A novel real-valued ESPRIT (RV-ESPRIT) algorithm is proposed to estimate the direction of arrival (DOA) and direction of departure (DOD) for noncircular signals in bistatic MIMO radar. By exploiting the property of signal noncircularity and Euler's formula, a new virtual array data of bistatic MIMO radar, which is twice that of the MIMO virtual array data, is established with real-valued sine and cosine data. Then the receiving/transmitting selective matrices are constructed to obtain the receiving/transmitting rotationally invariant factors. Compared to the existing angle estimation methods, the proposed algorithm has lower computational load. Simulation results confirm the effectiveness of the RV-ESPRIT.

A new class of visible light communication (VLC) systems, namely image sensor (IS) based VLC systems, has emerged. An IS consists of a two-dimensional (2D) array of photodetectors (PDs), and then VLC systems with an IS receiver are capable of exploiting the spatial dimensions invoked for transmitting information. This paper aims for providing a brief survey of topics related to the IS-based VLC, and then provides a matrix representation of how to map a series of one dimensional (1D) symbols onto a set of 2D symbols for efficiently exploit the associate grade of freedom offered by 2D VLC systems. As an example, the matrix representation is applied to the symbol mapping of layered space-time coding (L-STC), which is presented to enlarge the coverage of IS-based VLC that is limited by pixel resolution of ISs.

A power packet dispatching system is proposed to realize the function of power on demand. This system distributes electrical power in quantized form, which is called power processing. This system has extensibility and flexibility. Here, we propose to use the power packet dispatching system as the next generation power distribution system in self-established and closed system such as robots, cars, and aircrafts. This paper introduces the concept and the required researches to take the power packet dispatching system in practical phase from the total viewpoints of devices, circuits, power electronics, system control, computer network, and bio-inspired power consumption.

In the newly finalized video coding standard, namely high efficiency video coding (HEVC), new notations like coding unit (CU), prediction unit (PU) and transformation unit (TU) are introduced to improve the coding performance. As a result, the reconstruction loop in intra encoding is heavily burdened to choose the best partitions or modes for them. In order to solve the bottleneck problems in cycle and hardware cost, this paper proposed a high-throughput and compact implementation for such a reconstruction loop. By “high-throughput”, it refers to that it has a fixed throughput of 32 pixel/cycle independent of the TU/PU size (except for 4×4 TUs). By “compact”, it refers to that it fully explores the reusability between discrete cosine transform (DCT) and inverse discrete cosine transform (IDCT) as well as that between quantization (Q) and de-quantization (IQ). Besides the contributions made in designing related hardware, this paper also provides a universal formula to analyze the cycle cost of the reconstruction loop and proposed a parallel-process scheme to further reduce the cycle cost. This design is verified on the Stratix IV FPGA. The basic structure achieved a maximum frequency of 150MHz and a hardware cost of 64K ALUTs, which could support the real time TU/PU partition decision for 4K×2K@20fps videos.

Spatial modulation (SM) is introduced into layered space-time coding (L-STC) used in image sensor (IS)-based visible light communication (VLC) systems. STC was basically investigated for extending the communication range of the IS-based VLC link [10], although it is out of the range when IS receivers are at the long distance from the LED array of the transmitter where the number of pixels capturing the transmitter on the image plane is less than the number of LEDs of the array. Furthermore, L-STC was done in [11] for increasing the reception rate with improving the pixel resolution while the receiver was approaching the transmitter. In this paper, SM is combined into L-STC by mapping additional information bits on the location of the pair of STC bit matrices of each layer. Experimental results show that additional SM bits are extracted with no error, without deteriorating the reception quality of and shrinking the transmission range of the original L-STC.

We investigate a finite-sized self-complementary bow-tie antenna (SC-BTA) integrated with a semiconductor mesa with respect to radiation characteristics such as the peak radiation frequency and bandwidth around the fundamental radiation mode. For this investigation, we utilize an equivalent circuit model of the SC-BTA derived in our previous work and a finite element method solver. Moreover, we derive design guidelines for the radiation characteristics in the form of size scaling-rules with respect to the antenna outer size for a terahertz transmitter.

Image sensor communication (ISC), a type of visible light communication, is an emerging wireless communication technology that uses LEDs to transmit a signal and uses an image sensor in a camera to receive the signal. This paper discusses the present status of and future trends in ISC by describing the essential characteristics and features of ISC. Moreover, we overview the products and expected future applications of ISC.

