This paper proposes a method for reducing the peak-to-average power ratio (PAPR) at the output signal of a digital predistortion linearizer (DPDL) that compensates for frequency dependent intermodulation distortion (IMD) components. The proposed method controls the amplitude and phase values of the frequency components corresponding to the transmission bandwidth of the output signal. A DPDL employing the proposed method simultaneously provides IMD component cancellation of out-of-band components and PAPR reduction at the output signal. This paper identifies the amplitude and phase conditions to minimize the PAPR. Experimental results based on a 2-GHz band 1-W class power amplifier show that the proposed method improves the drain efficiency of the power amplifier when degradation is allowed in the error vector magnitude. To the best knowledge of the authors, this is the first PAPR reduction method for DPDL that reduces the PAPR while simultaneously compensating for IMD components.

Event-triggered control is a method that the control input is updated only when a certain triggering condition is satisfied. In networked control systems, quantization errors via A/D conversion should be considered. In this paper, a new method for quantized event-triggered control with switching triggering conditions is proposed. For a discrete-time linear system, we consider the problem of finding a state-feedback controller such that the closed-loop system is uniformly ultimately bounded in a certain ellipsoid. This problem is reduced to an LMI (Linear Matrix Inequality) optimization problem. The volume of the ellipsoid may be adjusted. The effectiveness of the proposed method is presented by a numerical example.

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.

This paper presents an overview of the advance of the China millimeter-wave multiple gigabit (CMMG) wireless local area network (WLAN) system which operates in the 45 GHz frequency band. The CMMG WLAN system adopts the multiple antennas technologies to support data rate up to 15Gbps. During the progress of CMMG WLAN standardization, some new key technologies were introduced to adapt the millimeter-wave characteristic, including the usage of the zero correlation zone (ZCZ) sequence, a novel lower density parity check code (LDPC)-based packet encoding, and multiple input multiple output (MIMO) single carrier transmission. Extensive numerical results and system prototype test are also given to validate the performance of the technologies adopted by CMMG WLAN system.

This paper presents a 44 Gbit/s Transimpedance Amplifier (TIA) with wide-dynamic range and high-linearity for optical receiver fabricated in 130 nm BiCMOS technology. The TIA has the features of 67dBΩ overall transimpedance gain, a bandwidth of 28GHz, 10pA/√Hz of Input Referred Noise Current Power Spectral Density (IRNCPSD), and a power consumption of 95mW from a 2.5V supply. The Total Harmonic Distortion (THD) is less than 5% for a differential input current up to 2.63mApp, when the static input current is 0.1mA.

Block-state realization of state-space digital filters offers reduced implementation complexity relative to canonical state-space filters while filter's internal structure remains accessible. In this paper, we present a quantitative analysis on l2 coefficient sensitivity of block-state digital filters. Based on this, we develop two techniques for minimizing average l2-sensitivity subject to l2-scaling constraints. One of the techniques is based on a Lagrange function and some matrix-theoretic techniques. The other solution method converts the problem at hand into an unconstrained optimization problem which is solved by using an efficient quasi-Newton algorithm where the key gradient evaluation is done in closed-form formulas for fast and accurate execution of quasi-Newton iterations. A case study is presented to demonstrate the validity and effectiveness of the proposed techniques.

We propose a framework to detect lug position and orientation in robotics that is insensitive to the lug orientation, incorporating a proposed optimization based on the artificial bee colony genetic algorithm. Experimental results show that the proposed optimization method outperformed traditional artificial bee colony and other meta-heuristics in the considered cases and was up to 3 times faster than the traditional approach. The proposed detection framework provided excellent performance to detect lug objects for all test cases.

A method for accurate estimation of personalized video preference using multiple users' viewing behavior is presented in this paper. The proposed method uses three kinds of features: a video, user's viewing behavior and evaluation scores for the video given by a target user. First, the proposed method applies Supervised Multiview Spectral Embedding (SMSE) to obtain lower-dimensional video features suitable for the following correlation analysis. Next, supervised Multi-View Canonical Correlation Analysis (sMVCCA) is applied to integrate the three kinds of features. Then we can get optimal projections to obtain new visual features, “canonical video features” reflecting the target user's individual preference for a video based on sMVCCA. Furthermore, in our method, we use not only the target user's viewing behavior but also other users' viewing behavior for obtaining the optimal canonical video features of the target user. This unique approach is the biggest contribution of this paper. Finally, by integrating these canonical video features, Support Vector Ordinal Regression with Implicit Constraints (SVORIM) is trained in our method. Consequently, the target user's preference for a video can be estimated by using the trained SVORIM. Experimental results show the effectiveness of our method.

