The collision of ID signals from a large number of co-located passive RFID tags is a serious problem; to realize a practical RFID systems we need an effective anti-collision algorithm. This letter presents an adaptive algorithm to minimize the total time slots and the number of rounds required for identifying the tags within the RFID reader's interrogation zone. The proposed algorithm is based on the framed ALOHA protocol, and the frame size is adaptively updated each round. Simulation results show that our proposed algorithm is more efficient than the conventional algorithms based on the framed ALOHA.

We suggest a dual thresholds method for the dynamic bandwidth allocation in EPON. In the suggested method, a buffer in ONU has two thresholds and ONU generates a normal request and a greedy request based on the two thresholds. Also, OLT estimates the overall traffic load and grants the greedy request when estimated traffic is light. We study upstream channel resource wastage and show the suggested method decreases the upstream channel resource wastage. Using simulation, we validate the dual thresholds method is superior to the existing methods in the mean delay.

This letter presents a novel frame splitting scheme for an error-robust audio streaming over packet-switching networks. In our approach to perceptual audio coding, an audio frame is split into several subframes based on the network configuration such that each packet can be decoded independently at the receiver. Through a subjective comparison category rating (CCR) test, it is discovered that our approach enhances the quality of the decoded audio signal under the lossy packet-switching networks environment.

We say that a signature scheme is strongly existentially unforgeable (SEU) if no adversary, given message/signature pairs adaptively, can generate a signature on a new message or a new signature on a previously signed message. We propose a general and efficient conversion in the standard model that transforms a secure signature scheme to SEU signature scheme. In order to construct that conversion, we use a chameleon commitment scheme. Here a chameleon commitment scheme is a variant of commitment scheme such that one can change the committed value after publishing the commitment if one knows the secret key. We define the chosen message security notion for the chameleon commitment scheme, and show that the signature scheme transformed by our proposed conversion satisfies the SEU property if the chameleon commitment scheme is chosen message secure. By modifying the proposed conversion, we also give a general and efficient conversion in the random oracle model, that transforms a secure signature scheme into a SEU signature scheme. This second conversion also uses a chameleon commitment scheme but only requires the key only attack security for it.

Auto-calibration for structure and motion recovery can be used for match move where the goal is to insert synthetic 3D objects into real scenes and create views as if they were part of the real scene. However, most auto-calibration methods for multi-views utilize bundle adjustment with non-linear optimization, which requires a very good starting approximation. We propose a novel key-frame selection measurement and LMedS (Least Median of Square)-based approach to estimate scene structure and motion from image sequences captured with a hand-held camera. First, we select key-frames considering the ratio of number of correspondences and feature points, the homography error and the distribution of corresponding points in the image. Then, by using LMedS, we reject erroneous frames among the key-frames in absolute quadric estimation. Simulation results demonstrated that the proposed method can select suitable key-frames efficiently and achieve more precise camera pose estimation without non-linear optimization.

The problem of estimating the timing of ultra-wide band signal is considered in the letter. We develop a maximum likelihood timing estimation algorithm for binary PAM DS-UWB systems. The derivation of the proposed algorithm is based on the known training sequence and AWGN channel. The Cramer-Rao Bound (CRB) for the ML timing estimator is presented as a performance benchmark. It is found via numerical results that the ML timing estimator on AWGN channels achieves the CRB when the values of Eb/N0 for the observation bits Nb=50 are sufficiently high. Finally, the performance of the proposed ML estimator is evaluated on actual channels with intersymbol interference such as an IEEE UWB indoor multipath channel model.

Software rejuvenation is a preventive and proactive solution that is particularly useful for counteracting the phenomenon of software aging. In this article, we consider periodic software rejuvenation models based on the expected cost per unit time in the steady state under discrete-time operation circumstance. By applying the discrete renewal reward processes, we describe the stochastic behavior of a telecommunication billing application with a degradation mode, and determine the optimal periodic software rejuvenation schedule minimizing the expected cost. Similar to the earlier work by the same authors, we develop a statistically non-parametric algorithm to estimate the optimal software rejuvenation schedule, by applying the discrete total time on test concept. Numerical examples are presented to estimate the optimal software rejuvenation schedules from the simulation data. We discuss the asymptotic behavior of estimators developed in this paper.

