This paper presents a new type of electromagnetic interference (EMI) measurement system. An EMI Camera LSI (EMcam) with a 124 on-chip 25050 µm2 loop antenna matrix in 65 nm CMOS is developed. EMcam achieves both the 2D electric scanning and 60 µm-level spatial precision. The down-conversion architecture increases the bandwidth of EMcam and enables the measurement of EMI spectrum up to 3.3 GHz. The shared IF-block scheme is proposed to relax both the increase of power and area penalty, which are inherent issues of the matrix measurement. The power and the area are reduced by 74% and 73%, respectively. EMI measurement with the smallest 3212 µm2 antenna to date is also demonstrated.

The mining of a complete set of frequent subgraphs from labeled graph data has been studied extensively. Furthermore, much attention has recently been paid to frequent pattern mining from graph sequences (dynamic graphs or evolving graphs). In this paper, we define a novel subgraph subsequence class called an “induced subgraph subsequence” to enable the efficient mining of a complete set of frequent patterns from graph sequences containing large graphs and long sequences. We also propose an efficient method for mining frequent patterns, called “FRISSs (Frequent Relevant, and Induced Subgraph Subsequences)”, from graph sequences. The fundamental performance of the method is evaluated using artificial datasets, and its practicality is confirmed through experiments using a real-world dataset.

We formulate the resource allocation problem to maximize the sum rate, subject to constraints on total power, bit error rate, and rate proportionality among the users for proportional resource allocation in orthogonal frequency division multiple access (OFDMA) systems. For this we propose a novel scheduling scheme based on weighted normalized user's channel state information (CSI). We then adopt the linear power distribution method and waterfilling technique to allocate power among the users and across the subcarriers respectively.

This paper considers a simple type of Dynamic Element Matching (DEM), Clocked Averaging (CLA) method referred to as one-element-shifting (OES) and its effectiveness for the implementation of high spurious-free dynamic range (SFDR) multi-bit Delta-Sigma modulators (DSMs). Generic DEM techniques are successful at suppressing the mismatch error and increasing the SFDR of data converters. However, they will induce additional glitch energy in most cases. Some recent DEM methods achieve improvements in minimizing glitch energy but sacrificing their effects in harmonic suppression due to mismatches. OES technique discussed in this paper can suppress the effect of glitch while preserving the reduction of element mismatch effects. Hence, this approach achieves better SFDR performance over the other published DEM methods. With this OES, a 3rd order, 10 MHz bandwidth continuous-time DSM is implemented in 90 nm CMOS process. The measured SFDR attains 83 dB for a 10 MHz bandwidth. The measurement result also shows that OES improves the SFDR by higher than 10 dB.

We propose and implement a cloud architecture of virtual Trusted Platform Modules (TPMs) to improve the usability of TPMs. In this architecture, virtual TPMs can be obtained from the TPM cloud on demand. Hence, the TPM functionality is available for applications that do not have physical TPMs in their local platforms. Moreover, the TPM cloud allows users to access their keys and data in the same virtual TPM even if they move to untrusted platforms. The TPM cloud is easy to access for applications in different languages since cloud computing delivers services in standard protocols. The functionality of the TPM cloud is demonstrated by applying it to implement the Needham-Schroeder public-key protocol for web authentications, such that the strong security provided by TPMs is integrated into high level applications. The chain of trust based on the TPM cloud is discussed and the security properties of the virtual TPMs in the cloud is analyzed.

