In heterogenous networks (HetNets), the deployment of small cells with the reuse of limited frequency resources to improve the spectral efficiency results in cross- and co-tier interference. In addition, the excessive power usage in such networks is also a critical problem. In this paper, we propose precoding and postcoding schemes to tackle interference and energy efficiency (EE) challenges in the two-tier downlink multiple-input-multiple-output (MIMO) HetNets. We propose transmission strategies based on hierarchical partial coordination (HPC) of the macro cell and small cells to reduce channel state information (CSI) exchange and guarantee the quality of service (QoS) in the upper tier with any change of network deployment in the lower tier. We employ the interference alignment (IA) scheme to cancel cross- and co-tier interference. Additionally, to maximize the EE, power allocation schemes in each tier are proposed based on a combination of Dinkelbach's method and the bisection searching approach. To investigate insights on the optimization problem, a theoretical analysis on the relationship between the maximum achievable EE and the transmit power is derived. Simulation results prove the superior EE performance of the proposed EE maximization scheme over the sum rate maximization approach and confirm the validity of our theoretical findings.

In order to realize an Internet-of-Things (IoT) with tiny sensors integrated in our buildings, our clothing, and the public spaces, battery lifetime and battery size remain major challenges. Power reduction in IoT sensor nodes is determined by both sleep mode as well as active mode contributions. A power state machine, at the system level, is the key to achieve ultra-low average power consumption by alternating the system between active and sleep modes efficiently. While, power consumption in the active mode remains dominant, other power contributions like for timekeeping in standby and sleep conditions are becoming important as well. For example, non-conventional critical blocks, such as crystal oscillator (XO) and resistor-capacitor oscillator (RCO) become more crucial during the design phase. Apart from power reduction, low-voltage operation will further extend the battery life. A 2.4GHz multi-standard radio is presented, as a test case, with an average power consumption in the µW range, and state-of-the-art performance across a voltage supply range from 1.2V to 0.9V.

A novel spur cancelled clock generator (SCCG) capable of recovering RX sensitivity degradations caused by digital clocks in wireless SoCs is presented. Clock spurs that degrade RX sensitivities are canceled by applying the SCCG to digital circuits or ADCs. The SCCG is integrated into a Bluetooth Low Energy (BLE) SoC fabricated in a 65 nm CMOS process. A measured clock spur reduction of 34 dB and an RX sensitivity recovery of 5 dB are achieved by the proposed SCCG. The power consumption and occupied area of the SCCG is only 18 µW and 40 μm × 120 μm, respectively.

This paper present a 20-GHz differential push-push voltage controlled oscillator (VCO) for 60-GHz frequency synthesizer. The 20-GHz VCO consists of a 10-GHz in-phase injection-coupled QVCO (IPIC-QVCO) with tail-filter and a differential output push-push doubler for 20-GHz output. The VCO fabricated in 65-nm CMOS technology, it achieves tuning range of 3 GHz from 17.5 GHz to 20.4 GHz with a phase noise of -113.8 dBc/Hz at 1 MHz offset. The core oscillator consumes up to 71 mW power and a FoM of -180.2 dBc/Hz is achieved.

We propose a statistical processing method to reduce the time of chip test of high-resolution and low-speed analog-to-digital converters (ADCs). For this kinds of ADCs, due to the influence of noise, conventional histogram or momentum method suffers from long time to collect required data for averaging. The proposed method, based on physically weighing the ADC, intending to physical weights in ADC/DAC under test. It can suppress white noise to 1/22 than conventional method in a case of 10bit binary ADC. Or it can reduce test data to 1/8 or less, which directly means to reduce measuring time to 1/8 or less. In addition, it earns complete Integrated Non-Linearity (INL) and Differential Non-linearity (DNL) even missing codes happens due to less data points. In this report, we theoretically describe how to guarantee missing codes at lacked measured data points.

