Добірка наукової літератури з теми "2-D demodulation"

This paper presents a low peak-to-average power ratio (PAPR) modulation scheme and demodulation method for low-cost terminals in sixth-generation (6G), which is called one plus delay (1 + D) pi/2(N + 1) BPSK. Explicitly, the modulation scheme is first generated based on pi/2 BPSK, then proceeded by interpolation and (1 + D) transformation. Simulation results show that the proposed (1 + D) pi/2(N + 1) BPSK scheme has lower PAPR and smaller out-of-band leakage in discrete Fourier transform spread orthogonal frequency division multiplexing (DFT-s-OFDM). Moreover, better performance can be attained by increasing the value of N. Finally, similar block error ratio (BLER) performance can be obtained at the same spectral efficiency of the conventional pi/2 BPSK scheme.

Coherent optical fiber communications for data rates of 100Gbit/s and beyond have recently been studied extensively primarily because high sensitivity of coherent receivers could extend the transmission distance. Spectrally efficient modulation techniques such as M-ary quadrature amplitude modulation (M-QAM) can be employed for coherent optical links. The integration of multi-level modulation formats based on coherent technologies with wavelength-division multiplexed (WDM) systems is key to meet the aggregate bandwidth demand. This paper reviews coherent 16 quadrature amplitude modulation (16QAM) systems to scale the network capacity and maximum reach of current optical communication systems to accommodate traffic growth. Full Text: PDF ReferencesK. Kikuchi, "Fundamentals of Coherent Optical Fiber Communications", J. Lightwave Technol., vol. 34, no. 1, pp. 157-179, 2016. CrossRef S. Tsukamoto, D.-S. Ly-Gagnon, K. Katoh, and K. Kikuchi, "Coherent Demodulation of 40-Gbit/s Polarization-Multiplexed QPSK Signals with16-GHz Spacing after 200-km Transmission", Proc. OFc, Paper PDP29, (2005). DirectLink K. Kikuchi, "Coherent Optical Communication Technology", Proc. OFC, Paper Th4F.4, (2015). CrossRef J. M. Kahn and K.-P. Ho, "Spectral efficiency limits and modulation/detection techniques for DWDM systems", IEEE J. Sel. Topics Quantum Electron., vol. 10, no. 2, pp. 259–272, (2004). CrossRef S. Tsukamoto, K. Katoh, and K. Kikuchi, "Coherent demodulation of optical multilevel phase-shift-keying signals using homodyne detection and digital signal processing", IEEE Photon. Technol. Lett., vol. 18, no. 10, pp. 1131–1133, (2006). CrossRef Y. Mori, C. Zhang, K. Igarashi, K. Katoh, and K. Kikuchi, "Unrepeated 200-km transmission of 40-Gbit/s 16-QAM signals using digital coherent receiver", Opt. Exp., vol. 17, no. 32, pp. 1435–1441, (2009). CrossRef H. Nakashima, Et al., "Digital Nonlinear Compensation Technologies in Coherent Optical Communication Systems", Proc. OFC, Paper W1G.5, (2017). CrossRef S. J. Savory, "Digital filters for coherent optical receivers", Opt. Exp., vol. 16, no. 2, pp. 804–817, (2008). CrossRef D. S. Millar, T. Koike-Akino, S. Ö. Arık, K. Kojima, K. Parsons, T. Yoshida, and T. Sugihara, "High-dimensional modulation for coherent optical communications systems", Opt. Express, vol. 22, no. 7, pp 8798-8812, (2014). CrossRef R. Griffin and A. Carter, "Optical differential quadrature phase-shift key (oDQPSK) for high capacity optical transmission", Proc. OFC, Paper WX6, (2002). DirectLink K. Kikuchi, "Digital coherent optical communication systems: fundamentals and future prospects", IEICE Electron. Exp., vol. 8, no. 20, pp. 1642–1662, (2011). CrossRef F. Derr, "Optical QPSK transmission system with novel digital receiver concept", Electron Lett., vol. 27, no. 23, pp. 2177–2179, (1991). CrossRef R. No’e, "Phase noise tolerant synchronous QPSK receiver concept with digital I&Q baseband processing", Proc. OECC, Paper 16C2-5, (2004). DirectLink D.-S. Ly-Gagnon, S. Tsukamoto, K. Katoh, and K. Kikuchi, "Coherent detection of optical quadrature phase-shift keying signals with carrier phase estimation", J. Lightw. Technol., vol. 24, no. 1, pp. 12–21, (2006). CrossRef M. Taylor, "Coherent detection method using DSP for demodulation of signal and subsequent equalization of propagation impairments", IEEE Photon. Technol. Lett., vol. 16, no. 2, pp. 674–676, (2004). CrossRef S. Tsukamoto, K. Katoh, and K. Kikuchi, "Unrepeated transmission of 20-Gb/s optical quadrature phase-shift-keying signal over 200-km standard single-mode fiber based on digital processing of homodyne-detected signal for Group-velocity dispersion compensation", IEEE Photon. Technol. Lett., vol. 18, no. 9, pp. 1016–1018, (2006). CrossRef S. Tsukamoto, Y. Ishikawa, and K. Kikuchi, "Optical Homodyne Receiver Comprising Phase and Polarization Diversities with Digital Signal Processing", Proc. ECOC, Paper Mo4.2.1, (2006). CrossRef K. Kikuchi and S. Tsukamoto, "Evaluation of Sensitivity of the Digital Coherent Receiver", J. Lightw. Technol., vol. 20, no. 13, pp. 1817–1822, (2008). CrossRef S. Ishimura and K. Kikuchi, "Multi-dimensional Permutation Modulation Aiming at Both High Spectral Efficiency and High Power Efficiency", Proc. OFC/NFOEC, Paper M3A.2, (2014). CrossRef F. I. El-Nahal and A. H. M. Husein, "Radio over fiber access network architecture employing RSOA with downstream OQPSK and upstream re-modulated OOK data", (Optik) Int. J. Light Electron Opt., vol. 123, no. 14, pp: 1301-1303, (2012). CrossRef T. Koike-Akino, D. S. Millar, K. Kojima, and K. Parsons, "Eight-Dimensional Modulation for Coherent Optical Communications", Proc. ECOC, Paper Tu.3.C.3, (2013). DirectLink B. Sklar, Digital communications: Fundamentals and Applications, Prentice-Hall, (2001).

