In this paper, an imaging components transmission scheme for the improvement of multipath delay resolution in a Fractional Sampling (FS) OFDM receiver is proposed. FS has been proposed as a diversity scheme and achieves path diversity by enlarging the bandwidth of the baseband filters in order to transmit the imaging components of the desired signal. However, FS is not able to achieve diversity with very short delay multipaths because of its low multipath delay resolution. Wider bandwidth of the transmission signal is required to improve the resolution of the delay. On the other hand, cognitive radio is an emerging technology to utilize frequency spectrum flexibly through dynamic spectrum access (DSA). To resolve the small delay multipaths and to use the spectrum flexibly with DSA, this paper investigates the FS path diversity with the imaging components on the separated frequency channel. The correlation between the 2 FS branches is analyzed theoretically on the 2 path channel under the conditions of sampling interval, delay spread, and frequency separation. Numerical results through computer simulation show that the proposed scheme improves the multipath resolution and the bit error rate (BER) performance under the existence of small delay multipaths.

Link prediction is the task of inferring the existence or absence of certain relationships among data objects such as identity, interaction, and collaboration. Link prediction is found in various applications in the fields of information integration, recommender systems, bioinformatics, and social network analysis. The increasing interest in dynamically changing networks has led to growing interest in a more general link prediction problem called temporal link prediction in the data mining and machine learning communities. However, only links among nodes at the same time point are considered in temporal link prediction. We propose a new link prediction problem called cross-temporal link prediction in which the links among nodes at different time points are inferred. A typical example of cross-temporal link prediction is cross-temporal entity resolution to determine the identity of real entities represented by data objects observed in different time periods. In dynamic environments, the features of data change over time, making it difficult to identify cross-temporal links by directly comparing observed data. Other examples of cross-temporal links are asynchronous communications in social networks such as Facebook and Twitter, where a message is posted in reply to a previous message. We adopt a dimension reduction approach to cross-temporal link prediction; that is, data objects in different time frames are mapped into a common low-dimensional latent feature space, and the links are identified on the basis of the distance between the data objects. The proposed method uses different low-dimensional feature projections in different time frames, enabling it to adapt to changes in the latent features over time. Using multi-task learning, it jointly learns a set of feature projection matrices from the training data, given the assumption of temporal smoothness of the projections. The optimal solutions are obtained by solving a single generalized eigenvalue problem. Experiments using a real-world set of bibliographic data for cross-temporal entity resolution and a real-world set of emails for unobserved asynchronous communication inference showed that introducing time-dependent feature projections improved the accuracy of link prediction.

In recent years, there has been an increasing demand with regard to available elemental services provided by independent firms for compositing new services. Currently, however, whenever it is difficult to maintain the required level of quality of a new composite web service, assignment of the new computer's resources as provisioning at the data center is not always effective, especially in the area of performance for composite web service providers. Thus, a new approach might be required. This paper presents a new control method aiming to maintain the performance requirements for composite web services. There are three aspects of our method that are applied: first of all, the theory of constraints (TOC) proposed by E.M. Goldratt ; secondly, an evaluation process in the non-linear feed forward controlling method: and finally multiple trials in applying policies with verification. In particular, we will discuss the architectural and theoretical aspects of the method in detail, and will show the insufficiency of combining the feedback controlling approach with TOC as a result of our evaluation.

A solution-processed photosensitive passivation layer with a low dielectric constant (PPLD) has been developed for an a-Si thin film transistor. The PPLD has three highly important properties: a low leakage current, low water absorption, and high-transparency. In addition to providing passivation, the PPLD doubles as a planarization layer. The photoactive property of the PPLD is convenient for its adaption to LCD manufacturing process. A photoactive compound contained in the PPLD enables the formation of contact holes and patterns via a photolithography process. Meanwhile, the PPLD requires ITO workability and strong adhesion property on metal and glass substrates. Apart from the above features, an a-Si TFT must perform with extremely high reliability if it is to replace the conventional inorganic passivation layer (SiNx:H). This reliability has been achieved by an a-Si TFT and LCD panel coated with the PPLD. A reliability test was conducted under a high-temperature, high-humidity (HH) condition to examine how resistant the electronic characteristics were to change. The PPLD-coated LCD panel display view showed no defects for a test duration of HH200 hours. This high reliability was presumed to be at least partly attributable to the low water absorption rate of the passivation layer and the suppression of the increase of the TFT off-leakage current by the PPLD, a passivation layer designed to be non-polar as possible. Judging from the results of these experiments, this solution-processed passivation layer seems to be a viable substitute for the conventional inorganic passivation layer. For a larger screen LCD and higher drive frequency, the problem of RC delay has been emerged. The low dielectric constant of the PPLD will suppress the RC delay of the signal and realize both a higher pixel and a higher drive frequency.