Mel Frequency Cepstral Coefficients (MFCC) are the most popular acoustic features used in automatic speech recognition (ASR), mainly because the coefficients capture the most useful information of the speech and fit well with the assumptions used in hidden Markov models. As is well known, MFCCs already employ several principles which have known counterparts in the peripheral properties of human hearing: decoupling across frequency, mel-warping of the frequency axis, log-compression of energy, etc. It is natural to introduce more mechanisms in the auditory periphery to improve the noise robustness of MFCC. In this paper, a k-nearest neighbors based frequency masking filter is proposed to reduce the audibility of spectra valleys which are sensitive to noise. Besides, Moore and Glasberg's critical band equivalent rectangular bandwidth (ERB) expression is utilized to determine the filter bandwidth. Furthermore, a new bandpass infinite impulse response (IIR) filter is proposed to imitate the temporal masking phenomenon of the human auditory system. These three auditory perceptual mechanisms are combined with the standard MFCC algorithm in order to investigate their effects on ASR performance, and a revised MFCC extraction scheme is presented. Recognition performances with the standard MFCC, RASTA perceptual linear prediction (RASTA-PLP) and the proposed feature extraction scheme are evaluated on a medium-vocabulary isolated-word recognition task and a more complex large vocabulary continuous speech recognition (LVCSR) task. Experimental results show that consistent robustness against background noise is achieved on these two tasks, and the proposed method outperforms both the standard MFCC and RASTA-PLP.

This paper presents an ADPLL using a hierarchical TDC composed of a 4fLO DCO followed by a divide-by-4 circuit and three stages of known phase interpolators. We derived simple design requirements for ensuring precision of the phase interpolator. The proposed architecture provides immunity to PVT and local variations, which allows calibration-free operation, as well as sub-inverter delay resolution contributing to good in-band phase noise performance. Also the hierarchical TDC makes it possible to employ a selective activation scheme for power saving. Measured performances demonstrate the above advantages and the in-band phase noise reaches -104 dBc/Hz. It is fabricated in a 65 nm CMOS process and the active area is 0.18 mm2.

In this paper, to reduce the memory size requirements of IFFT for OFDM-based applications, we propose a new IFFT design technique based on a combined integer mapping of three IFFT input signals: modulated data, pilot and null signals. The proposed method focuses on reducing the size of memory cells in the first two stages of the single-path delay feedback (SDF) IFFT architectures since the first two stages require 75% of the total memory cells. By simulations of 2048-point IFFT design for cognitive radio systems, it is shown that the proposed IFFT design method achieves more than 13% reduction in gate count and 11% reduction in power consumption compared with conventional IFFT design.

In the work we introduce novel approach to remote sensing from space for the estimation of sea wave heights with a spaceborne high precision two-frequency radar altimeter with nadir synthesis antenna aperture. Experiments show considerable reduction of the decorrelation factor of the correlation coefficient and so significant enhancement of the sensitivity of the altimeter for the estimation for the sea wave status.

We study threshold-based relaying in an amplify-and-forward (AF) cooperative diversity network. For the network, the relay helps the communication from the source to the destination only if the signal-to-noise ratio (SNR) of the link from the source to the relay is greater than or equal to a pre-determined threshold value; otherwise, the relay remains silent. We derive the exact bit-error rate (BER) of the threshold-based relaying for M-pulse amplitude modulation (PAM) and M-quadrature amplitude modulation (QAM). The obtained BER expression can help the design of the threshold-based relaying in determining the system parameters such as the transmission power, the amplifying coefficient at the relay, and the pre-determined threshold value.

A direct inter-mode selection algorithm for P-frames in fast homogeneous H.264/AVC bit-rate reduction transcoding is proposed in this paper. To achieve the direct inter-mode selection, we firstly develop a low-complexity distortion estimation method for fast transcoding, in which the distortion is directly calculated from the decoded residual together with the reference frames. We also present a linear estimation method to approximate the coding rate. With the estimated distortion and rate, the rate-distortion cost can be easily computed in the transcoder. In our algorithm, a method based on the normalized rate difference of P-frames (RP) is used to detect the high motion scene. To achieve fast transcoding, only for the P-frames with RP larger than a threshold, the rate-distortion optimized (RDO) mode decision is performed; meanwhile, the average cost of each inter-mode (ACM) is calculated. Then for the subsequent frames transcoding, the optimal coding mode can be directly selected using the estimated cost and the ACM threshold. Experiments show that the proposed method can significantly simplify the complex RDO mode decision, and achieve transcoding time reductions of up to 62% with small loss of rate-distortion performance.

