In this letter, an improved triple-tunable frequency synthesizer structure to achieve both high frequency resolution and fast switching speed without degradation of spurious signals (spurs) level performance is proposed. According to this structure, a high performance millimeter-wave frequency synthesizer with low spurious, low phase noise, and fast switching speed, is developed. This synthesizer driven by the direct digital synthesizer (DDS) AD9956 can adjust the output of a DDS and frequency division ratios of two variable frequency dividers (VFDs) to move the spurious components outside the loop bandwidth of the phase-locked loop (PLL). Moreover, the ADF4252 based microwave PLL can further suppress the phase noise. Experimental results from the implemented synthesizer show that remarkable performance improvements have been achieved.

Recently, a number of location-based services such as navigation and mobile advertising have been proposed. Such services require real-time user positions. Since a global positioning system (GPS), which is one of the most well-known techniques for real-time positioning, is unsuitable for indoor uses due to unavailability of GPS signals, many indoor positioning systems (IPSs) using WLAN, radio frequency identification tags, and so forth have been proposed. However, most of them suffer from high installation costs. In this paper, we propose a novel IPS for real-time positioning that utilizes a digital audio watermarking technique. The proposed IPS first embeds watermarks into an audio signal to generate watermarked signals, each of which is then emitted from a corresponding speaker installed in a target environment. A user of the proposed IPS receives the watermarked signals with a mobile device equipped with a microphone, and the watermarks are detected in the received signal. For positioning, we model various effects upon watermarks due to propagation in the air, i.e., delays, attenuation, and diffraction. The model enables the proposed IPS to accurately locate the user based on the watermarks detected in the received signal. The proposed IPS can be easily deployed with a low installation cost because the IPS can work with off-the-shelf speakers that have been already installed in most of the indoor environments such as department stores, amusement arcades, and airports. We experimentally evaluate the accuracy of positioning and show that the proposed IPS locates the user in a 6 m by 7.5 m room with root mean squared error of 2.25 m on average. The results also demonstrate the potential capability of real-time positioning with the proposed IPS.

This paper proposes likelihood smoothing techniques to improve decision tree-based acoustic models, where decision trees are used as replacements for Gaussian mixture models to compute the observation likelihoods for a given HMM state in a speech recognition system. Decision trees have a number of advantageous properties, such as not imposing restrictions on the number or types of features, and automatically performing feature selection. This paper describes basic configurations of decision tree-based acoustic models and proposes two methods to improve the robustness of the basic model: DT mixture models and soft decisions for continuous features. Experimental results for the Aurora 2 speech database show that a system using decision trees offers state-of-the-art performance, even without taking advantage of its full potential and soft decisions improve the performance of DT-based acoustic models with 16.8% relative error rate reduction over hard decisions.

This paper introduces a new dynamic 3D mesh representation that provides 3D animation support of progressive display and drastically reduces the amount of storage space required for 3D animation. The primary purpose of progressive display is to allow viewers to get animation as quickly as possible, rather than having to wait until all data has been downloaded. In other words, this method allows for the simultaneous transmission and playing of 3D animation. Experiments show that coarser 3D animation could be reconstructed with as little as 150 KB of data transferred. Using the sustained transmission of refined operators, viewers feel that resolution approaches that of the original animation. The methods used in this study are based on a compression technique commonly used in 3D animation - clustered principle component analysis, using the linearly independent rules of principle components, so that animation can be stored using smaller amounts of data. This method can be coupled with streaming technology to reconstruct animation through iterative updating. Each principle component is a portion of the streaming data to be stored and transmitted after compression, as well as a refined operator during the animation update process. This paper considers errors and rate-distortion optimization, and introduces weighted progressive transmitting (WPT), using refined sequences from optimized principle components, so that each refinement yields an increase in quality. In other words, with identical data size, this method allows each principle component to reduce allowable error and provide the highest quality 3D animation.

This paper proposes a novel scheme to reduce the complexity of existing transmit diversity solutions to time domain synchronous OFDM (TDS-OFDM). The space shifted constant amplitude zero autocorrelation (CAZAC) sequence based preamble is proposed for channel estimation. Two flexible frame structures are proposed for adaptive system design as well as cyclicity reconstruction of the received inverse discrete Fourier transform (IDFT) block. With regard to channel estimation and cyclicity reconstruction, the complexity of the proposed scheme is only around 7.20% of that of the conventional solutions. Simulation results demonstrate that better bit error rate (BER) performance can be achieved over doubly selective channels.