A method for spatio-temporal resolution enhancement of video sequences based on super-resolution reconstruction is proposed. A new observation model is defined for accurate resolution enhancement, which enables subpixel motion in intermediate frames to be obtained. A modified optimization formula for obtaining a high-resolution sequence is also adopted.

In this paper, we propose a high accuracy motion estimation method based on the spatio-temporal gradient method using high frame-rate images. In the method, we adopt spatial gradients with low estimated errors by the previous motion vectors. In addition, we evaluate the proposed method and confirm the effectiveness. Finally, we apply the method to super-resolution as an application of the proposed method.

The authors have proposed Multi-Input Multi-Output (MIMO)-Constant Envelope Modulation, (MIMO-CEM), as a power and complexity efficient alternative to MIMO-OFDM, suitable for wireless backhaul networks in which relay nodes are fixed in their positions. One of the major problems hindering the real application of MIMO-CEM is to estimate MIMO channel characteristics. MIMO-CEM is based upon two contrary schemes; one is nonlinear equalization such as maximum likelihood sequence estimator, which needs accurate channel information to replicate the received signal passing through it. The other is a low resolution analog-to-digital converter (ADC), e.g., 1-bit in the default operation that removes the received signal amplitude fluctuation. In this paper, as a solution to the channel estimation problem in MIMO-CEM with low resolution ADC receiver, we propose an adaptive MIMO-CEM channel estimation scheme where iterative adaptive channel estimation is carried out to minimize the error between the received preamble signal and the replicated one. We also prove that Code Division Multiplexing (CDM) preamble transmission is effective in estimating MIMO channel parameters in the presence of large quantization noise. Computer simulation results show that MIMO-CEM with the proposed channel estimator using CDM preambles achieves identical BER performance to that with the ideal channel estimation even in presence of severe quantization noise caused by a low resolution ADC.

Dynamic Framed Slotted ALOHA (DFSA) is one of the most popular protocols to resolve tag collisions in RFID systems. In DFSA, it is widely known that the optimal performance is achieved when the frame size is equal to the number of tags. So, a reader dynamically adjusts the next frame size according to the current number of tags. Thus it is important to estimate the number of tags exactly. In this paper, we propose a novel tag estimation and identification method using litmus (test) slots for DFSA. We compare the performance of the proposed method with those of existing methods by analysis. We conduct simulations and show that our scheme improves the speed of tag identification.

Based on Turbo-Decoding Message-Passing (TDMP) and Normalized Min-Sum (NMS) algorithm, an area efficient LDPC decoder that supports both structured and unstructured LDPC codes is proposed in this paper. We introduce a solution to solve the memory access conflict problem caused by TDMP algorithm. We also arrange the main timing schedule carefully to handle the operations of our solution while avoiding much additional hardware consumption. To reduce the memory bits needed, the extrinsic message storing strategy is also optimized. Besides the extrinsic message recover and the accumulate operation are merged together. To verify our architecture, a LDPC decoder that supports both China Multimedia Mobile Broadcasting (CMMB) and Digital Terrestrial/ Television Multimedia Broadcasting (DTMB) standards is developed using SMIC 0.13 µm standard CMOS process. The core area is 4.75 mm2 and the maximum operating clock frequency is 200 MHz. The estimated power consumption is 48.4 mW at 25 MHz for CMMB and 130.9 mW at 50 MHz for DTMB with 5 iterations and 1.2 V supply.