A partial transmit sequence with a clipping (PTS-Clipping) method can reduce considerably high peak-to-average power ratio (PAPR) of orthogonal frequency division multiplexing (OFDM) signal. However, exhaustive searching operations are needed in order to find optimal phase factors. Signal distortions also occur because the clipping is a nonlinear operation. In this letter, we propose a new partial transmit sequence (PTS) scheme using a phase factor selection algorithm with preset thresholds. The proposed scheme achieves considerable savings for determining the optimum phase factors without the signal distortions.

This report focuses on a design method for gradient index (GRIN) lens antennas with controllable aperture field distributions. First, we derive differential equations representing optical paths in a gradient index medium with two optical surfaces by using geometrical optics, and then we formulate a novel design method for GRIN lens antennas based on these equations. The Levenberg-Marquardt algorithm is applied as a nonlinear least squares method to satisfy two conditions-focusing and shaping the aperture field distribution-thus realizing a prescribed radiation pattern. The conditions can be fulfilled by optimizing only the index (or permittivity) distribution, whereas the shapes of the optical surfaces remain as free parameters that can be utilized for other purposes, such as reducing reflection losses that occur on the surfaces, as illustrated in this report. A plano-concave GRIN lens is designed as an example, applying the proposed method, to realize a sidelobe level of -30 dB pseudo Taylor distribution, and a maximum sidelobe level of -29.1 dB was observed, indicating it is sufficiently accurate for practical use. In addition, we discuss the convergence of this method considering the relationship between the number of the initial conditions and the differential order of the design equations, factoring in scale invariance of the design equations.

Nowadays portable devices with multiple wireless interfaces and using multimedia services are becoming more popular on the Internet. This paper describes a family of multipath binomial congestion control algorithms for audio/video streaming, where a low variant of transmission rate is important. We extend the fluid model of binomial algorithms for single-path transmission to support the concurrent transmission of packets across multiple paths. We focus on the extension of two particular algorithms, SQRT and IIAD, for multiple paths, called MPSQRT and MPIIAD, respectively. Additionally, we apply the design technique (using the multipath fluid model) for multipath TCP (MPTCP) into the extension of SQRT and IIAD, called fbMPSQRT and fbMPIIAD, respectively. Both two approaches ensure that multipath binomial congestion control algorithms achieve load-balancing, throughput improvement, and fairness to single-path binomial algorithms at shared bottlenecks. Through the simulations and comparison with the uncoordinated protocols MPSQRT/MPIIAD, fbMPSQRT/fbMPIIAD and MPTCP, we find that our extended multipath transport protocols can preserve lower latency and transmission rate variance than MPTCP, fairly share with single-path SQRT/IIAD, MPTCP and TCP, and also can achieve throughput improvements and load-balancing equivalent to those of MPTCP under various scenarios and network conditions.

We propose an optimal access-point (AP) selection algorithm for maximizing the aggregated throughput of each AP (system throughput) while preserving newly arrived-user throughput in multi rate WLAN system. In our algorithm, newly arrived users cooperate with a wireless local area network (WLAN) system they are trying to use, i.e., they are willing to move toward an appropriate AP before the newly arrived user connects to AP. To select the AP by using our AP selection algorithm, the newly arriving users request two novel parameter values, “the minimum acceptable throughput” with which newly arrived users can be satisfied and “the minimum movable distance” in which a user can move to an appropriate AP. While preserving these conditions, we maximize system throughput. When users cannot obtain a throughput greater than “the minimum acceptable throughput” with our proposed AP selection algorithm, they are rejected. Because, if users use streaming applications, which have strict bandwidth demands, with a very low bit-rate connection, they will not be satisfied. Thus, the newly arrived users having low bit-rate connection may be allowed to be rejected before the newly arrived user connects. In this paper, we show the optimal AP by using theoretical proof. We discuss the effectiveness of our proposed AP selection algorithm by using numerical analysis. We also clarify and analyze the characteristics of system throughput. Moreover, we show that a newly arrived user can select the movable distance and acceptable throughput by using examples from graphs depicting every position of newly arrived users. By using the graphs, we also show the relationship between the two parameters (the movable distance and the acceptable throughput) and the optimal AP, and the relationship between the two parameters and optimal system throughput when the movable distance and acceptable throughput are variable.

