In order to achieve adaptive channel coding and adaptive modulation, the main causes of degradation to system performance are the decoder selection error and modulator estimation error. The utilization of supplementary information, in an estimation system utilizing channel estimation results, blind modulation estimation, and blind encoder estimation using several decoders information and encoder transitions have been considered to overcome these two problems. There are however many issues in these methods, such as the channel estimation difference between transmitter and receiver, computational complexity and the assumption of perfect Channel State Information (CSI). Our proposal, on the other hand, decreases decoder and demodulator selection error using a Hidden-Markov Model (HMM). In order to estimate the switching patterns of the encoder and modulator, our proposed system selects the maximum likelihood encoder and modulator transition patterns using both encoder and modulator transition probability based on the HMM obtained by CSI and also Decoder and Demodulator Selection Error probabilities. Therefore, the decoder and demodulation results can be achieved efficiently without any restraint on the pattern of switching encoder and modulation.

This paper describes recent progress in research on wavelength converters that employ quasi-phase-matched LiNbO3 (QPM-LN) waveguides. The basic structure and operating principle of these devices are presented. The conversion efficiency in difference frequency generation (DFG), second harmonic generation (SHG) and an SHG/DFG cascade scheme are explained. Device fabrication technologies such as periodic poling, and those used for annealed proton-exchanged (APE) waveguides, and direct bonded waveguides are introduced. An APE waveguide is used to demonstrate the wavelength conversion of broadband (> 1 Tbit/s) WDM signals. The low penalty conversion of high-speed (40 Gbit/s) based WDM signals is also reported. Excellent resistance to photorefractive damage in a direct bonded waveguide is presented. This high level of resistance enabled highly efficient wavelength conversion. A new design concept is introduced for a multiple QPM device based on the continuous phase modulation of a periodically poled structure. This multiple QPM device enables the variable wavelength conversion of WDM signals. High-speed wavelength switching between ITU-T grid wavelengths using a finely tuned multiple QPM device is also reported. QPM-LN based wavelength converters have several advantages, including the ability to convert high-speed signals of 1 THz or greater, no signal-to-noise (S/N) ratio degradation, no modulation format dependence, and they are capable of the simultaneous conversion of broadband WDM channels. They will therefore be key devices in future photonic networks.

We are developing a simple three-dimensional (3-D) display method that uses only two transparent images using luminance division displays without any extra equipment. This method can be applied to not only electronic displays but also the printed sheets. The method utilizes a 3-D visual illusion in which two ordinary images with many edges can be perceived as an apparent 3-D image with continuous depth between the two image planes, when two identical images are overlapped from the midpoint of the observer's eyes and their optical-density ratio is changed according to the desired image depths. We can use transparent printed sheets or transparent liquid crystal displays to display two overlapping transparent images using this 3-D display method. Subjective test results show that the perceived depths changed continuously as the optical-density ratio changed. Deviations of the perceived depths from the average for each observer were sufficiently small. The depths perceived by all six observers coincided well.

The effect of planar waveguide with conductor cladding (PWGCC) on evanescent coupling with a side-polished fiber is investigated using the three-dimensional finite difference beam propagation method (3D FD-BPM). The coupling and propagation of light were found to depend on the relationship between the refractive index values of each structure and the configuration of the side-polished fiber used in the PWGCC.

Recently, in order to improve high speed data transmission and spectral efficiency in wireless communication systems, the combination of OFDM and space-time coding is being actively studied. In order to maximize the system efficiency, the problem of co-channel interference must be solved. One technique to overcome the co-channel interference and to increase the system capacity is to use adaptive antennas. Conventional beamforming techniques for single antenna cannot be applied directly to STBC-OFDM systems, because the signals transmitted from the two transmit antennas are superposed at the receive antenna and the interference between signals of the two transmit antennas occurs. In this paper, we present the MMSE beamforming technique using training sequence for STBC-OFDM systems in reverse link and evaluate the performance by using various parameters such as the number of training blocks, cluster sizes and angle spreads in Two-ray, TU and HT channels. From the simulation results, we show the best cluster sizes and the number of training blocks corresponding to these cluster sizes.

