A closed form frequency estimator is derived for estimating the frequency of a complex exponential signal, embedded in white Gaussian noise. The new estimator consists of the fast Fourier transform (FFT) as the coarse estimation and the phase of autocorrelation lags as the fine-frequency estimator. In the fine-frequency estimation, autocorrelations are calculated from the power-spectral density of the signal, based on the Wiener-Khinchin theorem. For simplicity and suppressing the effect of noise, only the spectrum lines around the actual tone are used. Simulation results show that, the performance of the proposed estimator is approaching the Cramer-Rao Bound (CRB), and has a lower SNR threshold compared with other existing estimators.

This paper focuses on system level simulation of heterogeneous networks (HetNet). Aiming at the imbalance offloading of macro cell and pico cell under the macro-pico coexistence case, we propose an adaptive cell-specific association strategy for HetNet to ensure that users can be served equitably by both macro cell and pico cell. The traditional cell range expansion (CRE) scheme with bias-based cell association has fixed bias values for all pico cells. Our proposal, on the other hand, sets different thresholds of attached users for all MeNB (macro enhanced node B) and PeNBs (pico enhanced node B), and all cell-specific biases are obtained by the proposed adaptive association strategy according to different cell-specific predefined thresholds. With this strategy, the load imbalance between MeNB and different PeNBs is well alleviated, and hence the entire network performance is elevated. Moreover, due to the newly deployed low-power nodes in HetNets, the achieved spectral efficiency of users, especially for cell edge users, is also affected by the downlink inter-cell interference. The idea we put forward is to combine the frequency and power coordination, and so suppress the inter-cell interference. Finally in this paper, we present some numerical results to verify the effectiveness of our proposed approach.

In this paper, an energy harvesting architecture in an Underlay Cooperative Cognitive Network (UCCN) is investigated, in which power constrained Decode-and-Forward relays harvest energy from radio-frequency signals received from a source, and then consume the harvested energy by forwarding the recoded signals to their destination. These recoded signals are launched by a transmitting power which is the harvested energy per a time interval. Based on the energy harvesting architectures that have been studied, two operation protocols are proposed: UCCN with Power Splitting architecture (UCCN-PS), and UCCN with Time Switching architecture (UCCN-TS). The best cooperative relay in both protocols is taken to be the one that satisfies the following conditions: maximum harvested energy, and maximum decoding capacity. As a result of the best relay selection, the signal quality of the selected link from the best relay to the destination is enhanced by the maximum harvested energy. The system performance of the secondary network in the UCCN-PS and UCCN-TS protocols is analyzed and evaluated by the exact closed-form outage probabilities and throughput analyses over Rayleigh fading channels. The Monte Carlo simulation method is performed to verify the theoretical expressions. Evaluations based on outage probability and throughput show that the system performance of the secondary network in the UCCN-PS and UCCN-TS protocols improves when the number of cooperative relays and the interference constraint increase as well as when the primary receiver is farther from the transmitting nodes such as the source and relays of the secondary network. In addition, the throughput performance of the UCCN-PS protocol outperforms that of the UCCN-TS protocol. Finally, the effects of the power splitting ratio, energy harvesting time, energy conversion efficiency, target Signal-to-Noise Ratio (SNR), and location of cooperative relays on the system performance of the secondary network are presented and discussed.

Recommender systems, which provide users with recommendations of content suited to their needs, have received great attention in today's online business world. However, most recommendation approaches exploit only a single source of input data and suffer from the data sparsity problem and the cold start problem. To improve recommendation accuracy in this situation, additional sources of information, such as friend relationship and user-generated tags, should be incorporated in recommendation systems. In this paper, we revise the user-based collaborative filtering (CF) technique, and propose two recommendation approaches fusing user-generated tags and social relations in a novel way. In order to evaluate the performance of our approaches, we compare experimental results with two baseline methods: user-based CF and user-based CF with weighted friendship similarity using the real datasets (Last.fm and Movielens). Our experimental results show that our methods get higher accuracy. We also verify our methods in cold-start settings, and our methods achieve more precise recommendations than the compared approaches.