With the consideration of real-time stream processing technology, it's important to develop high availability mechanism to guarantee stream-based application not interfered by faults caused by potential anomalies. In this paper, we present a novel online prediction technique for predicting some anomalies which may occur in the near future. Concretely, we first present a value prediction which combines the Hidden Markov Model and the Mixture of Expert Model to predict the values of feature metrics in the near future. Then we employ the Support Vector Machine to do anomaly identification, which is a procedure to identify the kind of anomaly that we are about to alarm. The purpose of our approach is to achieve a tradeoff between fault penalty and resource cost. The experiment results show that our approach is of high accuracy for common anomaly prediction and low runtime overhead.

In this letter, we address the issue of estimating the temporal dependence characteristic of link loss by using network tomography. We use a k-th order Markov chain (k > 1) to model the packet loss process, and estimate the state transition probabilities of the link loss model using a constrained optimization-based method. Analytical and simulation results indicate that our method yields more accurate packet loss probability estimates than existing loss inference methods.

Most large-scale Peer-to-Peer (P2P) live streaming systems are constructed as a mesh structure, which can provide robustness in the dynamic P2P environment. The pull scheduling algorithm is widely used in this mesh structure, which degrades the performance of the entire system. Recently, network coding was introduced in mesh P2P streaming systems to improve the performance, which makes the push strategy feasible. One of the most famous scheduling algorithms based on network coding is R2, with a random push strategy. Although R2 has achieved some success, the push scheduling strategy still lacks a theoretical model and optimal solution. In this paper, we propose a novel optimal pull-push scheduling algorithm based on network coding, which consists of two stages: the initial pull stage and the push stage. The main contributions of this paper are: 1) we put forward a theoretical analysis model that considers the scarcity and timeliness of segments; 2) we formulate the push scheduling problem to be a global optimization problem and decompose it into local optimization problems on individual peers; 3) we introduce some rules to transform the local optimization problem into a classical min-cost optimization problem for solving it; 4) We combine the pull strategy with the push strategy and systematically realize our scheduling algorithm. Simulation results demonstrate that decode delay, decode ratio and redundant fraction of the P2P streaming system with our algorithm can be significantly improved, without losing throughput and increasing overhead.

This paper proposes applying our inter-cell interference (ICI) cancellation method to fractional frequency reuse (FFR) and evaluates the resulting spectral efficiency improvement. With our ICI cancellation method based on base station cooperation, the control station generates ICI replica signals by simple linear processing. Moreover, FFR effectively utilizes frequency resources by both allowing users in the cell-center region to access all available sub-channels and increasing the transmission power to users in the cell-edge region. FFR provides the conditions under which the ICI cancellation method works effectively. Computer simulations show that the average spectral efficiency of the proposed method is comparable to that of cooperative MU-MIMO, which can completely remove ICI.

As ROADMs (Reconfigurable Optical Add/Drop Multiplexers) are becoming widely used in metro/core networks, distributed control of wavelength paths by extended GMPLS (Generalized MultiProtocol Label Switching) protocols has attracted much attention. For the automatic establishment of an arbitrary wavelength path satisfying dynamic traffic demands over a ROADM or WXC (Wavelength Cross Connect)-based network, precise determination of chromatic dispersion over the path and optimized assignment of dispersion compensation capabilities at related nodes are essential. This paper reports an experiment over in-field fibers where GMPLS-based control was applied for the automatic discovery of chromatic dispersion, path computation, and wavelength path establishment with dynamic adjustment of variable dispersion compensation. The GMPLS-based control scheme, which the authors called GMPLS-Plus, extended GMPLS's distributed control architecture with attributes for automatic discovery, advertisement, and signaling of chromatic dispersion. In this experiment, wavelength paths with distances of 24 km and 360 km were successfully established and error-free data transmission was verified. The experiment also confirmed path restoration with dynamic compensation adjustment upon fiber failure.