In this paper, we consider to develop a recovery algorithm of a sparse signal for a compressed sensing (CS) framework over finite fields. A basic framework of CS for discrete signals rather than continuous signals is established from the linear measurement step to the reconstruction. With predetermined priori distribution of a sparse signal, we reconstruct it by using a message passing algorithm, and evaluate the performance obtained from simulation. We compare our simulation results with the theoretic bounds obtained from probability analysis.

In social and information network analysis, ranking has been considered to be one of the most fundamental and important tasks where the goal is to rank the nodes of a given graph according to their importance. For example, the PageRank and the HITS algorithms are well-known ranking methods. While these traditional ranking methods focus only on the structure of the entire network, we propose to incorporate a local view into node ranking by exploiting the clustering structure of real-world networks. We develop localized ranking mechanisms by partitioning the graphs into a set of tightly-knit groups and extracting each of the groups where the localized ranking is computed. Experimental results show that our localized ranking methods rank the nodes quite differently from the traditional global ranking methods, which indicates that our methods provide new insights and meaningful viewpoints for network analysis.

This paper describes the design and experiment results of a 25Gbps vertical-cavity surface emitting laser (VCSEL) driver circuit for a multi channel optical transmitter. To compensate for the non-linearity of the VCSEL and achieve high speed data rate communication, an asymmetric pre-emphasis technique is proposed for the VCSEL driver. An asymmetric pre-emphasis signal can be created by adjusting the duty ratio of the emphasis signal. The VCSEL driver adopts a double cascode connection that can apply a drive current from a high voltage DC bias and feed-forward compensation that can enhance the band-width for common-cathode VCSEL. For the design of the optical module structure, a two-tier low temperature co-fired ceramics (LTCC) package is adopted to minimize the wire bonding between the signal pad on the LTCC and the anode pad on the VCSEL. This structure and circuit reduces the simulated deterministic jitter from 12.7 to 4.1ps. A test chip was fabricated with the 65-nm standard CMOS process and demonstrated to work as an optical transmitter. An experimental evaluation showed that this VCSEL driver with asymmetric pre-emphasis reduced the total deterministic jitter up to 8.6ps and improved the vertical eye opening ratio by 3% compared with symmetric pre-emphasis at 25Gbps with a PRBS=29-1 test signal. The power consumption of the VCSEL driver was 3.0mW/Gbps/ch at 25Gbps. An optical transmitter including the VCSEL driver achieved 25-Gbps, 4-ch fully optical links.

A ripple-free dual-rate control system is designed for a single-input single-output dual-rate system, in which the sampling interval of a plant output is longer than the holding interval of a control input. The dual-rate system is converged to a multi-input single-output single-rate system using the lifting technique, and a control system is designed based on an error system using the steady-state variable. Because the proposed control law is designed so that the control input is constant in the steady state, the intersample output as well as the sampled output converges to the set-point without both steady-state error and intersample ripples when there is neither modeling nor disturbance. Furthermore, in the proposed method, a two-degree-of-freedom integral compensation is designed, and hence, the transient response is not deteriorated by the integral action because the integral action is canceled when there is neither modeling nor disturbance. Moreover, in the presence of the modeling error or disturbance, the integral compensation is revealed, and hence, the steady-state error is eliminated on both the intersample and sampled response.

The method for estimating propagation loss that classifies receiving points into multiple groups by focusing on the number of reflections and diffractions, and applies a separate statistical model to each group was extended from only 2.4 GHz band to both 2.4 GHz and 5 GHz band. The extended statistical model was created from received power measurements. First, an appropriate grouping method was investigated based on the fitting error of statistical model. Non-line-of-sight (NLOS) receiving points were grouped in order of points that a wave reflected one time reaches, points that a wave reflected two times reaches, and points that a wave diffracted one time reaches. Next, the effectiveness of the proposed method was verified by comparison with conventional statistical models (one-slope, dual-slope, multi-wall, partitioned) on three office floors that differ from the environment used to create the statistical model. The average NLOS estimation error for the three evaluation environments was 4.9 dB, demonstrating that the proposed method has accuracy equal to or better than that of conventional methods.