Abstract. In this study, we use a nonlinear and non-stationary time series analysis method, the ensemble empirical mode decomposition method (EEMD), to analyze the polar motion (PM) time series (EOP C04 series from 1962 to 2013) to find a 531 day-period wobble (531 dW) signal. The 531 dW signal has been found in the early PM seires (1962–1977) while cannot be found in the recent PM seires (1978–2013) using conventional analysis approaches. By the virtue of the demodulation feature of EEMD, the 531 dW can be confirmed to be present in PM based on the differences of the amplitudes and phases between different intrinsic mode functions. Results from three sub-series divided from the EOP C04 series show that the period of the 531 dW is subject to variations, in the range of 530.9–524 d, and its amplitude is also time-dependent (about 2–11 mas). Synthetic tests are carried out to explain why the 531 dW can only be observed in recent 30-years PM time series after using EEMD. The 531 dW is also detected in two longest available superconducting gravimeter (SG) records, which further confirms the presence of the 531 dW. The confirmation of 531 dW existence could be significant in establishing a more reasonable Earth rotation model and may effectively contribute to the prediction of the PM and its mechanism interpretation.

In this work, we have studied the integration of an optical signal-based Indoor Positioning System (IPS) capable of supporting multi-access discrimination techniques. The research analyzes the different techniques and conditions that can be used to develop an IPS using a microcontroller unit (MCU)-based system-on-chip (SoC) systems. The main goal is to be able to integrate into the MCU both the hardware and software requirements for an IPS detector. In this way, different strategies that can implement multi-access discrimination using Frequency-division multiple access (FDMA) have been tested, such as I/Q demodulation, digital filtering, and discrete Fourier transform (DFT). This analysis has found a good technique to be executed in an MCU-based SoC, the DFT implemented through the Goertzel’s algorithm. The empirical tests carried out concluded that, using only one an MCU with the required HW and tuned SW, 15 position measurements per second were computed, with high accuracy in the 3-D positioning, with errors of less than 1 cm in a test area of 3.5 × 3.5 m 2 . The main contribution of the paper is the implementation of the optical signal based IPS in an MCU-SoC that includes signal acquisition and processing. The digital filtering or spectral processing for up to 16 received signals makes this IPS system very attractive from a design and cost point of view.