In this paper we propose a discrete program-size dependent software reliability growth model flexibly describing the software failure-occurrence phenomenon based on a discrete Weibull distribution. We also conduct model comparisons of our discrete SRGM with existing discrete SRGMs by using actual data sets. The program size is one of the important metrics of software complexity. It is known that flexible discrete software reliability growth modeling is difficult due to the mathematical manipulation under a conventional modeling-framework in which the time-dependent behavior of the cumulative number of detected faults is formulated by a difference equation. Our discrete SRGM is developed under an existing unified modeling-framework based on the concept of general order-statistics, and can incorporate the effect of the program size into software reliability assessment. Further, we discuss the method of parameter estimation, and derive software reliability assessment measures of our discrete SRGM. Finally, we show numerical examples of discrete software reliability analysis based on our discrete SRGM by using actual data.

Wireless content sharing where peers share content and services via wireless access networks requires user contributions, as in fixed P2P content sharing. However, in wireless access environments, since the resources of mobile terminals are strictly limited, mobile users are not as likely to contribute as ones in fixed environments. Therefore, incentives to encourage user contributions are more significant in wireless access environments. Although an incentive service differentiation architecture where the content transfer rate is adjusted according to the contributions of each downloading user has been already proposed for fixed P2P, it may not work well in wireless access environments because several factors effect wireless throughput. In this paper, we propose a novel architecture for contribution-based transfer-rate differentiation using wireless quality of service (QoS) techniques that motivates users to contribute their resources for wireless content sharing. We also propose a radio resource assignment method for our architecture. Computer simulations and game-theoretic calculations validate our architecture.

Most learning-based super-resolution methods neglect the illumination problem. In this paper we propose a novel method to combine blind single-frame super-resolution and shadow removal into a single operation. Firstly, from the pattern recognition viewpoint, blur identification is considered as a classification problem. We describe three methods which are respectively based on Vector Quantization (VQ), Hidden Markov Model (HMM) and Support Vector Machines (SVM) to identify the blur parameter of the acquisition system from the compressed/uncompressed low-resolution image. Secondly, after blur identification, a super-resolution image is reconstructed by a learning-based method. In this method, Logarithmic-wavelet transform is defined for illumination-free feature extraction. Then an initial estimation is obtained based on the assumption that small patches in low-resolution space and patches in high-resolution space share a similar local manifold structure. The unknown high-resolution image is reconstructed by projecting the intermediate result into general reconstruction constraints. The proposed method simultaneously achieves blind single-frame super-resolution and image enhancement especially shadow removal. Experimental results demonstrate the effectiveness and robustness of our method.

A parametric linear filter for a linear observation model usually requires a parameter selection process so that the filter achieves a better filtering performance. Generally, criteria for the parameter selection need not only the filtered solution but also the filter itself with each candidate of the parameter. Obtaining the filter usually costs a large amount of calculations. Thus, an efficient algorithm for the parameter selection is required. In this paper, we propose a fast parameter selection algorithm for linear parametric filters that utilizes a joint diagonalization of two non-negative definite Hermitian matrices.

We describe a new ultrasonography system, which can identify an implant position in bone. Although conventional X-ray fluoroscopy can visualize implants, it has the serious disadvantage of X-ray exposure. Therefore, we developed a system for orthopedic surgery that involves no X-ray exposure. Barriers to the development of the system were overcome using an ultrasonic instrument and fuzzy logic techniques. We located distal transverse screw holes in an intramedullary nail during surgery for femur fracture. The screw hole positions are identified by calculating two fuzzy degrees of intensity and the variance. Results allow this system to identify the screw hole positions within an error of 1.43 mm, an error ratio adequate for clinical surgical practice.