In this paper, we propose an algorithm that enhances the number of pixels for high-speed imaging. High-speed cameras have a principle problem that the number of pixels reduces when the number of frames per second (fps) increases. To enhance the number of pixels, we suppose an optical structure that block-randomly selects some percent of pixels in an image. Then, we need to reconstruct the entire image. For this, a state-of-the-art method takes three-dimensional reconstruction strategy, which requires a heavy computational cost in terms of time. To reduce the cost, the proposed method reconstructs the entire image frame-by-frame using a new cost function exploiting two types of sparsity. One is within each frame and the other is induced from the similarity between adjacent frames. The latter further means not only in the image domain, but also in a sparsifying transformed domain. Since the cost function we define is convex, we can find the optimal solution using a convex optimization technique with small computational cost. We conducted simulations using grayscale image sequences. The results show that the proposed method produces a sequence, mostly the same quality as the state-of-the-art method, with dramatically less computational time.

Particle filter algorithm is an important algorithm in the field of target tracking. however, this algorithm faces the problem of sample impoverishment which is caused by the introduction of re-sampling and easily affected by illumination variation. This problem seriously affects the tracking performance of a particle filter algorithm. To solve this problem, we introduce a particle filter target tracking algorithm based on a dynamic niche genetic algorithm. The application of this dynamic niche genetic algorithm to re-sampling ensures particle diversity and dynamically fuses the color and profile features of the target in order to increase the algorithm accuracy under the illumination variation. According to the test results, the proposed algorithm accurately tracks the target, significantly increases the number of particles, enhances the particle diversity, and exhibits better robustness and better accuracy.

The massive multiple input multiple output (MIMO) system with large-scale antenna array at base station (BS) simultaneously communicates with many mobile stations (MSs) ensuring high reliability using the pre-coding. But, in mobile communication, the performance of the pre-coding is degraded by fast fading. For improving the performance of the pre-coding, this letter proposes the power control scheme of the new approach that has the variable step size using the statistical characteristic of fast fading and Doppler frequency. From the simulation results, it is shown that the proposed scheme improves signal-to-interference-plus-noise ratio (SINR) performance.

This paper presents a high resolution mixed-domain Delta-Sigma (ΔΣ) time-to-digital converter (TDC) which utilizes a charge pump as time-to-voltage converter, a low resolution SAR ADC as quantizer, and a pair of delay-line digital-to-time converters to form a negative feedback. By never resetting the sampling capacitor of the charge-pump, an integrator is realized and first order noise shaping can be achieved. However, since the integrating capacitor is never cleared, this circuit is prone to charge-sharing issue during input sampling which can degrade TDC's performance. To deal with this issue, a compensation circuit consists of another pair of sampling capacitors and charge-pumps with doubled current is proposed. This TDC is designed and simulated in 65 nm CMOS technology and can operate at 200 MHz sampling frequency. For 2.5 MHz bandwidth, simulation shows that this TDC achieves 66.4 dB SNDR and 295 fsrms integrated noise for ±1 ns input range. The proposed TDC consumes 1.78 mW power that translates to FoM of 208 fJ/conv.

In this paper, a 500 MHz-BW -52.5 dB-THD Voltage-to-Time Converter (VTC) in 28 nm CMOS is presented. A two-step transition inverter raises the Voltage-to-Time (VT) conversion gain to 100 ps/V which is >10x higher than a conventional current-starved inverter. The number of required inverter stages is reduced to 4 from 64, resulting in 1/8 conversion latency and thus 13.2 dB THD suppression at a 500 MHz full Nyquist frequency. A feedback control of the bias voltage in the two-step transition inverter suppresses PVT variations in the VT conversion gain. A test-chip measurement successfully demonstrates -52.5 dB THD at 500 MHz input frequency without sampling-and-hold circuits. Effective VT conversion range over +/-64 ps time difference is measured with 1.2 Vpp differential input while keeping high linearity of less than +/-0.53 LSB INL/DNL, which results in 1 ps/LSB conversion linearity. The proposed VTC occupies 84 um2 silicon area and consumes 0.18 mW at 1 GS/s.

This paper presents the formal analysis of the feature negotiation and connection management procedures of the Datagram Congestion Control Protocol (DCCP). Using state space analysis we discover an error in the DCCP specification, that result in both ends of the connection having different agreed feature values. The error occurs when the client ignores an unexpected Response packet in the OPEN state that carries a valid Confirm option. This provides an evidence that the connection management procedure and feature negotiation procedures interact. We also propose solutions to rectify the problem.

