. Biomed. Eng. – 2015. – V. 31(3). – Ð.218-231.
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Implementation of integer recursive digital filters without multipliers on FPGA of the russian production
Artemiev V.V., e-mail: zzzrf413@bk.ru
Kashin A.V., e-mail: aKashin@niiis.nnov.ru
The Russian Federal Nuclear Center
Keywords: digital integer filter, implementation in FPGA, method-integer nonlinear programming.
Abstract
The article is devoted to the synthesis of recursive digital integer filter with the possibility of its implementation in FPGA. The article consists of six parts. The first part is an introduction. The second part provides an overview of the classical approaches of solving the problem of designing multiplierless digital filters. In the third part of the article proposes a method-integer nonlinear programming, allowing to solve the task on the specified set of parameters. Part four describes the hardware implementation on FPGA recursive digital filters without multiplier. In part five given the volume of the matrix space necessary for the implementation of digital filters synthesized on not equidistant set of parameters. The sixth part shows the performance of digital filters. The seventh part is the conclusion.
References
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Application of the complex filters for PAPR reduction of OFDM signals and FPGA implementation
V.N. Tran, e-mail: nghiamosmipt@gmail.com
Moscow Institute of Physics and Technology, Moscow, Russia
Keywords: Peak-to-Average Power Ratio (PAPR), OFDM modulation, Tone Reservation (TR), clipping and filtering, FPGA, complex filter.
Abstract
This paper analyzes the reconfigurable filtering techniques based on the tone reservation (TR) set and data bearing subcarriers in the time domain and frequency domain to reduce the peak-to-average power ratio (PAPR) of orthogonal frequency division multiplexing (OFDM) signals. The hardware architecture of these filters is proposed and mapped onto FPGA. The simulation results of the proposed methods and experimental results on FPGA for 16-QAM and 64-QAM modulation are presented. These results show that the PAPR of OFDM signals is significantly reduced (about 6.6 dB) and OFDM signals can achieve the desired threshold after 2-4 iterations.
To increase the PAPR reduction performance, we introduce a modified method of the TR technique and propose two combinational algorithms of the modified TR technique and the clipping-and-filtering (CAF) method, as well as two reconfigurable filters to implement these algorithms on FPGA. In the first objective of the proposed filter configuration, the modified TR method suppresses simultaneously all peaks like CAF methods, while in the traditional TR method, the largest peak is reduced. The modified TR method extracts clipping noise on reserved subcarriers to generate an “anti-peak” signal instead of using the impulse-like kernel. This configuration of the filter does not introduce in-band distortion and out-of-band radiation into the transmitted signal. Therefore, this filter configuration can be iteratively used to suppress significantly peaks of OFDM signals. After reconfiguring, the new filter configuration keeps the clipping noise on the data bearing subcarriers and resets to zero the frequency samples of the clipping noise associated with the reserved subcarrier indices. In this filter configuration, the CAF method is used. Therefore, clipping noise is added to the transmit signal. The proposed filters are based on the discrete Fourier transform (DFT)/ inverse DFT (IDFT) pair and finite impulse response (FIR) filters.
Simulation results on Matlab show that the proposed algorithms significantly reduced PAPR after the first iteration and the signal peaks can achieve the desired threshold after 2–4 iterations. Both algorithms give similar results in terms of PAPR reduction capability, the expense of system interference MER and the increase in the mean power.
FPGA implementation of the FFT/IFFT-based complex filter is suite for long OFDM symbols. It provides fast processing speed, low hardware resource utilisation and flexibility to reconfigure. The complex FIR-filter utilises great hardware resources, especially DSP48E1s. It gives a low processing delay.
References
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Algorithmic methods for compensation of power amplifier nonlinearity
Le Van Ky, e-mail: levanky@phystech.edu
Multimedia technology and telecommunications department, Moscow Institute of Physics and Technology (State University), Russia, Moscow
Keywords: adaptive predistortion, nonlinear distortion, Wiener model, Hammerstein model, singular value decomposition.
Abstract
Power amplifiers are essential components in communication systems and are inherently nonlinear. The nonlinearity creates spectral growth (broadening) beyond the signal bandwidth, which interferes with adjacent channels. It also causes distortions within the signal bandwidth, which decreases the bit error rate at the receiver. Newer transmission formats, such as wideband code division multiple access (WCDMA) or orthogonal frequency division multiplexing (OFDM), are especially vulnerable to the nonlinear distortions due to their high peak-to-average power ratios (PAPR). If we simply back-off the input signal to achieve the linearity required for the power amplifier, the power amplifier effciency will be very low for high PAPR signals.
Another choice is to linearize a nonlinear power amplifier so that overall we have a linear and reasonably effcient device. Digital predistortion is one of the most cost effective ways among all linearization techniques. However, most of the existing designs treat the power amplifier as a memoryless device. For wideband or high power applications, the power amplifier exhibits memory effects, for which memoryless predistorters can achieve only limited linearization performance.
Presently there are many effective methods for nonlinearity compensation of digital radio signal power amplifier. In this paper we analyze several well-known algorithms and propose a new variant of nonlinearity compensation of power amplifier. Computer simulation results confirms the effectiveness of the proposed method.
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3. Kang, H. W., Cho, Y. S., and Youn, D. H., “On compensating nolinear distortions of an OFDM system using effcient adaptive predistorter,” IEEE Trans. Commun., vol. 47, pp. 522–526, Apr. 1999.
4. Eskinat, E., Johnson, S. H., and Luyben, W. L., “Use of Hammerstein models in identification of nonlinear systems,” AIChE J., vol. 37, pp. 255–267, Feb. 1991.
5. Bai, E. W., “An optimal two stage identification algorithm for Hammerstein-Wiener nonlinear systems,” in Proc. American Contr. Conf., pp. 2756–2760, June 1998.
6. Ding, L., Zhou, G. T., Morgan, D. R., Ma, Z., Kenney, J. S., Kim, J., and Giardina, C. R., “Memory polynomial predistorter based on the indirect learning architecture,” in Proc. IEEE Global Telecommun. Conf., pp. 967–971, Nov. 2002.
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