Coordinate interleaved orthogonal design (CIOD) using four transmit antennas provides full diversity, full rate (FDFR) properties with low decoding complexity. However, the constellation expansion due to the coordinate interleaving of the rotated constellation results in peak to average power ratio (PAPR) increase. In this paper, we propose two signal constellation design methods which have low PAPR. In the first method we propose a signal constellation by properly selecting the signal points among the expanded square QAM constellation points, based on the co-prime interleaving of the first coordinate signal. We design a regular interleaving pattern so that the coordinate distance product (CPD) after the interleaving becomes large to get the additional coding gain. In the other method we propose a novel constellation with low PAPR based on the clipping of the rotated square QAM constellation. Our proposed signal constellations show much lower PAPR than the ordinary rotated QAM constellations for CIOD.

The Virtual Machine Consolidation (VMC) algorithm is the core strategy of virtualization resource management software. In general, VMC efficiency dictates cloud datacenter efficiency to a great extent. However, all the current Virtual Machine (VM) consolidation strategies, including the Iterative Correlation Match Algorithm (ICMA), are not suitable for the dynamic VM consolidation of the level of physical servers in actual datacenter environments. In this paper, we propose two VM consolidation and placement strategies which are called standard Segmentation Iteration Correlation Combination (standard SICC) and Multi-level Segmentation Iteration Correlation Combination (multi-level SICC). The standard SICC is suitable for the single-size VM consolidation environment and is the cornerstone of multi-level SICC which is suitable for the multi-size VM consolidation environment. Numerical simulation results indicate that the numbers of remaining Consolidated VM (CVM), which are generated by standard SICC, are 20% less than the corresponding parameters of ICMA in the single-level VM environment with the given initial condition. The numbers of remaining CVMs of multi-level SICC are 14% less than the corresponding parameters of ICMA in the multi-level VM environment. Furthermore, the used physical servers of multi-level SICC are also 5% less than the used servers of ICMA under the given initial condition.

As dual-polarized multiple-input multiple-output (MIMO) technique has little inter-antenna interference, it provides high data rate and reliability to a user equipment (UE) with the low system complexity. In the joint transmission (JT) technique of the coordinated multi-point (CoMP) transmission system, multiple transmission points (TPs) transmit the same data to the UE so that the UE can get the diversity gain and the high reliability, especially at the cell-edge. However, the system performance of the dual-polarized MIMO in the JT technique of CoMP system is very sensitive on the dual-polarized channel state when the channel is asymmetric. In this letter, an improved dual-polarized MIMO scheme for JT of the downlink CoMP transmission system is proposed. This scheme adaptively applies the transmission power to each dual-polarized MIMO antenna and the modulation order of the transmission data according to the channel state information (CSI). System-level simulation results show that the proposed scheme provides better bit-error-rate (BER) performance in the asymmetric dual-polarized channel state than the conventional scheme.

We have investigated PtHf silicide formation utilizing a developed PtHf-alloy target to realize low contact resistivity for the first time. A 20 nm-thick PtHf-alloy thin film was deposited on the n-Si(100) by RF magnetron sputtering at room temperature. Then, silicidation was carried out by rapid thermal annealing (RTA) system at 450-600°C/5 min in N2/4.9%H2 ambient. The PtHf-alloy silcide, PtHfSi, layers were successfully formed, and the Schottky barrier height (SBH) for electron of 0.45 eV was obtained by 450°C silicidation. Furthermore, low contact resistivity was achieved for fabricated PtHSi such as 8.4x10-8 Ωcm2 evaluated by cross-bridge Kelvin resistor (CBKR) method.