Speech is a non-stationary signal and contains modulations in both spectral and temporal domains. Based on the type of modulations studied, most speech processing algorithms can be classified into short-time analysis algorithms, narrow-band analysis algorithms, or joint spectro-temporal analysis algorithms. While traditional methods of speech analysis study the modulation along either time (Short-time analysis algorithms) or frequency (Narrowband analysis) at a time. A new class of algorithms that work simultaneously along both temporal as well as spectral dimensions, called the spectro-temporal analysis algorithms, have become prominent over the past decade. Joint spectro-temporal analysis (also referred to as 2-D speech analysis) has shown promise in applications such as formant estimation, pitch estimation, speech recognition, etc. Over the past decade, 2-D speech analysis has been independently motivated from several directions. Broadly these motivations for 2-D speech models can be grouped into speech-production motivated, source-separation/machine- learning motivated and neurophysiology motivated. In this thesis, we develop 2-D speech model based on the speech production motivation. The overall organization of the thesis is as follows: We first develop the context of 2-D speech processing in Chapter one, we then proceed to develop a 2-D multicomponent AM-FM model for narrowband spectrogram patch of voiced speech and experiment with the perceptual significance of number of components needed to represent a spectrogram patch in Chapter two. In Chapter three we develop a demodulation algorithm called the inphase and the quadrature phase demodulation (IQ), compared to the state-of-the art sinusoidal demodulation, the AM obtained using this method is more robust to carrier estimation errors. The demodulation algorithm was verified on call voiced sentences taken from the TIMIT database. In chapter four we develop a demodulation algorithm based on Riesz transform, a natural extension of the Hilbert transform to higher dimensions, unlike the sinusoidal and the IQ demodulation techniques, Riesz-transform-based demodulation does not require explicit carrier estimation and is also robust to pitch discontinuous in patches. The algorithm was validated on all voiced sentences from the TIMIT database. Both IQ and Riesz-transform-based methods were found to give more accurate estimates of the 2-D AM (relates to vocal tract) and 2-D carrier (relates to source) compared with the sinusoidal modulation. In Chapter five we show application of the demodulated AM and carrier to pitch estimation and for creation of hybrid sounds. The hybrid sounds created were found to have better perceptual quality compared with their counterparts created using the linear prediction analysis. In Chapter six we summarize the work and present with possible directions of future research.

Speech is a non-stationary signal and contains modulations in both spectral and temporal domains. Based on the type of modulations studied, most speech processing algorithms can be classified into short-time analysis algorithms, narrow-band analysis algorithms, or joint spectro-temporal analysis algorithms. While traditional methods of speech analysis study the modulation along either time (Short-time analysis algorithms) or frequency (Narrowband analysis) at a time. A new class of algorithms that work simultaneously along both temporal as well as spectral dimensions, called the spectro-temporal analysis algorithms, have become prominent over the past decade. Joint spectro-temporal analysis (also referred to as 2-D speech analysis) has shown promise in applications such as formant estimation, pitch estimation, speech recognition, etc. Over the past decade, 2-D speech analysis has been independently motivated from several directions. Broadly these motivations for 2-D speech models can be grouped into speech-production motivated, source-separation/machine- learning motivated and neurophysiology motivated. In this thesis, we develop 2-D speech model based on the speech production motivation. The overall organization of the thesis is as follows: We first develop the context of 2-D speech processing in Chapter one, we then proceed to develop a 2-D multicomponent AM-FM model for narrowband spectrogram patch of voiced speech and experiment with the perceptual significance of number of components needed to represent a spectrogram patch in Chapter two. In Chapter three we develop a demodulation algorithm called the inphase and the quadrature phase demodulation (IQ), compared to the state-of-the art sinusoidal demodulation, the AM obtained using this method is more robust to carrier estimation errors. The demodulation algorithm was verified on call voiced sentences taken from the TIMIT database. In chapter four we develop a demodulation algorithm based on Riesz transform, a natural extension of the Hilbert transform to higher dimensions, unlike the sinusoidal and the IQ demodulation techniques, Riesz-transform-based demodulation does not require explicit carrier estimation and is also robust to pitch discontinuous in patches. The algorithm was validated on all voiced sentences from the TIMIT database. Both IQ and Riesz-transform-based methods were found to give more accurate estimates of the 2-D AM (relates to vocal tract) and 2-D carrier (relates to source) compared with the sinusoidal modulation. In Chapter five we show application of the demodulated AM and carrier to pitch estimation and for creation of hybrid sounds. The hybrid sounds created were found to have better perceptual quality compared with their counterparts created using the linear prediction analysis. In Chapter six we summarize the work and present with possible directions of future research.

