An efficient handover measurement technique is proposed for millimeter-wave (mm-wave) cellular systems with directional antenna beams. As the beam synchronization signal (BSS) carries the cell ID and the beam ID in a hierarchal manner, handover events (interbeam handover and intercell handover) are distinguished at the physical layer. The proposed signal metrics are shown to be effective in detecting the beam boundaries and cell boundaries in mm-wave cellular systems, which allows to distinguish interbeam handover from intercell handover. The proposed handover measurement technique is shown to reduce the processing time significantly using the proposed signal metrics produced by the BSS.

Predicting the receiving sensitivity of an offset Gregorian reflector system antenna requires an accurate prediction of the antenna noise temperature. Calculating the antenna noise temperature is computationally intensive especially for the electrically larger reflector systems. Using the main reflector masking technique, which removes the main reflector from the calculation domain, considerably reduces the computation cost. For an electrically smaller reflector system, diffraction effects affect the accuracy of this technique. Recently an improvement to the technique was proposed that introduces diffraction compensation correction factors. In this paper we introduce new compensation factor and interpolation techniques that improve the accuracy of the approximated antenna noise temperature calculation. The techniques are applied to several offset Gregorian reflector systems similar to those considered for the Square Kilometre Array, with various feeds and the accuracy in terms of receiving sensitivity is evaluated. The techniques can reduce the prediction error of the receiving sensitivity for frequency-invariant feeds to fractions of a percent, while maintaining a significant speed-up over direct calculations.

Identification of urban road targets using radar systems is usually heavily dependent on the aspect angle between the target velocity and line of sight of the radar. To improve the performance of the classification result when the target is in a cross range position relative to the radar, a method based on range micro Doppler signature is proposed in this paper. Joint time-frequency analysis is applied in every range cell to extract the time Doppler signature. The spectrograms from all of the target range cells are combined to form the range micro Doppler signature to allow further identification. Experiments were conducted to investigate the performance of the proposed method, and the results proved the effectiveness of the method presented.

A method is proposed for improving the accuracy of the characteristic basis function method (CBFM) using the multilevel approach. With this technique, CBFs taking into account multiple scattering calculated for each block (IP-CBFs; improved primary CBFs) are applied to CBFM using a multilevel approach. By using IP-CBFs, the interaction between blocks is taken into account, and thus it is possible to reduce the number of CBFs while maintaining accuracy, even if the multilevel approach is used. The radar cross section (RCS) of a cube, a cavity, and a dielectric sphere were analyzed using the proposed CBFs, and as a result it was found that accuracy is improved over the conventional method, despite no major change in the number of CBFs.

We propose and demonstrate a method that can demultiplex an optical OFDM signal with various capacity based on time lens-based optical Fourier transform. The proposed tunable optical OFDM signal demultiplexer is composed of a phase modulator and a tunable chromatic dispersion emulator. The spectrum of the variable capacity OFDM signal is transformed into Nyquist time-division multiplexing pulses with the optical Fourier transform, and the OFDM sub-carrier channels are dumultiplexed in the time-domain. We also propose a simple method for approximating and generating quadratic waveform to drive the phase modulator. After explaining the operating principle of the method and the design of some parameters in detail, we show successful demultiplexing of 4×8 and 4×10 Gbit/s optical OFDM signals with our proposed method as the preliminary investigation results.