A hybrid buffer structured optical packet switch and its scheduling algorithm are presented for a limited number of tunable wavelength convertors (TWCs) and internal wavelengths. The hybrid buffer consists of the fiber delay line (FDL) buffer and the electronic buffer. With the proposed algorithm, it could lead realizable packet loss reduction that the LAUC-VF algorithm with only the FDL buffer does not reach. Also, we optimized the number of TWCs and internal wavelengths of the hybrid buffer structured OPS. For the fully shared TWC structure, the optimum number of TWCs and internal wavelengths to guarantee minimum packet loss is evaluated to prevent resource waste under the hybrid buffer.

We give characterizations of stable scaling functions with compact band regions, which have the oversampling property.

To reconstruct low-resolution facial photographs which are in focus and without motion blur, a novel algorithm based on local similarity preserving is proposed. It is based on the theories of local manifold learning. The innovations of the new method include mixing point-based entropy and Euclidian distance to search for the nearest points, adding point-to-patch degradation model to restrict the linear weights and compensating the fusing patch to keep energy coherence. The compensation reduces the algorithm dependence on training sets and keeps the luminance of reconstruction constant. Experiments show that our method can effectively reconstruct 1612 images with the magnification of 88 and the 3224 facial photographs in focus and without motion blur.

We study the problem of reconfiguring one list edge-coloring of a graph into another list edge-coloring by changing only one edge color assignment at a time, while at all times maintaining a list edge-coloring, given a list of allowed colors for each edge. Ito, Kamiski and Demaine gave a sufficient condition so that any list edge-coloring of a tree can be transformed into any other. In this paper, we give a new sufficient condition which improves the known one. Our sufficient condition is best possible in some sense. The proof is constructive, and yields a polynomial-time algorithm that finds a transformation between two given list edge-colorings of a tree with n vertices via O(n2) recoloring steps. We remark that the upper bound O(n2) on the number of recoloring steps is tight, because there is an infinite family of instances on paths that satisfy our sufficient condition and whose reconfiguration requires Ω(n2) recoloring steps.

In this paper, a decentralized concurrent transmission strategy in shared channel in Ad Hoc networks is proposed based on game theory. Firstly, a static concurrent transmissions game is used to determine the candidates for transmitting by channel quality threshold and to maximize the overall throughput with consideration of channel quality variation. To achieve NES (Nash Equilibrium Solution), the selfish behaviors of node to attempt to improve the channel gain unilaterally are evaluated. Therefore, this game allows each node to be distributed and to decide whether to transmit concurrently with others or not depending on NES. Secondly, as there are always some nodes with lower channel gain than NES, which are defined as hunger nodes in this paper, a hunger suppression scheme is proposed by adjusting the price function with interferences reservation and forward relay, to fairly give hunger nodes transmission opportunities. Finally, inspired by stock trading, a dynamic concurrent transmission threshold determination scheme is implemented to make the static game practical. Numerical results show that the proposed scheme is feasible to increase concurrent transmission opportunities for active nodes, and at the same time, the number of hunger nodes is greatly reduced with the least increase of threshold by interferences reservation. Also, the good performance on network goodput of the proposed model can be seen from the results.

The problem of a Gaussian beam that is incident on a plane dielectric interface from a denser dielectric medium to a rarer one and is reflected at the interface has been important research subjects studied by many researchers. In this paper, we have obtained a novel uniform asymptotic solution for reflection and beam shift of the Gaussian beam that is incident on the interface from the denser medium. The uniform asymptotic solution consists of the geometrically reflected beam, the lateral beam if any, and the newly derived transition beam which plays an important role in the transition region near the critical angle of the total reflection. We have confirmed the validity of the uniform asymptotic solution by comparing with the reference solution obtained numerically from the integral representation. We have shown that, in addition to the Goos-Hanchen shift and the angular shift, the Gaussian beam is shifted to either direction by the interference of the geometrically reflected beam and the lateral beam near the critical angle of the total reflection.