High-resolution spectrum estimation techniques have been extensively studied in recent publications. Knowledge of the noise variance is vital for spectrum estimation from noise-corrupted observations. This paper presents the use of noise compensation and data extrapolation for spectrum estimation. We assume that the observed data sequence can be represented by a set of autoregressive parameters. A recently proposed iterative algorithm is then used for noise variance estimation while autoregressive parameters are used for data extrapolation. We also present analytical results to show the exponential decay characteristics of the extrapolated samples and the frequency domain smoothing effect of data extrapolation. Some statistical results are also derived. The proposed noise-compensated data extrapolation approach is applied to both the autoregressive and FFT-based spectrum estimation methods. Finally, simulation results show the superiority of the method in terms of bias reduction and resolution improvement for sinusoids buried in noise.

Radio frequency identification (RFID) enables everyday objects to be identified, tracked, and recorded. The RFID tags are must be extremely simple and of low cost to be suitable for large scale application. An efficient RFID anti-collision mechanism must have low access latency and low power consumption. This paper investigates how to recognize multiple RFID tags within the reader's interrogation ranges without knowing the number of tags in advance by using framed ALOHA. To optimize power consumption and overall tag read time, a combinatory model was proposed to analyze both passive and active tags with consideration on capture effect over wireless fading channels. By using the model, the parameters on tag set estimation and frame size update were presented. Simulations were conducted to verify the analysis. In addition, we come up with a proposal to combat capture effect in deterministic anti-collision algorithms.

In this paper, single-input multiple-output (SIMO)-model-based blind source separation (BSS) is addressed, where unknown mixed source signals are detected at microphones, and can be separated, not into monaural source signals but into SIMO-model-based signals from independent sources as they are at the microphones. This technique is highly applicable to high-fidelity signal processing such as binaural signal processing. First, we provide an experimental comparison between two kinds of SIMO-model-based BSS methods, namely, conventional frequency-domain ICA with projection-back processing (FDICA-PB), and SIMO-ICA which was recently proposed by the authors. Secondly, we propose a new combination technique of the FDICA-PB and SIMO-ICA, which can achieve a higher separation performance than the two methods. The experimental results reveal that the accuracy of the separated SIMO signals in the simple SIMO-ICA is inferior to that of the signals obtained by FDICA-PB under low-quality initial value conditions, but the proposed combination technique can outperform both simple FDICA-PB and SIMO-ICA.

This paper presents a method of searching for the shortest route via the most designated points with the length not exceeding the preset upper bound. The proposed algorithm can obtain the quasi-optimum route efficiently and its effectiveness is verified by applying the algorithm to the actual map data.

Holey Fiber (HF) technology has progressed rapidly in recent years and has resulted in the development of a wide range of optical fibers with unique and highly useful optical properties including endlessly single-mode guidance, and high optical nonlinearity. In this paper the state-of-the-art HF technology for all-optical signal processing devices is reviewed from a perspective of possible application for telecommunications.

This paper presents a novel algorithm for spectral subtraction (SS). The method is derived from a relation between the spectrum obtained by the discrete Fourier transform (DFT) and that by a subspace decomposition method. By using the relation, it is shown that a noise reduction algorithm based on subspace decomposition is led to an SS method in which noise components in an observed signal are eliminated by subtracting variance of noise process in the frequency domain. Moreover, it is shown that the method can significantly reduce computational complexity in comparison with the method based on the standard subspace decomposition. In a similar manner to the conventional SS methods, our method also exploits the variance of noise process estimated from a preceding segment where speech is absent, whereas the noise is present. In order to more reliably detect such non-speech segments, a novel robust voice activity detector (VAD) is then proposed. The VAD utilizes the spread of eigenvalues of an autocorrelation matrix corresponding to the observed signal. Simulation results show that the proposed method yields an improved enhancement quality in comparison with the conventional SS based schemes.