LSIs are generally designed through four stages including architectural design, logic design, circuit design, and physical design. In architectural design and logic design, designers describe their target hardware in RTL. However, they generally use different languages for each phase. Typically a general purpose programming language such as C or C++ and a hardware description language such as Verilog HDL or VHDL are used for architectural design and logic design, respectively. That is time-consuming way for designing a hardware and more efficient design environment is required. In this paper, we propose a new hardware modeling and high-speed simulation environment for architectural design and logic design. Our environment realizes writing and verifying hardware by one language. The environment consists of (1) a new hardware description language called ArchHDL, which enables to simulate hardware faster than Verilog HDL simulation, and (2) a source code translation tool from ArchHDL code to Verilog HDL code. ArchHDL is a new language for hardware RTL modeling based on C++. The key features of this language are that (1) designers describe a combinational circuit as a function and (2) the ArchHDL library realizes non-blocking assignment in C++. Using these features, designers are able to write a hardware transparently from abstracted level description to RTL description in Verilog HDL-like style. Source codes in ArchHDL is converted to Verilog HDL codes by the translation tool and they are used to synthesize for FPGAs or ASICs. As the evaluation of our environment, we implemented a practical many-core processor in ArchHDL and measured the simulation speed on an Intel CPU and an Intel Xeon Phi processor. The simulation speed for the Intel CPU by ArchHDL achieves about 4.5 times faster than the simulation speed by Synopsys VCS. We also confirmed that the RTL simulation by ArchHDL is efficiently parallelized on the Intel Xeon Phi processor. We convert the ArchHDL code to a Verilog HDL code and estimated the hardware utilization on an FPGA. To implement a 48-node many-core processor, 71% of entire resources of a Virtex-7 FPGA are consumed.

This paper presents the Received-Signal-Strength-Indicator (RSSI) based living-body radar, which uses only a single RF front-end and a few parasitic antennas. This radar measures the RSSI variation at the single active antenna while varying the terminations of the parasitic antennas. The propagation channel is estimated from just the temporal transition of RSSI; our proposal reconstructs the phase information of the signal. In this paper, we aim to estimate the direction of living-body. Experiments are carried out and it is found that most angular errors are within the limit of the angular width of the living-body.

Considering that different people are different in their linguistic preference and in order to determine the consensus state when using Computing with Words (CWW) for supporting consensus decision making, this paper first proposes an interval composite scale based 2-tuple linguistic model, which realizes the process of translation from word to interval numerical and the process of retranslation from interval numerical to word. Second, this paper proposes an interval composite scale based personalized individual semantics model (ICS-PISM), which can provide different linguistic representation models for different decision-makers. Finally, this paper proposes a consensus decision making model with ICS-PISM, which includes a semantic translation and retranslation phase during decision process and determines the consensus state of the whole decision process. These models proposed take into full consideration that human language contains vague expressions and usually real-world preferences are uncertain, and provide efficient computation models to support consensus decision making.

Block compressed sensing with random permutation (BCS-RP) has been shown to be very effective for image Encryption-then-Compression (ETC) applications. However, in the BCS-RP scheme, the statistical information of the blocks is disclosed, because the encryption is conducted within each small block of the image. To solve this problem, a two-dimension compressed sensing (2DCS) with 2D random permutation (2DRP) strategy for image ETC applications is proposed in this letter, where the 2DRP strategy is used for encrypting the image and the 2DCS scheme is used for compressing the encrypted image. Compared with the BCS-RP scheme, the proposed approach has two benefits. Firstly, it offers better security. Secondly, it obtains a significant gain of peak signal-to-noise ratio (PSNR) of the reconstructed-images.

In this paper, the problem of target detection and tracking utilizing the single frequency network (SFN) is addressed. Specifically, by exploiting the characteristics of the signal in SFN, a novel likelihood model which avoids the measurement origin uncertain problem in the point measurement model is proposed. The particle filter based track-before-detect (PF-TBD) algorithm is adopted for the proposed SFN likelihood to detect and track the possibly existed target. The advantage of using TBD algorithm is that it is suitable for the condition of low SNR, and specially, in SFN, it can avoid the data association between the measurement and the transmitters. The performance of the adopted algorithm is examined via simulations.