In this study, we investigated Si(100), Si(110) and Si(111) surface flattening process utilizing sacrificial oxidation method, and its effect on Metal-Insulator-Semiconductor (MIS) diode characteristics. By the etching of the 100 nm-thick sacrificial oxide formed by thermal oxidation at 1100°C, the surface roughness of Si(100), Si(110) and Si(111) substrates were reduced. The obtained Root-Mean-Square (RMS) roughness of Si(100) was reduced from 0.22 nm (as-cleaned) to 0.07 nm (after etching), while it was reduced from 0.23 nm to 0.12 nm in the case of Si(110), and from 0.23 nm to 0.11 nm in the case of Si(111), respectively. Furthermore, it was found that time-dependent dielectric breakdown (TDDB) characteristics of MIS diodes for p-Si(100), p-Si(110) and p-Si(111) were improved with the reduction of Si surface RMS roughness.

The cycling wheelchair “Profhand” was developed in Japan as locomotion and lower limb rehabilitation device for hemiplegic subjects and elderly persons. Functional electrical stimulation (FES) control of paralyzed lower limbs enables application of the Profhand to paraplegic subjects as a rehabilitation device. In this paper, simplified muscle stimulation control for FES cycling with Profhand was examined for practical application, because cycling speed was low and not stable in our preliminary study and there was a difficulty in setting stimulation electrodes for the gluteus maximus. First, a guideline of target cycling speed to be achieved by FES cycling was determined from voluntary cycling with healthy subjects in order to evaluate FES cycling control. The cycling speed of 0.6m/s was determined as acceptable value and 1.0m/s was as ideal one. Then, stimulation to the gluteus maximus and that to the dorsiflexor muscles in addition to the quadriceps femoris were examined for simple FES cycling control for Profhand with healthy subjects. Stimulation timing was adjusted automatically during cycling based on muscle response time to electrical stimulation and cycling speed, which was shown to be effective for FES cycling control. Simple FES cycling control with Profhand removing stimulation to the gluteus maximus was found to be feasible. Stimulation to the dorsiflexor muscles with the quadriceps femoris was suggested to be effective for practical, simple FES cycling with Profhand in case of removing the gluteus maximus stimulation.

In this letter, we propose a novel texture descriptor that takes advantage of an anisotropic neighborhood. A brand new encoding scheme called Reflection and Rotation Invariant Uniform Patterns (rriu2) is proposed to explore local structures of textures. The proposed descriptor is called Oriented Local Binary Patterns (OLBP). OLBP may be incorporated into other varieties of Local Binary Patterns (LBP) to obtain more powerful texture descriptors. Experimental results on CUReT and Outex databases show that OLBP not only significantly outperforms LBP, but also demonstrates great robustness to rotation and illuminant changes.

Codebooks with good parameters are preferred in many practical applications, such as direct spread CDMA communications and compressed sensing. In this letter, an upper bound on the set size of a codebook is introduced by modifying the Levenstein bound on the maximum amplitudes of such a codebook. Based on an estimate of a class of character sums over a finite field by Katz, a family of codebooks nearly meeting the modified bound is proposed.

Cognitive radio sensor networks (CRSNs) with their dynamic spectrum access capability appear to be a promising solution to address the increasing challenge of spectrum crowding faced by the traditional WSN. In this paper, through maximizing the utility index of the CRSN, a node density-adaptive spectrum access strategy for sensor nodes is proposed that takes account of the node density in a certain event-driven region. For this purpose, considering the burst real-time data traffic, we analyze the energy efficiency (EE) and the packet failure rate (PFR) combining network disconnected rate (NDR) and packet loss rate (PLR) during the channel switching interval (CSI) for both underlay and interweave spectrum access schemes. Numerical results confirm the validity of our theoretical analyses and indicate that the adaptive node density threshold (ANDT) exists for underlay and interweave spectrum access scheme switching.