We propose a high-speed and low-complexity architecture for the very large-scale integration (VLSI) implementation of the maximum a posteriori probability (MAP) algorithm suited to the double binary turbo decoder. For this purpose, equation manipulations on the conventional Linear-Log-MAP algorithm and architectural optimization are proposed. It is shown by synthesized simulations that the proposed architecture improves speed, area and power compared with the state-of-the-art Linear-Log-MAP architecture. It is also observed that the proposed architecture shows good overall performance in terms of error correction capability as well as decoder hardware's speed, complexity and throughput.

This paper proposes a single-carrier transmission method based on an overlap frequency-domain equalizing (FDE) and a coherent averaging. FDE is a block-based equalizing technique using discrete Fourier transform. A cyclic prefix is often used to avoid inter-block interference under multipath channel conditions, which reduces transmission efficiency. An overlap FDE is a technique to avoid the cyclic prefix insertion, but the residual interferences often exist after the FDE processing according to the channel conditions. The method proposed in this paper suppresses the residual interferences by applying a coherent averaging to the FDE outputs and improve the equalization performances. Computer simulation shows the effect of the proposed technique over the multipath channels.

We have studied effects of additive elements into the channel layers of amorphous IGZO TFTs on threshold voltage shift issues under light illumination stress condition. By addition of Hf or Si element, the Vth shift under light illumination and negative bias-temperature stress and illumination stress conditions was drastically suppressed while the switching operation of TFTs using IGZO with Mn or Cu was not observed. It was found that the addition of Si or Hf element into the IGZO channel layer leads to reducing the hole trap sites formed at or near the gate insulator/IGZO channel interface.

We have previously proposed a howling canceller which cancels howling by using a cascade notch filter designed from a distance between a loudspeaker and a microphone. This method utilizes a pilot signal to estimate the distance. In this paper, we introduce two methods into the distance-based howling canceller to improve speech quality. The first one is an adaptive cascade notch filter which adaptively adjusts the nulls to eliminate howling and to keep speech components. The second one is a silent pilot signal whose frequencies exist in the ultrasonic band, and it is inaudible while on transmission. We implement the proposed howling canceller on a DSP to evaluate its capability. The experimental results show that the proposed howling canceller improves speech quality in comparison to the conventional one.

In this letter, we propose a power allocation scheme to optimize the ergodic secrecy rate of multiple-input single-output (MISO) fading wiretap channels with a probabilistic constraint, using the statistical channel state information (CSI) of the eavesdropper (CSI-E). The analytical expressions of the false secrecy probability are derived and used as constraints in the rate maximization problem. Moreover, we obtain a suboptimal solution by formulating the power allocation problem as a Rayleigh quotient problem.

An image appearance model called iCAM06 was designed for high dynamic range (HDR) image rendering. The dynamic range of an HDR image needs to be mapped on output devices, which is called tone compression or tone mapping. The iCAM06, the representative HDR rendering algorithm, uses tone compression for image reproduction on the low dynamic range of output devices. However, color saturation reduction occurs during its tone compression process. We propose a saturation correction method using the inverse compensation in order to recover the saturation reduction in the iCAM06. Experimental results show that the proposed method has better performance than the iCAM06 from the viewpoint of saturation accuracy and rendering preference.

We propose a simple approximate model for unslotted opportunistic spectrum access networks under nonsaturation conditions. The main simplification we introduce is that all secondary users, except a tagged one, in nonsaturated setting can be approximated by saturated ones with a scaled version of backoff interval. We analyze the approximate model and verify the model using simulations.

For amplify-and-forward (AF) relaying with imperfect channel estimation, we present the average symbol error rate (SER) and the diversity and multiplexing tradeoff (DMT) analysis for both opportunistic relaying (OPR) and all-participate relaying (APR) schemes. SER comparisons show that when the channel estimation quality order is no larger than 1, OPR will perform worse than APR in high SNR region. Moreover, small channel estimation quality orders will also lead to significant DMT loss.

