Named Data Networking (NDN) is a promising architecture for the future Internet and it is mainly designed for efficient content delivery and retrieval. However, producer mobility support is one of the challenging problems of NDN. This paper proposes a scheme which aims to optimize the tunneling-based producer mobility solution in NDN. It does not require NDN routers to change their routing tables (Forwarding Information Base) after a producer moves. Instead, the Interest packet can be sent from a consumer to the moved producer using the tunnel. The piggybacked Data packet which is sent back to the consumer will trigger the consumer to send the following Interest packets through the optimized path to the producer. Moreover, a naming scheme is proposed so that the NDN caching function can be fully utilized. An analysis is carried out to evaluate the performance of the proposal. The results indicate that the proposed scheme reduces the network cost compared to related works and supports route optimization for enhanced producer mobility support in NDN.

Novel design approaches for microwave active circuits using composite right-/left-handed (CRLH) transmission line (TL) stubs are presented. We show that, by modifying the dispersion diagram of the CRLH TL stub, the frequency band or the harmonic tuning capability can be enhanced in such a way that it would have been difficult or impractical if done using conventional micro-strip line stubs. The frequency response of the CRLH TL stub can be controlled almost arbitrarily while at the same time reducing the stub length significantly, because the dispersion curve in the left-handed region and in the right-handed region is controlled independently. As a proof of concept, a triple-band rectifier, single-band and dual-band harmonic tuning circuits for class-F amplifiers are demonstrated.

In this paper, we propose a similarity searchable encryption in the symmetric key setting for the weighted Euclidean distance, by extending the functional encryption scheme for inner product proposed by Bishop et al. [4]. Our scheme performs predetermined encoding independently of vectors x and y, and it obtains the weighted Euclidean distance between the two vectors while they remain encrypted.

In order to satisfy the very high traffic demand in crowded hotspot areas and realize adequate security in future fifth-generation networks, this paper studies physical-layer security in the downlink of a two-tier ultra dense heterogeneous network, where a ubiquitous array formed by ultra dense deployed small-cells surrounds a macrocell base station. In this paper, the locations of legitimate users and eavesdroppers are drawn from Poisson point processes. Then, the cumulative distribution functions of the receive signal-to-interference-plus-noise ratio for legitimate users and eavesdroppers are derived. Further, the average secrecy rate and secrecy coverage probability for each tier as well as for the whole network are investigated. Finally, we analyze the influences on secrecy performance caused by eavesdropper density, transmit power allocation ratio, antenna number allocation ratio, and association area radius.

This paper focuses on underwater wireless power transfer with electric coupling. First, the maximum available efficiency is derived by using the S-parameters of the parallel plate coupler. The frequency which represents the maximal value of the efficiency is revealed. Further, the elevation in the efficiency in association with a reduction of the electrode size is found. It is clarified that the elevation depends on the characteristic of the water dielectric loss. From these results, the optimal electrode size that obtains the maximal value of the efficiency is provided. Finally, we fabricate the couplers by utilizing the optimal frequency and the electrode size. The efficiency of 75.8% under water is achieved.

This paper introduces distributed array antenna (DAA) systems that offer high antenna gain. A DAA consists of several small antennas with improved antenna gain. This paper proposes a technique that suppresses the off-axis undesired radiation and compensates the time delay by combining signal processing with optimization of array element positioning. It suppresses the undesired radiation by compensating the delay timing with high accuracy and deliberately generating the inter-symbol interference (ISI) in side-lobe directions. Computer simulations show its effective suppression of the equivalent isotropic radiated power (EIRP) pattern and its excellent BER performance.

Locally repairable code (LRC) can recover any codeword symbol failure by accessing a small number of other symbols, which can increase the efficiency during the repair process. In a distributed storage system with locally repairable codes, any node failure can be rebuilt by accessing other fixed nodes. It is a promising prospect for the application of LRC. In this paper, some methods of constructing matrices which can generate codes with small locality will be proposed firstly. By analyzing the parameters, we construct the generator matrices of the best-known ternary linear codes of dimension 6, using methods such as shortening, puncturing and expansion. After analyzing the linear dependence of the column vectors in the generator matrices above, we find out the locality of the codes they generate. Many codes with small locality have been found.

Wireless engineers and business planners commonly raise the question on where, when, and how millimeter-wave (mmWave) will be used in 5G and beyond. Since the next generation network is not just a new radio access standard, but also an integration of networks for vertical markets with diverse applications, answers to the question depend on scenarios and use cases to be deployed. This paper gives four 5G mmWave deployment examples and describes in chronological order the scenarios and use cases of their probable deployment, including expected system architectures and hardware prototypes. The first example is a 28 GHz outdoor backhauling for fixed wireless access and moving hotspots, which will be demonstrated at the PyeongChang Winter Olympic Games in 2018. The second deployment example is a 60 GHz unlicensed indoor access system at the Tokyo-Narita airport, which is combined with Mobile Edge Computing (MEC) to enable ultra-high speed content download with low latency. The third example is mmWave mesh network to be used as a micro Radio Access Network (µ-RAN), for cost-effective backhauling of small-cell Base Stations (BSs) in dense urban scenarios. The last example is mmWave based Vehicular-to-Vehicular (V2V) and Vehicular-to-Everything (V2X) communications system, which enables automated driving by exchanging High Definition (HD) dynamic map information between cars and Roadside Units (RSUs). For 5G and beyond, mmWave and MEC will play important roles for a diverse set of applications that require both ultra-high data rate and low latency communications.