In recent years, multiple-input multiple-output (MIMO) channel models for crowded areas, such as indoor offices, shops, and outdoor hotspot environments, have become a topic of significant interest. In such crowded environments, propagation paths are frequently shadowed by moving objects, such as pedestrians or vehicles. These shadowing effects can cause time variations in the delay and angle-of-arrival (AoA) characteristics of a channel. In this paper, we propose a method for modeling the shadowing effects of pedestrians in a cluster-based channel model. The proposed method uses cluster power variations to model the time-varying channel properties. We also propose a novel method for estimating the cluster power variation properties from measured data. In order to validate our proposed method, channel sounding in the 3GHz band is conducted in a cafeteria during lunchtime. The results for the K parameter, delay spreads, and AoA azimuth spreads are compared for the measured data and the channel data generated using the proposed method. The results indicate that the time-varying delay-AoA characteristics can be effectively modeled using our proposed method.

Mixed-signal integrated circuit design and simulation highly rely on behavioral models of circuit blocks. Such models are used for the validation of design specification, optimization of system topology, and behavioral synthesis using a description language, etc. However, automatic behavioral model generation is still in its early stages; in most scenarios designers are responsible for creating behavioral models manually, which is time-consuming and error prone. In this paper an automatic behavioral model generation method for switched-capacitor (SC) integrator is proposed. This technique is based on symbolic circuit modeling with approximation, by which parametric behavioral integrator model can be generated. Such parametric models can be used in circuit design subject to severe process variational. It is demonstrated that the automatically generated integrator models can accurately capture process variation effects on arbitrarily selected circuit elements; furthermore, they can be applied to behavioral simulation of SC Sigma-Delta modulators (SDMs) with acceptable accuracy and speedup. The generated models are compared to a recently proposed manually generated behavioral integrator model in several simulation settings.

To efficiently monitor the link performance in an OpenFlow network with a single measurement box (referred to a “beacon”), this paper presents a measurement scheme that calculates a set of measurement paths from the beacon to cover all links in the network based on the controllable feature of individual measurement paths in the OpenFlow network and comprehensively estimates the performance of all the physical links from round-trip active measurements. The scheme has a novel feature that minimize the maximum number of exclusive flow-entries for active measurements on OpenFlow switches by utilizing common packet header values in the probing packets to aggregate multiple entries into a single entry to save the resources in OpenFlow switches and controller. We demonstrate the effectiveness and feasibility of our solution through simulations and emulation scenarios.

Although SDN provides desirable characteristics such as the manageability, flexibility and extensibility of the networks, it has a considerable disadvantage in its reliability due to its centralized architecture. To protect SDN-enabled networks under large-scale, unexpected link failures, we propose ResilientFlow that deploys distributed modules called Control Channel Maintenance Module (CCMM) for every switch and controllers. The CCMMs makes switches able to maintain their own control channels, which are core and fundamental part of SDN. In this paper, we design, implement, and evaluate the ResilientFlow.

This paper proposes 1-bit feedforward distortion compensation for digital radio frequency conversion (DRFC) with 1-bit bandpass delta-sigma modulation (BP-DSM). The 1-bit BP-DSM allows direct RF signal transmission from a digitally modulated signal. However, it has been previously reported that 1-bit digital pulse trains with non-ideal rectangle waveform cause spectrum regrowth. The proposed architecture adds a feedforward path with another 1-bit BP-DSM and so can cancel out the distortion components at any target carrier frequency. Both the main signal and the distortion compensation signal are 1-bit digital pulse trains and so no additional analog RF circuit is required for distortion compensation. Simulation results show that the proposed method holds the adjacent channel leakage ratio to 60dB for LTE signal transmission. A prototype of the proposed 1-bit DRFC with an additional 1-bit BP-DSM in the feedforward path shows an ACLR of 50dB, 4dB higher than that of the conventional 1-bit DRFC.

This paper considers the beamforming design for energy efficiency transmission over multiple-input and single-output (MISO) channels. The energy efficiency maximization problem is non-convex due to the fractional form in its objective function. In this paper, we propose an efficient method to transform the objective function in fractional form into the difference of two concave functions (DC) form, which can be solved by the successive convex approximation (SCA) algorithm. Then we apply the proposed transformation and pricing mechanism to develop a distributed beamforming optimization for multiuser MISO interference channels, where each user solves its optimization problem independently and only limited information exchange is needed. Numerical results show the effectiveness of our proposed algorithm.