In time division multiple access (TDMA)-based wireless mesh networks, interference relationships should be considered when time slots are assigned to links. In graph theory-based time slot assignment algorithms, the protocol interference model is widely used to determine radio interference information, although it is an inaccurate model of actual radio interference. On the other hand, the signal-to-interference-plus-noise-ratio model (SINR model) gives more accurate interference relationships but is difficult to apply to time slot assignment algorithms since the radio interference information cannot be determined before time slot assignment. In this paper, we investigate the effect of the parameters of the protocol interference model on the accuracy of the interference relationships determined using this model. Specifically, after assigning time slots to links based on the protocol interference model with various interference ratios, which is the major parameter of the protocol interference model, we compare the interference relationship among links in the protocol interference and SINR models. Through simulation experiments, we show that accuracy of the protocol interference model is improved by up to 15% by adjusting the interference ratios of the protocol interference model.

In 2010, Guo and Zhang proposed a group key agreement protocol based on the chaotic hash function. This letter points out that Guo-Zhang's protocol is still vulnerable to off-line password guessing attacks, stolen-verifier attacks and reflection attacks.

Power analysis can be used to attack many implementations of cryptosystems, e.g., RSA and ECC, and the doubling attack is a collision based power analysis performed on two chosen ciphertexts. In this paper, we introduced a modified doubling attack to threaten RSA and ECC implementations by exploiting only one chosen ciphertext of small order. To attack the RSA implementations we selected an input of order two while to attack the ECC implementations we exploited one chosen invalid point of small order on a cryptographically weak curve rather than on the original curve. We showed that several existing power analysis countermeasures for RSA and ECC implementations are still vulnerable to the proposed attack. To prevent the proposed attack, we suggested countermeasures for RSA as well as for ECC.

This letter presents a novel user scheduling algorithm that provides a maximum sum-rate based on zero-forcing beamforming (ZFBF) in multiple-input multiple-output (MIMO) systems. The proposed technique determines primary user pairs in which the sum-rate exceeds a predetermined threshold. To determine the threshold, we define the maximum-sum-rate criterion (MSRC) derived from the extreme value theory (EVT). Applying the MSRC in ZFBF-based user scheduling, we find that the performance of the proposed method is comparable to that of the exhaustive searching scheme which has a greater computational load. Through computer simulations, we show that the proposed method outperforms the very well-known correlation-based method, semi-orthogonal user selection (SUS), yielding a sum rate that is about 0.57 bps/Hz higher when the transmit SNR is 10 dB with perfect CSI at BS and the numbers of users and transmit antennas in a cell are 100 and 4, respectively.

This paper proposes a novel waveguide intersection separating two H-plane waveguide systems from each other. If a four-port network in a four-fold rotational symmetry is completely matched, it has necessarily intersection properties. The proposed waveguide intersection consists of a square H-plane waveguide planar circuit connected four input/output waveguide ports in a four-fold rotational symmetry, and several metallic posts inserted at the junction without destroying the symmetry to realize a perfect matching. By optimizing the circuit parameters, high isolation properties are obtained in a relatively wide frequency band of about 8.6% for return loss and isolation better than 20 and 30 dB, respectively, for a circuit designed at 10 GHz. The proposed waveguide intersection can be analyzed by H-plane planar circuit approach, and possess advantages of compactness, simplicity, and high-power handling capability. Furthermore, an SIW intersection is designed by applying H-plane planar circuit approach to a waveguide circuit filled with dielectric material, and high isolation properties similar to H-plane waveguide intersection can be realized. The validity of these design concepts is confirmed by em-simulations and experiments.

In this paper, we show that the covariance-eigenvalue approach converges much faster than using cumulative distribution function (CDF) for determining diversity gain from channel measurements in reverberation chamber. The covariance-eigenvalue approach can be used for arbitrary multi-port antennas, but it is limited to Maximum Ratio Combining (MRC).

Kernel biased discriminant analysis (KBDA), as a subspace learning algorithm, has been an attractive approach for the relevance feedback in content-based image retrieval. Its performance, however, still suffers from the “small sample learning” problem and “kernel learning” problem. Aiming to solve these problems, in this paper, we present a new semi-supervised scheme of KBDA (S-KBDA), in which the projection learning and the “kernel learning” are interweaved into a constrained optimization framework. Specifically, S-KBDA learns a subspace that preserves both the biased discriminant structure among the labeled samples, and the geometric structure among all training samples. In kernel optimization, we directly optimize the kernel matrix, rather than a kernel function, which makes the kernel learning more flexible and appropriate for the retrieval task. To solve the constrained optimization problem, a fast algorithm based on gradient ascent is developed. The image retrieval experiments are given to show the effectiveness of the S-KBDA scheme in comparison with the original KBDA, and the other two state-of-the-art algorithms.