Network equipment, such as routers, switches, and RADIUS servers, generate various log messages induced by network events such as hardware failures and protocol flaps. In large production networks, analyzing the log messages is crucial for diagnosing network anomalies; however, it has become challenging due to the following two reasons. First, the log messages are composed of unstructured text messages generated in accordance with vendor-specific rules. Second, network events that induce the log messages span several geographical locations, network layers, protocols, and services. We developed a method to tackle these obstacles consisting of two techniques: statistical template extraction (STE) and log tensor factorization (LTF). The former leverages a statistical clustering technique to automatically extract primary templates from unstructured log messages. The latter builds a statistical model that collects spatial-temporal patterns of log messages. Such spatial-temporal patterns provide useful insights into understanding the impact and patterns of hidden network events. We evaluate our techniques using a massive amount of network log messages collected from a large operating network and confirm that our model fits the data well. We also investigate several case studies that validate the usefulness of our method.

This paper proposes a new methodology to design optimal antennas for MIMO (Multi-Input Multi-Output) communication systems by using spherical mode expansion. Given spatial channel properties of a MIMO channel, such as the angular profile at both sides, the optimal MIMO antennas should provide the largest channel capacity with a constraint of the limited implementation space (volume). In designing a conventional MIMO antenna, first the antenna structure (current distribution) is determined, second antenna directivity is calculated based on the current distribution, and thirdly MIMO channel capacity is calculated by using given angular profiles and obtained antenna directivity. This process is repeated by adjusting the antenna structure until the performance satisfies a predefined threshold. To the contrary, this paper solves the optimization problem analytically and finally gives near optimal antenna structure (current distribution) without any greedy search. In the proposed process, first the optimal directivity of MIMO antennas is derived by applying spherical mode expansion to the angular profiles, and second a far-near field conversion is applied on the derived optimal directivity to achieve near optimal current distributions on a limited surface. The effectiveness of the proposed design methodology is validated via numerical calculation of MIMO channel capacity as in the conventional design method while giving near optimal current distribution with constraint of an antenna structure derived from proposed methodology.

Beamforming technology is an effective method to build a robust link. The commonly used digital beamforming is an expensive and power consuming approach to realizing millimeter-wave transmission. This makes radio frequency(RF) beamforming, which has low cost and low power consumption due to its use of phase shifters the more feasible approach to creating stable links in the millimeter-wave band. Unfortunately, the performance of RF processing is degraded by the limited precision of digital phase shifters. In this paper, we analyze the gain loss caused by the limited precision of phase shifter in millimeter wave single stream beam steering. We deduce a theoretical relationship between the array gain loss and variance of phase error. The theoretical results are validated by the Monte Carlo simulations, which indicate that gain loss could be reduced by the increased precision of phase shifter. In practical applications, 4-bit phase shifters provide sufficient accuracy for single stream beam steering.

This paper presents a novel identification method for hybrid dynamical system models, where parameters have stochastic and time-varying characteristics. The proposed parameter identification scheme is based on a modified implementation of particle filtering, together with a time-smoothing technique. Parameters of the identified model are considered as time-varying random variables. Parameters are identified independently at each time step, using the Bayesian inference implemented as an iterative particle filtering method. Parameters time dynamics are smoothed using a distribution based moving average technique. Modes of the hybrid system model are handled independently, allowing any type of nonlinear piecewise model to be identified. The proposed identification scheme has low computation burden, and it can be implemented for online use. Effectiveness of the scheme is verified by numerical experiments, and an application of the method is proposed: analysis of driving behavior through identified time-varying parameters.

A Wiener-based inpainting quality prediction method is presented in this paper. The proposed method is the first method that can predict inpainting quality both before and after the intensities have become missing even if their inpainting methods are unknown. Thus, when the target image does not include any missing areas, the proposed method estimates the importance of intensities for all pixels, and then we can know which areas should not be removed. Interestingly, since this measure can be also derived in the same manner for its corrupted image already including missing areas, the expected difficulty in reconstruction of these missing pixels is predicted, i.e., we can know which missing areas can be successfully reconstructed. The proposed method focuses on expected errors derived from the Wiener filter, which enables least-squares reconstruction, to predict the inpainting quality. The greatest advantage of the proposed method is that the same inpainting quality prediction scheme can be used in the above two different situations, and their results have common trends. Experimental results show that the inpainting quality predicted by the proposed method can be successfully used as a universal quality measure.