In ubiquitous networks, Mobile Nodes (MNs) often suffer from performance degradation due to the following two reasons: (1) reduction of signal strength by the movement of an MN and intervening objects, and (2) radio interference with other WLANs. Therefore, handover initiation based on quick and reliable detection of the deterioration in a wireless link condition arising from the above two reasons is essential for achieving seamless handover. In previous studies, we focused on a handover decision criterion and described the problems related to the two existing decision criteria. Furthermore, we showed the effectiveness of the number of frame retransmissions through simulation experiments. However, a comparison of the signal strength and the number of frame retransmissions could not be examined due to the unreliability of the signal strength in simulations. Therefore, in the present paper, by employing FTP and VoIP applications, we compare the signal strength and the number of frame retransmissions as a handover decision criterion with experiments in terms of (1) and (2) in a real environment. Finally, we clarify the problem of the signal strength in contrast to the effectiveness of the number of frame retransmissions as a handover decision criterion.

This paper presents an ultra wideband (UWB) channel sounding scheme with a technique for estimating time of arrival (TOA) and angle of arrival (AOA) using measurement signals. Since the power spectrum over the UWB bandwidth can be measured in advance, we propose a signal model using the measurement power spectrum to design the proper UWB signals model. This signal model is more similar to measurement signals than the flat spectrum model which is an ideal model. If more than three waves impinge on a receiver, we must determine the proper grouping of the elements of TOA vector and AOA vector. It is difficult to determine the grouping using only measurement signals because of many degradation factors. We also propose pairing the elements of TOA vector and that of AOA vector using correlation method based on measurement signals and the proposed signal model. This technique is available for more than the case of three paths if pairing the estimated TOAs and AOAs of measurement signals is not accurately determined. We evaluated the proposed techniques for a vector network analyzer (VNA) with a three-dimensional virtual antenna array.

This paper describes the experimental evaluation of a testbed with a simple decision-feedback channel tracking scheme for MIMO-OFDM systems. The channel tracking scheme periodically estimates the channel state matrix for each subcarrier from received signals and replicas of the transmitted signal. The estimated channel state matrices, which are obtained at mutually different timings, are combined based on maximum ratio combining and used for MIMO signal detection. The testbed was implemented on field programmable gate arrays (FPGAs) of 1/5 scale, which confirms the implementation feasibility of the channel tracking scheme. The packet error rate (PER) and mobility performance of the testbed were measured. The testbed employed a 22 MIMO channel, zero-forcing algorithm for MIMO signal detection, 16QAM for the subcarrier modulation scheme, and coding rate of 1/2. The proposed scheme suppressed the increase in the required SNR for PER of 10-2 to less than 1 dB when the relative velocity between the transmitter and the receiver was less than 45 km/h assuming 5 GHz band operation. In addition, the proposed scheme offers 6.3% better throughput than the conventional scheme. The experimental results demonstrate that the channel tracking scheme implemented in the testbed effectively tracks the fluctuation of a MIMO channel.

A blind joint parametric channel estimation and non-coherent data detection algorithm is proposed for the downlink of an orthogonal-frequency-division-multiplexing code-division-multiple-access (OFDM-CDMA) system with multiple-input-multiple-output (MIMO) antenna arrays. To reduce the computational complexity, we first develop a tree-structured algorithm to estimate high dimensional parameters predominantly describing the involved multipath channels by employing several stages of low dimensional parameter estimation algorithms. In the tree structure, to exploit the space-time distribution of the receive multipath signals, spatial beamformers and spectral filters are adopted for clustered-multipath grouping and path isolation. In conjunction with the multiple access interference (MAI) suppression techniques, the proposed tree architecture algorithm jointly estimates the direction of arrivals, propagation delays, carrier frequency offsets and fading amplitudes of the downlink wireless channels in a MIMO OFDM-CDMA system. With the outputs of the tree architecture, the signals of interest can then be naturally detected with a path-wise maximum ratio combining scheme.