This research aims to construct a high-quality Japanese TTS (Text-to-Speech) system that has high flexibility in treating prosody. Many TTS systems have implemented a prosody control system but such systems have been fundamentally designed to output speech with a standard pitch and speech rate. In this study, we employ a unit selection-concatenation method and also introduce an analysis-synthesis process to provide precisely controlled prosody in output speech. Speech quality degrades in proportion to the amount of prosody modification, therefore a target cost for prosody is set to evaluate prosodic difference between target prosody and speech candidates in such a unit selection system. However, the conventional cost ignores the original prosody of speech segments, although it is assumed that the quality deterioration tendency varies in relation to the pitch or speech rate of original speech. In this paper, we propose a novel cost function design based on the prosody of speech segments. First, we recorded nine databases of Japanese speech with different prosodic characteristics. Then with respect to the speech databases, we investigated the relationships between the amount of prosody modification and the perceptual degradation. The results indicate that the tendency of perceptual degradation differs according to the prosodic features of the original speech. On the basis of these results, we propose a new cost function design, which changes a cost function according to the prosody of a speech database. Results of preference testing of synthetic speech show that the proposed cost functions generate speech of higher quality than the conventional method.

Spontaneously spoken Japanese includes a lot of grammatically ill-formed linguistic phenomena such as fillers, hesitations, inversions, and so on, which do not appear in written language. This paper proposes a novel method of robust dependency parsing using a large-scale spoken language corpus, and evaluates the availability and robustness of the method using spontaneously spoken dialogue sentences. By utilizing stochastic information about the appearance of ill-formed phenomena, the method can robustly parse spoken Japanese including fillers, inversions, or dependencies over utterance units. Experimental results reveal that the parsing accuracy reached 87.0%, and we confirmed that it is effective to utilize the location information of a bunsetsu, and the distance information between bunsetsus as stochastic information.

Optical regeneration technique using an electro-absorption modulator (EAM) is reviewed. Simple 3R optical regeneration using an EAM was proposed and verified at 20 Gbit/s. The optical nonlinearities including cross-absorption modulation (XAM) and cross-phase modulation (XPM) induced in an EAM were quantitatively characterized by experiment. High bit-rate 2R type all-optical regeneration (wavelength conversion) at 100 Gbit/s was demonstrated by an EAM in conjunction with a delayed interferometer (DI) with required optical pulse energy of 1.5 pJ. It was verified that the operable bandwidth of the EAM-DI wavelength converter at 40 Gbit/s covered almost full range of C-band without tuning operation conditions.

This paper describes the modeling of various emotional expressions and speaking styles in synthetic speech using HMM-based speech synthesis. We show two methods for modeling speaking styles and emotional expressions. In the first method called style-dependent modeling, each speaking style and emotional expression is modeled individually. In the second one called style-mixed modeling, each speaking style and emotional expression is treated as one of contexts as well as phonetic, prosodic, and linguistic features, and all speaking styles and emotional expressions are modeled simultaneously by using a single acoustic model. We chose four styles of read speech -- neutral, rough, joyful, and sad -- and compared the above two modeling methods using these styles. The results of subjective evaluation tests show that both modeling methods have almost the same accuracy, and that it is possible to synthesize speech with the speaking style and emotional expression similar to those of the target speech. In a test of classification of styles in synthesized speech, more than 80% of speech samples generated using both the models were judged to be similar to the target styles. We also show that the style-mixed modeling method gives fewer output and duration distributions than the style-dependent modeling method.

In this paper, we propose a new feature extraction method that combines both HMT-based denoising and weighted filter bank analysis for robust speech recognition. The proposed method is made up of two stages in cascade. The first stage is denoising process based on the wavelet domain Hidden Markov Tree model, and the second one is the filter bank analysis with weighting coefficients obtained from the residual noise in the first stage. To evaluate performance of the proposed method, recognition experiments were carried out for additive white Gaussian and pink noise with signal-to-noise ratio from 25 dB to 0 dB. Experiment results demonstrate the superiority of the proposed method to the conventional ones.