Multichannel speech enhancement systems (MSES') have been widely utilized for diverse types of speech interface applications. A state-of-the-art MSES primarily utilizes multichannel minima-controlled recursive averaging for noise estimations and a parameterized multichannel Wiener filter for noise reduction. Many MSES' are implemented in the frequency domain, but they are computationally burdensome due to the numerous complex matrix operations involved. In this paper, a novel MSES intended to reduce the computational complexity with improved performance is proposed. The proposed system is implemented in the mel-filterbank domain using a frequency-averaging technique. Through a performance evaluation, it is verified that the proposed mel-filterbank MSES achieves improvements in the perceptual speech quality with a reduced level of computation compared to a conventional MSES.

The Long Term Evolution (LTE) of mobile communication standard was designed by the 3rd generation partnership project (3GPP) to serve the requirements. Nowadays, the combining of the orthogonal frequency division multiplexing (OFDM) and the multiple input multiple output (MIMO) is supported in LTE system. The MIMO-OFDM is considered to improve data rate and channel capacity without additional bandwidth. Because the receivers get all transmission signals from all transmitters at the same time, many detection schemes have been developed for accurate estimation and low complexity. Among the detection schemes, the QR decomposition with M algorithm (QRD-M) achieves optimal error performance with low complexity. Nevertheless, the conventional QRD-M has high complexity for implementation. To overcome the problem, this letter proposes the low complexity QRD-M detection scheme in MIMO-OFDM systems. The proposed scheme has two elements which decide layer value and the limited candidates. The two elements are defined by the number of transmit antennas and the cardinality of modulation set respectively. From simulation results, the proposed scheme has the same error performance with the conventional QRD-M and very lower complexity than the conventional QRD-M.

This paper deals with a novel, interesting problem of detecting frauds in comparison-shopping services (CSS). In CSS, there exist frauds who perform excessive clicks on a target item. They aim at making the item look very popular and subsequently ranked high in the search and recommendation results. As a result, frauds may distort the quality of recommendations and searches. We propose an approach of detecting such frauds by analyzing click behaviors of users in CSS. We evaluate the effectiveness of the proposed approach on a real-world clickstream dataset.

In this paper, a novel approach is proposed for stereo vision-based ground plane detection at superpixel-level, which is implemented by employing a Disparity Texture Map in a convolution neural network architecture. In particular, the Disparity Texture Map is calculated with a new Local Disparity Texture Descriptor (LDTD). The experimental results demonstrate our superior performance in KITTI dataset.

Range resolution is one of the metrics of radar performance. Synthetic bandwidth radar has been proposed for high-range-resolution. The transmitted frequency and down-conversion frequency of this type of radar are shifted by fixed amounts from pulse to pulse. Received signals are synthesized by taking IFFT for high-range-resolution. However, this type of radar has a problem with second-time-around echoes since multiple pulses are utilized. Moreover, a range shift occurs due to Doppler velocity. Thus second-time-around echo suppression and Doppler velocity compensation are required for accurate target range measurement. We show in this paper a Doppler velocity measurement method with second-time-around echo suppression for synthetic bandwidth radars. Our proposed method interleaves the transmission of ascending and descending frequency sequences. The Doppler velocity is measured by using a Fourier transform of the multiplication of the signals received using both sequences. The transmitted frequency difference of the adjacent pulses is wider than the bandwidth of the matched filter, so the second-time-around echoes are down-converted to the outside band of the matched filter and suppressed. We verify the principle of the proposed method using numerical simulations and experiments. The results show that second-time-around echoes were suppressed by 7.8dB, the Doppler velocity could be obtained and the range shift due to Doppler velocity was reduced by 7.37 times compared to the conventional SBR.

The breadth-first tree searching (BFTS) detection algorithm such as the QR decomposition with M algorithm (QRD-M) which is the generally K-best detection algorithm is suboptimal, but has high complexity. In this letter, the K-best BFTS detection algorithm having reduced complexity is proposed. The proposed detection algorithm calculates the channel condition to decide the thresholds for regulating complexity and performance and from the simulation results, it has good error performance with very low complexity.

In the case of drive-by download attacks, most malicious web sites identify the software environment of the clients and change their behavior. Then we cannot always obtain sufficient information appropriate to the client organization by automatic dynamic analysis in open services. It is required to prepare for expected incidents caused by re-accessing same malicious web sites from the other client in the organization. To authors' knowledge, there is no study of utilizing analysis results of malicious web sites for digital forensic on the incident and hedging the risk of expected incident in the organization. In this paper, we propose a system for evaluating the impact of accessing malicious web sites by using the results of multi-environment analysis. Furthermore, we report the results of evaluating malicious web sites by the multi-environment analysis system, and show how to utilize analysis results for forensic analysis and risk hedge based on actual cases of analyzing malicious web sites.