An FPGA-based hardware hand sign recognition system was proposed in our previous work. The hand sign recognition system consisted of a preprocessing and a self-organizing map (SOM)-Hebb classifier. The training of the SOM-Hebb classifier was carried out by an off-chip computer using training vectors given by the system. The recognition performance was reportedly improved by adding perturbation to the training data. The perturbation was added manually during the process of image capture. This paper proposes a new off-chip training method with automatic performance improvement. To improve the system's recognition performance, the off-chip training system adds artificially generated perturbation to the training feature vectors. Advantage of the proposed method compared to additive scale perturbation to image is its low computational cost because the number of feature vector elements is much less than that of pixels contained in image. The feasibility of the proposed off-chip training was tested in simulations and experiments using American sign language (ASL). Simulation results showed that the proposed perturbation computation alters the feature vector so that it is same as the one obtained by a scaled image. Experimental results revealed that the proposed off-chip training improved the recognition accuracy from 78.9% to 94.3%.

SUMPLE, one of important signal combining approaches, its combining loss increases when a sensor in an array fails. A novel failure detection circuit for SUMPLE is proposed by using variability index. This circuit can effectively judge whether a sensor fails or not. Simulation results validate its effectiveness with respect to the existing algorithms.

In this paper, we propose a novel phrase-based model for Korean morphological analysis by considering a phrase as the basic processing unit, which generalizes all the other existing processing units. The impetus for using phrases this way is largely motivated by the success of phrase-based statistical machine translation (SMT), which convincingly shows that the larger the processing unit, the better the performance. Experimental results using the SEJONG dataset show that the proposed phrase-based models outperform the morpheme-based models used as baselines. In particular, when combined with the conditional random field (CRF) model, our model leads to statistically significant improvements over the state-of-the-art CRF method.

Multiple Subcarrier Multiple Access (MSMA) enables concurrent sensor data streamings from multiple wireless and batteryless sensors using the principle of subcarrier backscatter used extensively in passive RFID. Since the interference cancellation performance of MSMA depends on the Signal to Interference plus Noise Ratio of each subcarrier, the choice of channel allocation scheme is essential. Since the channel allocation is a combinatorial problem, obtaining the true optimal allocation requires a vast amount of examinations which is impracticable in a system where we have tens of sensor RF tags. It is particularly true when we have variable distance and variable bandwidth sensor RF tags. This paper proposes a channel allocation scheme in the variable distance and variable bandwidth MSMA system based on a newly introduced performance index, total contamination power, to prioritize indecision cases. The performance of the proposal is evaluated with existing methods in terms of average communication capacity and system fairness using MATLAB Monte Carlo simulation to reveal its advantage. The accuracy of the simulation is also verified with the result obtained from the brute force method.

Concurrent transmission (CT) is a revolutionary multi-hop protocol that significantly improves the MAC- and network-layer efficiency by allowing synchronized packet collisions. Although its superiority has been empirically verified, there is still a lack of studies on how the receiver survives such packet collisions, particularly in the presence of the carrier frequency offsets (CFO) between the transmitters. This work rectifies this omission by providing a comprehensive evaluation of the physical-layer receiver performance under CT, and a theoretical analysis on the fading duration of the beating effect resulting from the CFO. The main findings from our evaluations are the following points. (1) Beating significantly affects the receiver performance, and an error correcting mechanism is needed to combat the beating. (2) In IEEE 802.15.4 systems, the direct sequence spread spectrum (DSSS) plays such a role in combatting the beating. (3) However, due to the limited length of DSSS, the receiver still suffers from the beating if the fading duration is too long. (4) On the other hand, the basic M-ary FSK mode of IEEE 802.15.4g is vulnerable to CT due to the lack of error correcting mechanism. In view of the importance of the fading duration, we further theoretically derive the closed form of the average fading duration (AFD) of the beating under CT in terms of the transmitter number and the standard deviation of the CFO. Moreover, we prove that the receiver performance can be improved by having higher CFO deviations between the transmitters due to the shorter AFD. Finally, we estimate the AFD in the real system by actually measuring the CFO of a large number of sensor nodes.