This paper presents 3D keyframe animation watermarking using orientation interpolators. 3D keyframe animation consists of a number of transform nodes, including a geometrical node from the initial model and several interpolator nodes that represent object movement. Therefore, the proposed algorithm randomly selects transform nodes with orientation interpolator nodes, then resamples the quaternion components to maintain a uniform key time. Thereafter, watermark bits are embedded into quaternion components with large rotation angles. Experimental results verify the robustness of the proposed algorithm to geometrical and timeline attacks, along with the subjective and objective quality of its invisibility.

To describe joint time- and frequency-selective (doubly-selective) channels in mobile broadband wireless communications, we propose to use the finite parameter model based on the same Bessel functions for each tap (Bessel model). An expression of channel estimation mean squared error (MSE) based on the finite parameter models in Orthogonal Frequency Division Multiplexing (OFDM) systems is derived. Then, our Bessel model is compared with commonly used finite parameter models in terms of the channel estimation MSE. Even if the channel taps have different channel correlations and some of the taps do not coincide with the Bessel function, the channel estimation MSE of the Bessel model is shown to be comparable or outperform existing models as validated by Monte-Carlo simulations over an ensemble of channels in typical urban and suburban environments.

In recent years, algorithms based on Computer Algebra ([1]-[3]) have been introduced into a range of control design problems because of the capacity to handle unknown parameters as indeterminates. This feature of algorithms in Computer Algebra reduces the costs of computer simulation and the trial and error process involved, enabling us to design and analyze systems more theoretically with the behavior of given parameters. In this paper, we apply Computer Algebra algorithms to H∞ control theory, representing one of the most successful achievements in post-modern control theory. More specifically, we consider the H∞ norm minimization problem using a state feedback controller. This problem can be formulated as follows: Suppose that we are given a plant described by the linear differential equation = Ax + B1w + B2u, z = Cx + Du, where A,B1,B2,C,D are matrices whose entries are polynomial in an unknown parameter k. We apply a state feedback controller u = -F x to the plant, where F is a design parameter, and obtain the system = (A - B2F)x + B1w, z =(C - DF)x. Our task is to compute the minimum H∞ norm of the transfer function G(s)(=(C - DF)(sI - A + B2F)-1B1) from w to z achieved using a static feedback controller u = -Fx, where F is a constant matrix. In the H∞ control theory, it is only possible to check if there is a controller such that ||G(s)||∞ < γ is satisfied for a given number γ, where ||G(s)||∞ denotes the H∞ norm of the transfer function G(s). Thus, a typical procedure to solve the H∞ optimal problem would involve a bisection method, which cannot be applied to plants with parameters. In this paper, we present a new method of solving the H∞ norm minimization problem that can be applied to plants with parameters. This method utilizes QE (Quantifier Elimination) and a variable elimination technique in Computer Algebra, and expresses the minimum of the H∞ norm as a root of a bivariate polynomial. We also present a numerical example to illustrate each step of the algorithm.

The open-vocabulary name recognition technique is one of the most challenging tasks in the application of automatic Chinese speech recognition technology. It can be used as the free name input method for telephony speech applications and automatic directory assistance systems. A Chinese name usually has two to three characters, each of which is pronounced as a single tonal syllable. Obviously, it is very confusing to recognize a three-syllable word from millions to billions of possible candidates. A novel interactive automatic-speech-recognition system is proposed to resolve this highly challenging task. This system was built as an open-vocabulary Chinese name recognition system using character-based approaches. Two important character-input speech-recognition modules were designed as backoff approaches in this system to complete the name input or to correct any misrecognized characters. Finite-state networks were compiled from regular grammar of syllable spellings and character descriptions for these two speech recognition modules. The possible candidate names cover more than five billions. This system has been tested publicly and proved a robust way to interact with the speaker. An 86.7% name recognition success rate was achieved by the interactive open-vocabulary Chinese name input system.