This paper presents a thin, compact beacon transmitter operating without needing battery replacement by using a photovoltaic (PV) film harvester. The beacon is formed of a power-control circuit (PCC) that can monitor small amounts of power from the harvester and properly control mode switching at low-power consumption. This leads to the realization of a maintenance-free beacon requiring no battery replacement. The beacon prototype is 55×20×2 mm in size and has a PV cell of 3 cm2. It allows a start-up operation from just 44-lux illuminance. The PV area required for the operation can be 1.7 times smaller than that of conventional beacons, thanks to the current saving with appropriate sequential control of the PCC. Since the beacon makes operation possible in emergency stairs, underground passages and other dark places, the application field for Internet of things (IoT) services can be expanded. Furthermore, a beacon equipped with a secondary battery (BSB: Beacon with Secondary Battery) can be configured by adding a charge-discharge power monitoring circuit. The BSB transmits an advertising packet during the daytime while charging surplus power, and works using the stored power during the night; this results in a continuous operation for one week with one transmission every 3 seconds even at 0-lux illuminance. Without developing a new radiofrequency chip or module, commercial low-power devices can be easily adjusted depending on the application by adding appropriate power-control circuits. We are convinced that this design scheme will be effective as a rapid design proposal for IoT services.

Narrow swipe sensor has been widely used in embedded systems such as smart-phone. However, the size of captured image is much smaller than that obtained by the traditional area sensor. Therefore, the limited template coverage is the performance bottleneck of such kind of systems. Aiming to increase the geometry coverage of templates, a novel fingerprint template feature synthesis scheme is proposed in the present study. This method could synthesis multiple input fingerprints into a wider template by clustering the minutiae descriptors. The proposed method consists of two modules. Firstly, a user behavior-based Registration Pattern Inspection (RPI) algorithm is proposed to select the qualified candidates. Secondly, an iterative clustering algorithm Modified Fuzzy C-Means (MFCM) is proposed to process the large amount of minutiae descriptors and then generate the final template. Experiments conducted over swipe fingerprint database validate that this innovative method gives rise to significant improvements in reducing FRR (False Reject Rate) and EER (Equal Error Rate).

The purpose of document modeling is to learn low-dimensional semantic representations of text accurately for Natural Language Processing tasks. In this paper, proposed is a novel attention-based hybrid neural network model, which would extract semantic features of text hierarchically. Concretely, our model adopts a bidirectional LSTM module with word-level attention to extract semantic information for each sentence in text and subsequently learns high level features via a dynamic convolution neural network module. Experimental results demonstrate that our proposed approach is effective and achieve better performance than conventional methods.

Second-order sampling of 2-D frequency distributions is examined in this paper. When a figure in the frequency space can fill up the entire frequency space by tiling, we call this figure a tiling cluster. We also introduce the concept of pair regions. The results obtained for the second-order sampling of 1-D and 2-D frequency distributions are arranged using these two concepts. The sampling functions and sampling positions of second-order sampling of a 2-D rectangular-complement highpass frequency distribution, which have not been solved until now, are explicitly presented by using these two concepts.

We propose a microphone array speech enhancement method that integrates spatial-cue-based source power spectral density (PSD) estimation and statistical speech model-based PSD estimation. The goal of this research was to clearly pick up target speech even in noisy environments such as crowded places, factories, and cars running at high speed. Beamforming with post-Wiener filtering is commonly used in many conventional studies on microphone-array noise reduction. For calculating a Wiener filter, speech/noise PSDs are essential, and they are estimated using spatial cues obtained from microphone observations. Assuming that the sound sources are sparse in the temporal-spatial domain, speech/noise PSDs may be estimated accurately. However, PSD estimation errors increase under circumstances beyond this assumption. In this study, we integrated speech models and PSD-estimation-in-beamspace method to correct speech/noise PSD estimation errors. The roughly estimated noise PSD was obtained frame-by-frame by analyzing spatial cues from array observations. By combining noise PSD with the statistical model of clean-speech, the relationships between the PSD of the observed signal and that of the target speech, hereafter called the observation model, could be described without pre-training. By exploiting Bayes' theorem, a Wiener filter is statistically generated from observation models. Experiments conducted to evaluate the proposed method showed that the signal-to-noise ratio and naturalness of the output speech signal were significantly better than that with conventional methods.