A robust time synchronization algorithm is proposed for orthogonal frequency division multiplexing (OFDM) based aeronautical mobile airport communication systems (AeroMACS). Using a very sharp timing metric obtained from the preamble, the proposed algorithm shows very robust time synchronization performance for various channel models in an airport. Simulation results show that the proposed algorithm achieves an SNR gain of 2 to 3dB at the failure rate of 10-2 to 10-3 compared with previous algorithms.

Monopulse is a classical technique for radar angle estimation and still adopted for fast angle estimation in phased array antenna. The classical formula can be applied to a 2-dimentional phased array antenna if two conditions---the unbiasedness and the independence of the azimuth and the elevation estimate---are satisfied. However, if the sum and difference beams are adapted to suppress the interference under jamming condition, they can be severely distorted. Thus the difference beams become highly correlated and violate the conditions. In this paper, we show the numerical implementation of the generalized monopulse estimation using the distorted and correlated beams, especially for a subarray configured antenna. Because we use the data from the measured subarray patterns rather than the mathematical model, this numerical method can be easily implemented for the complex array configuration and gives good performance for the uncertainty of the real system.

Distributed file systems, which manage large amounts of data over multiple commercially available machines, have attracted attention as management and processing systems for Big Data applications. A distributed file system consists of multiple data nodes and provides reliability and availability by holding multiple replicas of data. Due to system failure or maintenance, a data node may be removed from the system, and the data blocks held by the removed data node are lost. If data blocks are missing, the access load of the other data nodes that hold the lost data blocks increases, and as a result, the performance of data processing over the distributed file system decreases. Therefore, replica reconstruction is an important issue to reallocate the missing data blocks to prevent such performance degradation. The Hadoop Distributed File System (HDFS) is a widely used distributed file system. In the HDFS replica reconstruction process, source and destination data nodes for replication are selected randomly. We find that this replica reconstruction scheme is inefficient because data transfer is biased. Therefore, we propose two more effective replica reconstruction schemes that aim to balance the workloads of replication processes. Our proposed replication scheduling strategy assumes that nodes are arranged in a ring, and data blocks are transferred based on this one-directional ring structure to minimize the difference in the amount of transfer data for each node. Based on this strategy, we propose two replica reconstruction schemes: an optimization scheme and a heuristic scheme. We have implemented the proposed schemes in HDFS and evaluate them on an actual HDFS cluster. We also conduct experiments on a large-scale environment by simulation. From the experiments in the actual environment, we confirm that the replica reconstruction throughputs of the proposed schemes show a 45% improvement compared to the HDFS default scheme. We also verify that the heuristic scheme is effective because it shows performance comparable to the optimization scheme. Furthermore, the experimental results on the large-scale simulation environment show that while the optimization scheme is unrealistic because a long time is required to find the optimal solution, the heuristic scheme is very efficient because it can be scalable, and that scheme improved replica reconstruction throughput by up to 25% compared to the default scheme.

This paper presents an inductive coupling interface using a relay transmission scheme and a low-skew 3D clock distribution network synchronized with an external reference clock source for 3D chip stacking. A relayed transmission scheme using one coil is proposed to reduce the number of coils in a data link. Coupled resonation is utilized for clock and data recovery (CDR) for the first time in the world, resulting in the elimination of a source-synchronous clock link. As a result, the total number of coils required is reduced to one-fifth of the conventional number required, yielding a significant improvement in data rate, layout area, and energy consumption. A low-skew 3D clock distribution network utilizes vertically coupled LC oscillators and horizontally coupled ring oscillators. The proposed frequency-locking and phase-pulling scheme widens the lock range to $pm$ 10%. Two test chips were designed and fabricated in 0.18 $mu$m CMOS. The bandwidth of the proposed interface using relay transmission ThruChip Interface (TCI) is 2.7 Gb/s/mm$^2$; energy consumption per chip is 0.9 pJ/b/chip. Clock skew is less than 18- and 25- ps under a 1.8- and 0.9- V supply. The distributed RMS jitter is smaller than 1.72 ps.

Android applications that using WebView can load and display web pages. Interaction with web pages allows JavaScript code within the web pages to access resources on the Android device by using the Java object, which is registered into WebView. If this WebView feature were exploited by an attacker, JavaScript code could be used to launch attacks, such as stealing from or tampering personal information in the device. To address these threats, we propose an access control on the security-sensitive APIs at the Java object level. The proposed access control uses static analysis to identify these security-sensitive APIs, detects threats at runtime, and notifies the user if threats are detected, thereby preventing attacks from web pages.