This letter studies a nesting discrete particle swarm optimizer for multi-solution problems. The algorithm operates in discrete search space and consists of two stages. The first stage is global search in rough lattice points for constructing local sub-regions each of which includes one target solution. The second stage is local search where the algorithm operates in parallel in fine lattice points of local subspaces and tires to find all the approximate solutions within a criterion. We then propose an application to finding multiple fixed points in nonlinear dynamical systems and investigate the algorithm efficiency.

A monopulse angle measurement method is often utilized to measure a target angle. However, this method cannot measure correct angles for multiple targets which cannot be distinguished by range, Doppler frequency and beamwidth. When the number of targets which cannot be distinguished by these parameters is restricted to two, a method which can measure two targets angles has been proposed. However, an approximation is utilized with this method, so that measured angles have errors even though the signal-to-noise ratio is infinite. Another method which can simultaneously measure azimuths and elevations for only two targets has also been proposed. However, this conventional method requires four receivers, and is therefore difficult to apply when there is a hard ware limitation. In this paper, we propose a method to measure azimuths and elevations of two targets by using two receivers and a time division system. A pairing problem has occurred due to the time division angle measurement with this method, so we also propose an algorithm to solve this pairing problem. We finally verify the proposed method by a numerical simulation and experimentation. The results show that the angles of two targets can be measured by our proposed method by using two receivers.

Concomitantly with the progress of wireless communications, cognitive radio has attracted attention as a solution for depleted frequency bands. Cognitive radio is suitable for wireless sensor networks because it reduces collisions and thereby achieves energy-efficient communication. To make cognitive radio practical, we propose a low-power multi-resolution spectrum sensing (MRSS) architecture that has flexibility in sensing frequency bands. The conventional MRSS scheme consumes much power and can be adapted only slightly to process scaling because it comprises analog circuits. In contrast, the proposed architecture carries out signal processing in a digital domain and can detect occupied frequency bands at multiple resolutions and with low power. Our digital MRSS module can be implemented in 180-nm and 65-nm CMOS processes using Verilog-HDL. We confirmed that the processes respectively dissipate 9.97 mW and 3.45 mW.

This paper presents the design and implementation of a supply and process-insensitive 12-bit Digital Pulse Width Modulator (DPWM) for digital DC-DC converters. The DPWM is realized by a ring oscillator-based segmented tapped delay line and a counter-comparator. The number of delay cells required is reduced by employing a proposed delay cell reuse technique. The ring oscillator of the tapped delay line is made insensitive to supply and process variation by biasing the differential delay cells with a supply-insensitive replica bias circuit. Simulation results show that the variation of the switching frequency of the DPWM at 1.02 MHz is 0.4% for supply voltage variation between 1.5 V and 2.5 V and 0.95% over the temperature range from -40 to 90. Monte-Carlo simulation was also performed to account for the effect of mismatch between the transistors of the ring oscillator. The worst case delay of the delay cells is 0.87% for 5% (3-σ) mismatch. The design was fabricated in CMOS 0.18 µm process and the fabricated DPWM achieved a supply sensitivity of 0.82% and a current consumption of 14 µA.

In this paper, a novel algorithm, Cross Low-dimension Pursuit, based on a new structured sparse matrix, Permuted Block Diagonal (PBD) matrix, is proposed in order to recover sparse signals from incomplete linear measurements. The main idea of the proposed method is using the PBD matrix to convert a high-dimension sparse recovery problem into two (or more) groups of highly low-dimension problems and crossly recover the entries of the original signal from them in an iterative way. By sampling a sufficiently sparse signal with a PBD matrix, the proposed algorithm can recover it efficiently. It has the following advantages over conventional algorithms: (1) low complexity, i.e., the algorithm has linear complexity, which is much lower than that of existing algorithms including greedy algorithms such as Orthogonal Matching Pursuit and (2) high recovery ability, i.e., the proposed algorithm can recover much less sparse signals than even 1-norm minimization algorithms. Moreover, we demonstrate both theoretically and empirically that the proposed algorithm can reliably recover a sparse signal from highly incomplete measurements.