An online nonnegative matrix factorization (NMF) algorithm based on recursive least squares (RLS) is described in a matrix form, and a simplified algorithm for a low-complexity calculation is developed for frame-by-frame online audio source separation system. First, the online NMF algorithm based on the RLS method is described as solving the NMF problem recursively. Next, a simplified algorithm is developed to approximate the RLS-based online NMF algorithm with low complexity. The proposed algorithm is evaluated in terms of audio source separation, and the results show that the performance of the proposed algorithms are superior to that of the conventional online NMF algorithm with significantly reduced complexity.

An output voltage-current equation of charge pump DC-DC voltage multiplier using diodes is provided to cover wide clock frequency and output current ranges for designing energy harvester operating at a near-threshold voltage or in sub-threshold region. Equivalent circuits in slow and fast switching limits are extracted. The effective threshold voltage of the diode in slow switching limit is also derived as a function of electrical characteristics of the diodes, such as the saturation current and voltage slope parameter, and design parameters such as the number of stages, capacitance per stage, parasitic capacitance at the top plate of the main boosting capacitor, and the clock frequency. The model is verified compared with SPICE simulation.

Improving robustness in electrostatic discharge (ESD) protection by inserting drain-side isolated silicon-controlled rectifiers (SCRs) in a high-voltage (HV) p-channel lateral-diffused MOSFET (pLDMOS) device was investigated in this paper. Additionally, the effects of anti-ESD reliability in the HV pLDMOS transistors provided by this technique were evaluated. From the experimental data, it was determined that the holding voltage (Vh) values of the pLDMOS with an embedded npn-arranged SCR and discrete thin-oxide (OD) layout on the cathode side increased as the parasitic SCR OD row number decreased. Moreover, the trigger voltage (Vt1) and the Vh values of the pLDMOS with a parasitic pnp-arranged SCR and discrete OD layout on the drain side fluctuated slightly as the SCR OD-row number decreased. Furthermore, the secondary breakdown current (It2) values (i.e., the equivalent ESD-reliability robustness) of all pLDMOS-SCR npn-arranged types increased (>408.4%) to a higher degree than those of the pure pLDMOS, except for npn-DIS_3 and npn-DIS_2, which had low areas of SCRs. All pLDMOS-SCR pnp-arranged types exhibited an increase of up to 2.2A-2.4A, except for the pnp_DIS_3 and pnp_DIS_2 samples; the pnp_DIS_91 increased by approximately 2000.9% (249.1%), exhibiting a higher increase than that of the reference pLDMOS (i.e., the corresponding pnp-stripe type). The ESD robustness of the pLDMOS-SCR pnp-arranged type and npn-arranged type with a discrete OD layout on the SCR cathode side was greater than that of the corresponding pLDMOS-SCR stripe type and a pure pLDMOS, particularly in the pLDMOS-SCR pnp-arranged type.

This paper presents accurate DC and high frequency power-supply rejection (PSR) models for low drop-out (LDO) regulators using different types of active loads and pass transistors. Based on the proposed PSR model, we suggest design guidelines to achieve a high DC PSR or flat bandwidth (BW) by choosing appropriate active loads and pass transistors. Our PSR model captures the intricate interaction between the error amplifiers (EAs) and the pass devices by redefining the transfer function of the LDO topologies. The accuracy of our model has been verified through SPICE simulation and measurements. Moreover, the measurement results of the LDOs fabricated using the 0.18 µm CMOS process are consistent with the design guidelines suggested in this work.