This paper presents a novel decoding algorithm for turbo codes, in which the likelihood values for redundant parts are updated in order for those values to become more reliable. A criterion for updating the redundant likelihood values is proposed, which is based on the comparisons of the channel values with the re-generated values by the soft-input and soft-output encoders. It is shown that the proposed method can improve the error correcting capabilities, i.e., the improvement of BER/BLER performance and the achievable BER limit.

Use of directional antenna in the context of ad hoc wireless networks can largely reduce radio interference, thereby improving the utilization of wireless medium. Our major contribution in this paper is to devise a MAC protocol that exploits the advantages of directional antenna in ad hoc networks for improved system performance. In this paper, we have illustrated a MAC protocol for ad hoc networks using directional antenna with the objective of effective utilization of the shared wireless medium. In order to implement effective MAC protocol in this context, a node should know how to set its transmission direction to transmit a packet to its neighbors and to avoid transmission in other directions where data communications are already in progress. In this paper, we are proposing a receiver-centric approach for location tracking and MAC protocol, so that, nodes become aware of its neighborhood and also the direction of the nodes for communicating directionally. A node develops its location-awareness from these neighborhood-awareness and direction-awareness. In this context, researchers usually assume that the gain of directional antennas is equal to the gain of corresponding omni-directional antenna. However, for a given amount of input power, the range R with directional antenna will be much larger than that using omni-directional antenna. In this paper, we also propose a two level transmit power control mechanism in order to approximately equalize the transmission range R of an antenna operating at omni-directional and directional mode. This will not only improve medium utilization but also help to conserve the power of the transmitting node during directional transmission. Our proposed directional MAC protocol can be effective in both ITS (Intelligent Transportation System), which we simulate in String and Parallel Topology, and in any community network, which we simulate in Random Topology. The performance evaluation on QualNet network simulator clearly indicates the efficiency of our protocol.

In this paper, we investigate packet loss and system dimensioning of feedback (FB) type wavelength division multiplexing (WDM) optical routers under asynchronous and variable packet length self-similar traffic. We first study the packet loss performance for two different types of WDM optical routers under asynchronous and variable packet length self-similar traffic. Based on simulation results, we demonstrate that a 1616 FB type WDM optical router employing more than 4 re-circulated ports without using void filling (VF) algorithm has better performance. We then present the system dimensioning issues of FB type WDM optical routers, by showing the performance of FB type WDM optical routers as a function of the number of re-circulated ports, buffer depth, re-circulation limit, basic delay unit in the fiber delay line optical buffers and traffic characteristics. The sensitivity of the mutual effects of the above parameters on packet loss is investigated in details. Based on our results, we conclude that the FB type WDM optical routers must be dimensioned with the appropriate number of re-circulated ports, re-circulation limits, buffer depth, and optimal basic delay unit in the fiber delay line optical buffers under relevant traffic characteristics to achieve high switching performance.

This paper describes continuous speech recognition incorporating the additional complement information, e.g., voice characteristics, speaking styles, linguistic information and noise environment, into HMM-based acoustic modeling. In speech recognition systems, context-dependent HMMs, i.e., triphone, and the tree-based context clustering have commonly been used. Several attempts to utilize not only phonetic contexts, but additional complement information based on context (factor) dependent HMMs have been made in recent years. However, when the additional factors for testing data are unobserved, methods for obtaining factor labels is required before decoding. In this paper, we propose a model integration technique based on general factor dependent HMMs for decoding. The integrated HMMs can be used by a conventional decoder as standard triphone HMMs with Gaussian mixture densities. Moreover, by using the results of context clustering, the proposed method can determine an optimal number of mixture components for each state dependently of the degree of influence from additional factors. Phoneme recognition experiments using voice characteristic labels show significant improvements with a small number of model parameters, and a 19.3% error reduction was obtained in noise environment experiments.