People expose their personal information on social network services (SNSs). This paper warns of the dangers of this practice by way of an example. We show that the residence registration numbers (RRNs) of many Koreans, which are very important and confidential personal information analogous to social security numbers in the United States, can be estimated solely from the information that they have made open to the public. In our study, we utilized machine learning algorithms to infer information that was then used to extract a part of the RRNs. Consequently, we were able to extract 45.5% of SNS users' RRNs using a machine learning algorithm and brute-force search that did not consume exorbitant amounts of resources.

We propose a quasi-linear trellis-coded modulation (TCM) using nonbinary convolutional codes for quadrature amplitude modulation (QAM). First, we study a matched mapping which is able to reduce the computational complexity of the Euclidean distances between signal points of MQAM. As an example, we search for rate R=1/2 convolutional codes for coded 64QAM by this method. The symbol error rates of the proposed codes are estimated by the distance properties theoretically and they are verified by simulation. In addition, we compare the minimum free Euclidean distances of these new codes with their upper bounds. Finally, the bit error probabilitiy of the proposed coded modulation is compared with uncoded signal constellations and a conventional TCM code proposed by Ungerboeck. The result shows the proposed scheme outperform them on the AWGN channels.

This paper discusses the perspectives of using a wake-up receiver (WUR) in wireless body area network (WBAN) applications with event-driven data transfers. First we compare energy efficiency between the WUR-based and the duty-cycled medium access control protocol -based IEEE 802.15.6 compliant WBAN. Then, we review the architectures of state-of-the-art WURs and discuss their suitability for WBANs. The presented results clearly show that the radio frequency envelope detection based architecture features the lowest power consumption at a cost of sensitivity. The other architectures are capable of providing better sensitivity, but consume more power. Finally, we propose the design modification that enables using a WUR to receive the control commands beside the wake-up signals. The presented results reveal that use of this feature does not require complex modifications of the current architectures, but enables to improve energy efficiency and latency for small data blocks transfers.

We analyze the error performance of coding for ordered random variables with side information at the decoder, where encoder input as well as side information are deliberately extracted from the output of correlated sources. A tight upper bound on error probability is derived for linear encoding, and minimum distance decoding for a binary source and Gaussian distributed side information. Some features caused by the signal extraction are discussed.

The field electron emission characteristics of a p-type Si emitter sharpened by a spirally scanned Ga focused-ion-beam milling process were investigated. Saturated Fowler--Nordheim (F--N) plots, which are unique phenomena of p-type semiconductor emitters, were observed. The slight increase of the emission current in the saturated F--N plots region was discussed in terms of the depletion layer width in which electron generation occurs. The temperature dependence of the field electron emission current was also discussed. The activation energy of carrier generation was determined to be 0.26,eV, ascribable to the surface states that accompany the defects introduced by the Ga ion beam. When the emitter was irradiated by a 650-nm-wavelength laser, the increase in the emission current, i.e., the photoexcited emission current, was observed in the saturated region of the F--N plots. The photoexcited emission current was proportional to the laser intensity.

Recommendation systems have been widely used in E-commerce sites, social media and etc. An important recommendation task is to predict items that a user will perform actions on with users' historical data, which is called top-K recommendation. Recently, there is huge amount of emerging items which are divided into a variety of categories and researchers have argued or suggested that top-K recommendation of item category could be very beneficial for users to make better and faster decisions. However, the traditional methods encounter some common but crucial problems in this scenario because additional information, such as time, is ignored. The ranking algorithm on graphs and the increasingly growing amount of online user behaviors shed some light on these problems. We propose a construction method of time-aware graphs to use ranking algorithm for personalized recommendation of item category. Experimental results on real-world datasets demonstrate the advantages of our proposed method over competitive baseline algorithms.

In order to improve the motion control performance, a new friction determination method, using the LuGre model, is proposed. The model parameters are determined by performing two-step closed-loop experiments using a proportional-integral observer (PIO). The PIO is also used to develop a robust motion controller to deal with additional uncertainties including the effect of the inaccurate estimation of the friction. The experimental results reveal improved performance compared to that of a single-PIO-based controller.