We report on robust and low-power-consumption InP- and GaN-HEMT Low-Noise-Amplifiers (LNAs) operating in Q-band frequency range. A multi-stage common-gate (CG) amplifier with current reuse topology was used. To improve the survivability of the CG amplifier, we introduced a feedback resistor at the gate bias feed. The design technique was adapted to InP- and GaN-HEMT LNAs. The 75nm gate length InP HEMT LNA exhibited a gain of 18dB and a noise figure (NF) of 3dB from 33 to 50GHz. The DC power consumption was 16mW. The Robustness of the InP HEMT LNA was tested by injecting a millimeter-wave input power of 13dBm for 10 minutes. No degradation in a small signal gain was observed. The fabricated 0.12µm gate length GaN HEMT LNA exhibited a gain of 15dB and an NF of 3.2dB from 35 to 42GHz. The DC power consumption was 280mW. The LNA survived until an input power of 28dBm.

Nowadays, vector map content is widely used in the areas of life, science and the military. Due to the fact that vector maps bring great value and that their production process is expensive, a large volume of vector map data is attacked, stolen and illegally distributed by pirates. Thus, vector map data must be encrypted before being stored and transmitted in order to ensure the access and to prevent illegal copying. This paper presents a novel perceptual encryption algorithm for ensuring the secured storage and transmission of vector map data. Polyline data of vector maps are extracted to interpolate a spline curve, which is represented by an interpolating vector, the curvature degree coefficients, and control points. The proposed algorithm is based on encrypting the control points of the spline curve in the frequency domain of discrete cosine transform. Control points are transformed and selectively encrypted in the frequency domain of discrete cosine transform. They are then used in an inverse interpolation to generate the encrypted vector map. Experimental results show that the entire vector map is altered after the encryption process, and the proposed algorithm is very effective for a large dataset of vector maps.

Image steganography is a technique of embedding secret message into a digital image to securely send the information. In contrast, steganalysis focuses on detecting the presence of secret messages hidden by steganography. The modern approach in steganalysis is based on supervised learning where the training set must include the steganographic and natural image features. But if a new method of steganography is proposed, and the detector still trained on existing methods will generally lead to the serious detection accuracy drop due to the mismatch between training and detecting steganographic method. In this paper, we just attempt to process unsupervised learning problem and propose a detection model called self-learning ensemble discriminant clustering (SEDC), which aims at taking full advantage of the statistical property of the natural and testing images to estimate the optimal projection vector. This method can adaptively select the most discriminative subspace and then use K-means clustering to generate the ultimate class labels. Experimental results on J-UNIWARD and nsF5 steganographic methods with three feature extraction methods such as CC-JRM, DCTR, GFR show that the proposed scheme can effectively classification better than blind speculation.

The measurement accuracy of frequency difference of arrival (FDOA) is usually determinant for emitters location system using rapidly moving receivers. The classic technique of expanding the integration time of the cross ambiguity function (CAF) to achieve better performance of FDOA is likely to incur a significant computational burden especially for wideband signals. In this paper, a nonconsecutive short-time CAF's methods is proposed with expansion of root mean square (RMS) integration time, instead of the integration time, and a factor of estimation precision improvement is given which is relative to the general consecutive method. Furthermore, by analyzing the characteristic of coherent CAF and the influence of FDOA rate, an upper bound of the precision improvement factor is derived. Simulation results are provided to confirm the effectiveness of the proposed method.

This paper investigates the performance of an overloaded multiple-input multiple-output (MIMO) - orthogonal frequency division multiplexing (OFDM) system with and without antenna selection. In the overloaded MIMO-OFDM system, even if only a small amount of feedback is available, performance can be improved by selecting the transmit antennas. Thus, this paper compares the performance of an overloaded MIMO system with and without antenna selection under different code rates. It is shown that the performance of the MIMO-OFDM system for six signal streams with QPSK modulation is about 2.0dB better than that for three signal streams with 16QAM modulation while it is about 5.0dB better than that of the MIMO-OFDM system for two signal streams with 64QAM modulation at a bit error rate (BER) of 10-3. However, it is also shown that the performance of the overloaded MIMO system is worse if the code rate of the repetition code increases.