This contribution presents and analyzes the statistical regularity related to the noise power spectrum series and the speech spectrum series. It also undertakes a thorough inquiry of the quasi-Gaussian distributed power spectrum series obtained using the radical root transformation. Consequently, a noise-estimation algorithm is proposed for speech enhancement. This method is effective for separating the noise power spectrum from the noisy speech power spectrum. In contrast to standard noise-estimation algorithms, the proposed method requires no speech activity detector. It was confirmed to be conceptually simple and well suited to real-time implementations. Practical experiment tests indicated that our method is preferred over previous methods.

This letter considers the robust transceiver design for multiple-input multiple-output interference channels under channel state information mismatch. According to alternating schemes, an adaptive algorithm is proposed to solve the minimum SINR maximization problem. Simulation results show the convergence and the effectiveness of the proposed algorithm.

This paper presents a novel framework called error case frames for correcting preposition errors. They are case frames specially designed for describing and correcting preposition errors. Their most distinct advantage is that they can correct errors with feedback messages explaining why the preposition is erroneous. This paper proposes a method for automatically generating them by comparing learner and native corpora. Experiments show (i) automatically generated error case frames achieve a performance comparable to previous methods; (ii) error case frames are intuitively interpretable and manually modifiable to improve them; (iii) feedback messages provided by error case frames are effective in language learning assistance. Considering these advantages and the fact that it has been difficult to provide feedback messages using automatically generated rules, error case frames will likely be one of the major approaches for preposition error correction.

In this paper, we present sub-1-V CMOS-based electrophoresis method for small-form-factor biomolecule manipulation that is contained in a microchip. This is the first time this type of device has been presented in the literature. By combining CMOS technology with electroless gold plating, the electrode pitch can be reduced and the required input voltage can be decreased to less than 1 V. We fabricated the CMOS electrophoresis chip in a cost-competitive 0.6 µm standard CMOS process. A sample/hold circuit in each cell is used to generate a constant output from an analog input. After forming gold electrodes using an electroless gold plating technique, we were able to manipulate red food coloring with a 0-0.7 V input voltage range. The results shows that the proposed CMOS chip is effective for electrophoresis-based manipulation.

Appearance-based generic object recognition is a challenging problem because all possible appearances of objects cannot be registered, especially as new objects are produced every day. Function of objects, however, has a comparatively small number of prototypes. Therefore, function-based classification of new objects could be a valuable tool for generic object recognition. Object functions are closely related to hand-object interactions during handling of a functional object; i.e., how the hand approaches the object, which parts of the object and contact the hand, and the shape of the hand during interaction. Hand-object interactions are helpful for modeling object functions. However, it is difficult to assign discrete labels to interactions because an object shape and grasping hand-postures intrinsically have continuous variations. To describe these interactions, we propose the interaction descriptor space which is acquired from unlabeled appearances of human hand-object interactions. By using interaction descriptors, we can numerically describe the relation between an object's appearance and its possible interaction with the hand. The model infers the quantitative state of the interaction from the object image alone. It also identifies the parts of objects designed for hand interactions such as grips and handles. We demonstrate that the proposed method can unsupervisedly generate interaction descriptors that make clusters corresponding to interaction types. And also we demonstrate that the model can infer possible hand-object interactions.

Existing noise inference algorithms neglected the smooth characteristics of noise data, which results in executing slowly of noise inference. In order to address this problem, we present a noise inference algorithm based on fast context-aware tensor decomposition (F-CATD). F-CATD improves the noise inference algorithm based on context-aware tensor decomposition algorithm. It combines the smoothness constraint with context-aware tensor decomposition to speed up the process of decomposition. Experiments with New York City 311 noise data show that the proposed method accelerates the noise inference. Compared with the existing method, F-CATD reduces 4-5 times in terms of time consumption while keeping the effectiveness of the results.

In this paper, we investigate a novel preamble channel estimation (CE) method based on the compressed sensing (CS) theory in the orthogonal frequency division multiplexing system with offset quadrature amplitude modulation (OQAM/OFDM) over a frequency selective fading channel. Most of the preamble based CE methods waste power by deploying the pilots in all the subcarriers. Inspired by the CS theory, we focus on using many fewer pilots than one of traditional CE methods and realize accurate reconstruction of the channel response. After describing and analyzing the concept of OQAM/OFDM and its traditional CE methods, we propose a novel channel estimation method based on CS that requires fewer pilots in the preamble, and we design the corresponding preamble pattern to meet the requirements of CS. Simulation results validate the efficiency and superior performance of the proposed method in wireless channel.