This paper studies a simultaneous wireless information and power transfer (SWIPT) system in which the transmitter not only sends data and energy to many types of wireless users, such as multiple information decoding users, multiple hybrid power-splitting users (i.e., users with a power-splitting structure to receive both information and energy), and multiple energy harvesting users, but also prevents information from being intercepted by a passive eavesdropper. The transmitter is equipped with multiple antennas, whereas all users and the eavesdropper are assumed to be equipped with a single antenna. Since the transmitter does not have any channel state information (CSI) about the eavesdropper, artificial noise (AN) power is maximized to mask information as well as to interfere with the eavesdropper as much as possible. The non-convex optimization problem is formulated to minimize the transmit power satisfying all signal-to-interference-plus-noise (SINR) and harvested energy requirements for all users so that the remaining power for generating AN is maximized. With perfect CSI, a semidefinite relaxation (SDR) technique is applied, and the optimal solution is proven to be tight. With imperfect CSI, SDR and a Gaussian randomization algorithm are proposed to find the suboptimal solution. Finally, numerical performance with respect to the maximum SINR at the eavesdropper is determined by a Monte-Carlo simulation to compare the proposed AN scenario with a no-AN scenario, as well as to compare perfect CSI with imperfect CSI.

In this paper, we present a novel regression-based robust locality preserving projections (RRLPP) method to effectively deal with the issue of noise and occlusion in facial expression recognition. Similar to robust principal component analysis (RPCA) and robust regression (RR) approach, the basic idea of the presented RRLPP approach is also to lead in the low-rank term and the sparse term of facial expression image sample matrix to simultaneously overcome the shortcoming of the locality preserving projections (LPP) method and enhance the robustness of facial expression recognition. However, RRLPP is a nonlinear robust subspace method which can effectively describe the local structure of facial expression images. The test results on the Multi-PIE facial expression database indicate that the RRLPP method can effectively eliminate the noise and the occlusion problem of facial expression images, and it also can achieve better or comparative facial expression recognition rate compared to the non-robust and robust subspace methods meantime.

To design antennas for ingestible capsule endoscope systems, the transmission factors of dipole and loop antennas placed in the torso-shaped phantom filled with deionized water or human body equivalent liquid (HBEL) are investigated by numerical and experimental study. The S-parameter method is used to evaluate transmission characteristics through a torso-shaped phantom in a broadband frequency range. Good agreement of S-parameters between measured results and numerical analysis is observed and the transmission factors for both cases are obtained. Comparison of the transmission factors between HBEL and deionized water is presented to explain the relation between conductivity and the transmission characteristics. Two types of antennas, dipole antenna and loop antenna are compared. In the case of a dipole antenna placed in deionized water, it is observed that the transmission factor decreases as conductivity increases. On the other hand, there is a local maximum in the transmission factor at 675 MHz in the case of HBEL. This phenomenon is not observed in the case of a loop antenna. The transmission factor of capsule dipole antenna and capsule loop antenna are compared and the guideline in designing capsule antennas by using transmission factor is also proposed.

This paper proposes a genetic algorithm (GA) based design method for arbitrarily-shaped resonant elements that offer enhanced reflectarray antenna performance. All elements have the specified phase property over the range of 360°, and also have dual-polarization and low cross-polarization properties for better reflectarray performance. In addition, the proposal is suitable for linear-to-circular polarization conversion elements. Thus, polarizer reflectarray elements are also presented in this paper. The proposed elements are validated using both numerical simulations and experiments.

An area-efficient FPGA-based annealing processor that is based on Ising model is proposed. The proposed processor eliminates random number generators (RNGs) and temperature schedulers, which are the key components in the conventional annealing processors and occupying a large portion of the design. Instead, a shift-register-based spin flipping scheme successfully helps the Ising model from stucking in the local optimum solutions. An FPGA implementation and software-based evaluation on max-cut problems of 2D-grid torus structure demonstrate that our annealing processor solves the problems 10-104 times faster than conventional optimization algorithms to obtain the solution of equal accuracy.