This paper introduces a simple but effective way to boost the performance of scene classification through a novel approach to the LLC coding process. In our proposed method, a local descriptor is encoded not only with k-nearest visual words but also with k-farthest visual words to produce more discriminative code. Since the proposed method is a simple modification of the image classification model, it can be easily integrated into various existing BoF models proposed in various areas, such as coding, pooling, to boost their scene classification performance. The results of experiments conducted with three scene datasets: 15-Scenes, MIT-Indoor67, and Sun367 show that adding k-farthest visual words better enhances scene classification performance than increasing the number of k-nearest visual words.

This paper investigates current-gain and high-frequency characteristics of double heterojunction bipolar transistors (DHBTs) with a uniform GaAsSb, compositionally graded GaAsSb, uniform InGaAsSb, or compositionally graded InGaAsSb base. DHBTs with a compositionally graded InGaAsSb base exhibit a high current gain of ∼75 and fT=504GHz. In order to boost fmax of DHBTs with a compositionally graded InGaAsSb base, a highly doped GaAsSb base contact layer is inserted. The fabricated DHBTs exhibit fT/fmax=513/637GHz and a breakdown voltage of 5.2V.

In this work, the bias polarity dependent resistive switching behaviors in Cu/Si3N4/p+ Si RRAM memory cell have been closely studied. Different switching characteristics in both unipolar and bipolar modes after the positive forming are investigated. The bipolar switching did not need a forming process and showed better characteristics including endurance cycling, uniformity of switching parameters, and on/off resistance ratio. Also, the resistive switching characteristics by both positive and negative forming switching are compared. It has been confirmed that both unipolar and bipolar modes after the negative forming exhibits inferior resistive switching performances due to high forming voltage and current.

Layout strategies including source edge to substrate space (SESS) and inserted substrate-pick stripes of gate-grounded NMOS(ggNMOS) are optimized in this work for on-chip electrostatic discharge (ESD) protection. In order to fully investigate influences of substrate resistors on triggering and conduction behaviors of ggNMOS, various devices are designed and fabricated in a 65-nm CMOS process. Direct current (DC), transmission-line-pulsing (TLP), human body model (HBM) and very-fast TLP (VF-TLP) tests are executed to fully characterize performance of fabricated ggNMOS. Test results reveal that an enlarged SESS parameter results in an earlier triggering behavior of ggNMOS, which presents a layout option for subtle adjustable triggering behaviors. Besides, inserted substrate-pick stripes are proved to have a bell-shape influence on the ESD robustness of ggNMOS and this bell-shape influence is valid in TLP, HBM and VF-TLP tests. Moreover, the most ESD-robust ggNMOS optimized under different inserted substrate-pick stripes always achieves a higher HBM level over the traditional ggNMOS at each concerned total device-width. Physical mechanisms of test results will be deeply discussed in this work.

Flow classification is of great significance for network management. Machine-learning-based flow classification is widely used nowadays, but features which depict the non-Gaussian characteristics of network flows are still absent. In this paper, we propose the Windowed Higher-order Statistical Analysis (WHOSA) for machine-learning-based flow classification. In our methodology, a network flow is modeled as three different time series: the flow rate sequence, the packet length sequence and the inter-arrival time sequence. For each sequence, both the higher-order moments and the largest singular values of the Bispectrum are computed as features. Some lower-order statistics are also computed from the distribution to build up the feature set for contrast, and C4.5 decision tree is chosen as the classifier. The results of the experiment reveals the capability of WHOSA in flow classification. Besides, when the classifier gets fully learned, the WHOSA feature set exhibit stronger discriminative power than the lower-order statistical feature set does.