Speech signals possess a rich time-varying spectral content, which makes their analysis a challenging signal processing problem. Developing methods for accurate speech analysis has a direct impact on applications such as speech synthesis, speaker recognition, speech recognition, voice morphing, etc. A widely used tool to visualize the time-varying spectral content is the spectrogram, which represents the spectral content of the signal in the joint time-frequency plane. A spectrogram can be viewed as a collection of several localized spectrotemporal patches. By analyzing the structure of two-dimensional (2-D) patterns in the spectrogram, we propose modeling it using 2-D amplitude-modulated and frequency-modulated (AM-FM) sinusoids. The justification for the 2-D AM-FM model for speech can be provided based on the physical process behind its generation. From a speech production perspective, the AM and FM components correspond to the vocal-tract smooth envelope and excitation signal, respectively. We demonstrate that analyzing speech jointly in time and frequency reveals several important characteristics, which are otherwise not evident either in purely time-domain or frequency-domain analysis. The central problem in this dissertation is 2-D demodulation of a speech spectrogram, which yields 2-D AM and FM components. We advocate the use of the Riesz transform, which is a 2-D extension of the Hilbert transform, to demodulate narrowband and pitch adaptive spectrograms. Interestingly, the 2-D AM and FM components obtained as a result of demodulation have potential benefits for speech analysis. We demonstrate the impact of the proposed modeling technique for vocal tract filter estimation, voiced/unvoiced component separation, pitch tracking, speech synthesis, and periodic/aperiodic decomposition of speech signals. The accuracy of the estimated speech parameters is validated considering the task of speech reconstruction. The first part of the thesis is focused on theoretical developments related to 2-D modeling. We consider prototypical 2-D cosine signals, analyze their Fourier transform properties, solve the problem of demodulation of a 2-D AM-FM cosine signal and extend the model to spectrotemporal patches. Following this, we examine the taxonomy of time-frequency patterns in the FM component, highlighting the salient attributes of different types of phonation in speech. We show that 2-D patterns specific to different speech sounds (voiced/unvoiced) can be captured by computing two novel time-frequency maps from the 2-D FM component: the coherencegram and orientationgram. The usefulness of the maps is demonstrated for the problem of periodic and aperiodic decomposition of speech signals. In the second part, we use the FM component for estimating the source parameters. We show that the FM component is a rich representation of the source signal in 2-D and use it to estimate the speaker’s fundamental frequency (or pitch), speech aperiodicity, and voiced/unvoiced segmentation of the speech signal. We propose novel spectrotemporal features for voiced and unvoiced segmentation of speech. In contrast to time-domain features such as short-time energy, zero crossings, and autocorrelation coefficients, the proposed features are relatively insensitive to local variations of the speech waveform. The FM component is obtained by demodulating the narrowband speech spectrogram, which exhibits high frequency resolution. Consequently, the FM component encodes the speaker’s pitch. Hence, we propose methods for estimating the pitch from the FM component. Another critical component of a speech signal is its aperiodicity. Voiced sounds are quasi-periodic and have a noise component of strength relatively weaker than unvoiced sounds. Utilizing the time-frequency properties of the FM component, we propose methods for the estimation of speech aperiodicity. While the FM component is used to estimate the source parameters, the 2-D AM component models the slowly varying vocal-tract filter. However, estimation of the vocal-tract filter is challenging due to its interaction with the quasi-periodic excitation. Two issues arise in this context: the first one is related to the length of the analysis window used for computing the spectrogram. We argue that a fixed-length analysis window is not ideal for vocal tract estimation. We show that the best results can be obtained by adapting the window length to the speaker’s pitch while computing the spectrogram. Such a spectrogram is referred to as the pitch-adaptive spectrogram. The second issue is related to the processing involved in demodulation, which has the undesirable effect of broadening the formant bandwidths. Hence, we propose a method to compensate for the formant broadening. It is crucial to estimate the optimum formant bandwidths as they determine the shape of the vocal tract filter and govern speech intelligibility during synthesis. The effectiveness of the estimated source and filter parameters is shown by incorporating them in a spectral synthesis model and a neural vocoder for speech reconstruction. For neural vocoder, we use WaveNet, which is a deep generative model for audio generation. By conditioning the model on acoustic features, one can guide WaveNet to produce realistic speech waveforms. We use the Riesz transform-based acoustic features as conditional features in WaveNet vocoder. The quality of generated speech waveforms is evaluated by using objective and subjective measures.

Optical full-field measurement techniques have been widely studied in academia and applied to many actual fields of automated inspection, reverse engineering, cosmetic surgery, and so on. With the advent of color CCD cameras and DMD (Digital Micromirror Device) based color DLP (Digital Light Processing) projectors, their major red, green, and blue channels have been used as a carrier to code fringe patterns. Since three fringe patterns can be simultaneously projected and captured at one shot, the acquisition time reduces to 1/3 of the value by the gray fringe pattern projection. This chapter will introduce two kinds of applications of red, green, and blue as a carrier: 1) modulation and demodulation method of coding sinusoidal fringe patterns into RGB channels of a composite color image; and 2) modulation and demodulation method of coding sinusoidal and binary fringe patterns into RGB channels of multiple composite color images. Experiments on testing the two kinds of applications were carried out by measuring the shape of objects’ surface. The results confirm that red, green, and blue channels can be used as a carrier to reduce the acquisition time.