Compressive sensing (CS) exploits the sparsity or compressibility of signals to recover themselves from a small set of nonadaptive, linear measurements. The number of measurements is much smaller than Nyquist-rate, thus signal recovery is achieved at relatively expense. Thus, many signal processing problems which do not require exact signal recovery have attracted considerable attention recently. In this paper, we establish a framework for parameter estimation of a signal corrupted by additive colored Gaussian noise (ACGN) based on compressive measurements. We also derive the Cramer-Rao lower bound (CRB) for the frequency estimation problems in compressive domain and prove some useful properties of the CRB under different compressive measurements. Finally, we show that the theoretical conclusions are along with experimental results.

The short-channel effect (SCE) in a MOSFET with an atomically thin MoS$_{2}$ channel was studied using a TCAD simulator. We derived the surface potential roll-up, drain-induced barrier lowering (DIBL), threshold voltage, and subthreshold swing (SS) as indexes of the SCE and analyzed their dependency on the channel thickness (number of atomic layers) and channel length. The minimum scalable channel length for a one-atomic-layer-thick MoS$_{2}$ MOSFET was determined from the threshold voltage roll-off to be 7.6,nm. The one-layer-thick device showed a small DIBL of 87,mV/V at a 20 nm gate length. By using high-k gate insulator, an SS lower than 70,mV/dec is achievable in sub-10-nm-scale devices.

This paper presents a downlink interference mitigation framework for two-tier heterogeneous networks, that consist of spectrum-sharing macrocells and femtocells*. This framework establishes cooperation between the two tiers through two algorithms, namely, the restricted waterfilling (RWF) algorithm and iterative reweighted least squares interference alignment (IRLS-IA) algorithm. The proposed framework models the macrocell-femtocell two-tier cellular system as an overlay cognitive radio system in which the macrocell system plays the role of the primary user (PU) while the femtocell networks play the role of the cognitive secondary users (SUs). Through the RWF algorithm, the macrocell basestation (MBS) cooperates with the femtocell basestations (FBSs) by releasing some of its eigenmodes to the FBSs to do their transmissions even if the traffic is heavy and the MBS's signal to noise power ratio (SNR) is high. Then, the FBSs are expected to achieve a near optimum sum rate through employing the IRLS-IA algorithm to mitigate both the co-tier and cross-tier interference at the femtocell users' (FUs) receivers. Simulation results show that the proposed IRLS-IA approach provides an improved sum rate for the femtocell users compared to the conventional IA techniques, such as the leakage minimization approach and the nuclear norm based rank constraint rank minimization approach. Additionally, the proposed framework involving both IRLS-IA and RWF algorithms provides an improved total system sum rate compared with the legacy approaches for the case of multiple femtocell networks.

Forty years after the first application of Superconducting Quantum Interference Devices (SQUIDs) [1], [2] for geophysical purposes, they have recently become a valued tool for mineral exploration. One of the most common applications is time domain (or transient) electromagnetics (TEM), an active method, where the inductive response from the ground to a changing current (mostly rectangular) in a loop on the surface is measured. After the current in the transmitter coil is switched, eddy currents are excited in the ground, which decay in a manner dependent on the conductivity of the underlying geologic structure. The resulting secondary magnetic field at the surface is measured during the off-time by a receiver coil (induced voltage) or by a magnetometer (e.g. SQUID or fluxgate). The recorded transient signal quality is improved by stacking positive and negative decays. Alternatively, the TEM results can be inverted and give the electric conductivity of the ground over depth. Since SQUIDs measure the magnetic field with high sensitivity and a constant frequency transfer function, they show a superior performance compared to conventional induction coils, especially in the presence of strong conductors. As the primary field, and especially its slew rate, are quite large, SQUID systems need to have a large slew rate and dynamic range. Any flux jump would make the use of standard stacking algorithms impossible. IPHT and Supracon are developing and producing SQUID systems based on low temperature superconductors (LTS, in our case niobium), which are now state-of-the-art. Due to the large demand, we are additionally supplying systems with high temperature superconductors (HTS, in our case YBCO). While the low temperature SQUID systems have a better performance (noise and slew rate), the high temperature SQUID systems are easier to handle in the field. The superior performance of SQUIDs compared to induction coils is the most important factor for the detection of good conductors at large depth or ore bodies underneath conductive overburden.