Power amplifiers (PAs) are key components of mobile base stations. In the last decade, the power efficiency of PAs for 3G/4G mobile base stations has risen to over 50% as a result of employing efficiency enhancement techniques, such as Doherty, envelope tracking, and outphasing, in combination with GaN devices and digital predistortion. This trend has significantly contributed to reducing the power consumption of mobile base stations. Furthermore, digital transmitters using switch-mode PAs have the potential of breaking through the 70% efficiency level. Achieving this goal will require advances not only in circuitry but also in device technology. For active antenna systems of 5G mobile systems, ease of integration, as well as high efficiency, becomes important for PAs, and thus, Si-based devices will play a major role.

Compressive spectral imaging (CSI) systems capture the 3D spatiospectral data by measuring the 2D compressed focal plane array (FPA) coded projection with the help of reconstruction algorithms exploiting the sparsity of signals. However, the contradiction between the multi-dimension of the scenes and the limited dimension of the sensors has limited improvement of recovery performance. In order to solve the problem, a novel CSI system based on a coded aperture snapshot spectral imager, RGB-CASSI, is proposed, which has two branches, one for CASSI, another for RGB images. In addition, considering that conventional reconstruction algorithms lead to oversmoothing, a RGB-guided low-rank (RGBLR) method for compressive hyperspectral image reconstruction based on compressed sensing and coded aperture spectral imaging system is presented, in which the available additional RGB information is used to guide the reconstruction and a low-rank regularization for compressive sensing and a non-convex surrogate of the rank is also used instead of nuclear norm for seeking a preferable solution. Experiments show that the proposed algorithm performs better in both PSNR and subjective effects compared with other state-of-art methods.

In this letter, we study a scenario based on decoupled RF energy harvesting networks (DRF-EHNs) that separate energy sources from information sources to overcome the doubly near-far problem and improve harvesting efficiency. We propose an algorithm to maximize energy efficiency (EE) while satisfying constraints on the maximum transmit power of the hybrid access point (H-AP) and power beacon (PB), while further satisfying constraints on the minimum quality of service and minimum amount of harvested power in multi-user Rayleigh fading channel. Using nonlinear fractional programming and Lagrangian dual decomposition, we optimize EE with four optimization arguments: the transmit power from the H-AP and PB, time-splitting ratio, and power-splitting ratio. Numerical results show that the proposed algorithm is more energy-efficient compared to baseline schemes.

This research addresses improvements in the efficiency of spectrum utilization by defending against jamming attacks and corrupting the communications of the adversary network by executing its own jamming strategy. The proposed scheme, based on game theory, selects the best operational strategy (i.e., communications and jamming strategies) to maximize the successful communications and jamming rates of the network. Moreover, an estimation algorithm is investigated to predict the behavior of the adversary network in order to improve the efficiency of the proposed game theory-based scheme.

In this paper, we propose an indoor localization method that uses only the Received Signal Strength Indicator (RSSI) of signals transmitted from wireless beacons. The beacons use three-element array antennas, and the position of the receiving terminal is estimated by using multiple DOD information. Each beacon transmits four beacon signals with different directivities by feeding signals to the three-element array antennas via 180-degree and 90-degree hybrids. The correlation matrix of the propagation channels is estimated from just the strength of the signals, and the DOD is estimated from the calculated correlation matrix. For determining the location of the receiving terminal, the existence probability function is introduced. Experiments show that the proposed method attains lower position estimation error than the conventional method.

Three-dimensional (3-D) scattering center models use a finite number of point scatterers to efficiently represent complex radar target signature. Using the CLEAN algorithm, 3-D scattering center model is extracted from the inverse synthetic aperture radar (ISAR) image, which is generated based on the shooting and bouncing ray (SBR) technique. The conventional CLEAN extracts the strongest peak iteratively based on the assumption that the scattering centers are isolated. In a realistic target, however, both interference from the closely spaced points and additive noise distort the extraction process. This paper proposes a matched filter-based CLEAN algorithm to improve accuracy efficiently. Using the matched filtering of which impulse response is the known point spread function (PSF), a point most correlated with the PSF is extracted. Thus, the proposed method optimally enhances the accuracy in the presence of massive distortions. Numerical simulations using canonical and realistic targets demonstrate that the extraction accuracy is improved without loss of time-efficiency compared with the existing CLEAN algorithms.