This paper discusses key technologies specific for fifth generation (5G) cellular systems which are expected to connect internet of things (IoT) based vertical sectors. Because services for 5G will be expanded drastically, from information transfer services to mission critical and massive connection IoT connection services for vertical sectors, and requirement for cellular systems becomes quite different compared to that of fourth generation (4G) systems, after explanation for the service and technical trends for 5G, key wireless access technologies will be discussed, especially, from the view point of what is new and how import. In addition to the introduction of new technologies for wireless access, flexibility of networking is also discussed because it can cope with QoS support services, especially to cope with end-to-end latency constraint conditions. Therefore, this paper also discuss flexible network configuration using mobile edge computing (MEC) based on software defined network (SDN) and network slicing.

In order to support user data rates of Gbps and above in the fifth generation (5G) communication systems, millimeter wave (mm-wave) communication is proposed as one of the most important enabling technologies. In this paper, we consider the spectrum bands shared by 5G cellular base stations (BS) and some existing networks, such as WiGig and proposed a method for spectrally efficient coexistence of multiple interfering BSs through adaptive self-organized beam scheduling. These BSs might use multiple radio access technologies belonging to multiple operators and are deployed in the unlicensed bands, such as 60GHz. Different from the recently emerging coexistence scenarios in the unlicensed 5GHz band, where the proposed methods are based on omni-directional transmission, beamforming needs to be employed in mm-wave bands to combat the high path loss problem. The proposed method is concerned with this new scenario of communication in the unlicensed bands where (a) beam-forming is mandatory to combat severe path loss, (b) without optimal scheduling of beams mutual interference could be severe due to the possibility of beam-collisions, (c) unlike LTE which users time-frequency resource blocks, a new resource, i.e., the beam direction, is used as mandatory feature. We propose in this paper a novel multi-RAT coexistence mechanism where neighbouring 5G BSs, each serving their own associated users, schedule their beam configurations in a self-organized manner such that their own utility function, e.g. spectral efficiency, is maximized. The problem is formulated as a combinatorial optimization problem and it is shown via simulations that our proposed distributed algorithms yield a comparable spectral efficiency for the entire networks as that using an exhaustive search, which requires global coordination among coexisting RATs and also has a much higher algorithmic complexity.

Cost-effective cloud storage services are attracting users with their convenience, but there is a trade-off between service availability and usage cost. We develop two cloud provider selection models for cloud storage services to minimize the total cost of usage. The models select multiple cloud providers to meet the user requirements while considering unavailability. The first model, called a user-copy (UC) model, allows the selection of multiple cloud providers, where the user copies its data to multiple providers. In addition to the user copy function of the UC model, the second model, which is called a user and cloud-provider copy (UCC) model, allows cloud providers to make copies of the data to deliver them to other cloud providers. The cloud service is available if at least one cloud provider is available. We formulate both models as integer linear programming (ILP) problems. Our performance evaluation observes that both models reduce the total cost of usage, compared to the single cloud provider selection approach. As the cost of bandwidth usage between a user and a cloud provider increases, the UCC model becomes more beneficial than the UC model. We implement the prototype for cloud storage services, and demonstrate our models via Science Information Network 5.

This paper presents study results regarding the analytical method for performance characteristics and application scheme, which cover a feature detection scheme using a Cyclic Prefix (CP) that is attached to an OFDM signal. The detection scheme is especially important when used as a sensing technology in advanced systems such as Device-to-Device (D-to-D) or Internet of Things (IoT). Herein, we present several basic performance characteristics of the signal processing involved in feature detection, namely, the Output S/N (Signal-to-Noise power ratio) and probability density functions of the OFDM signal and the noise measured at the output of the feature detector. The Output S/Nis described by an analytical expression and is also examined by conducting a software simulation. An analytical approach is investigated by modeling the spectral density of the OFDM signal and input noise and by executing the mathematical operations such as convolutional integration on the combination of OFDM signal and noise. The analytical results coincide closely with the simulation results. As for the applications to mobile communication system, some methods of the feature detection schemes are addressed. These are an estimation method for the Input C/N (Carrier-to-Noise power ratio) and a system discrimination scheme, especially under the assumption that two OFDM systems using different CP lengths are simultaneously operated in the same frequency. Furthermore, under the condition that two OFDM signals are transmitted in an asynchronous manner, a scheme to estimate their timing offset and signal power ratio is also described.

For a service-oriented architecture based system, the problem of synthesizing a concrete model, i.e., behavioral model, for each service configuring the system from an abstract specification, which is referred to as choreography, is known as the choreography realization problem. In this paper, we assume that choreography is given by an acyclic relation. We have already shown that the condition for the behavioral model is given by lower and upper bounds of acyclic relations. Thus, the degree of freedom for behavioral models increases; developing algorithms of synthesizing an intelligible model for users becomes possible. In this paper, we introduce several metrics for intelligibility of state machines, and study the algorithm of synthesizing Pareto efficient state machines.

In this paper, an algorithm is proposed for license plate recognition (LPR) in video traffic surveillance applications. In an LPR system, the primary steps are license plate detection and character segmentation. However, in practice, false alarms often occur due to images of vehicle parts that are similar in appearance to a license plate or detection rate degradation due to local illumination changes. To alleviate these difficulties, the proposed license plate segmentation employs an adaptive binarization using a superpixel-based local contrast measurement. From the binarization, we apply a set of rules to a sequence of characters in a sub-image region to determine whether it is part of a license plate. This process is effective in reducing false alarms and improving detection rates. Our experimental results demonstrate a significant improvement over conventional methods.

This study focuses on the design of electrical stimulator for retinal prosthesis. The stimulator must be designed such that the occurrence of electrolysis or any irreversible process in the electrodes and flexible lead is prevented in order to achieve safe stimulation over long periods using the large number of electrodes. Some types of biphasic current pulse circuits, charge balance circuits, and AC power delivery circuits were developed to address this issue. Electronic circuitry must be introduced in the stimulator to achieve the large number of electrodes required to obtain high quality of vision. The concept of a smart electrode, in which a microchip is embedded inside an electrode, is presented for future retinal prostheses with over 1000 electrodes.

Automatic music transcription from audio has long been one of the most intriguing problems and a challenge in the field of music information retrieval, because it requires a series of low-level tasks such as onset/offset detection and F0 estimation, followed by high-level post-processing for symbolic representation. In this paper, a comprehensive transcription system for monophonic singing voice based on harmonic structure analysis is proposed. Given a precise tracking of the fundamental frequency, a novel acoustic feature is derived to signify the harmonic structure in singing voice signals, regardless of the loudness and pitch. It is then used to generate a parametric mixture model based on the von Mises-Fisher distribution, so that the model represents the intrinsic harmonic structures within a region of smoothly connected notes. To identify the note boundaries, the local homogeneity in the harmonic structure is exploited by two different methods: the self-similarity analysis and hidden Markov model. The proposed system identifies the note attributes including the onset time, duration and note pitch. Evaluations are conducted from various aspects to verify the performance improvement of the proposed system and its robustness, using the latest evaluation methodology for singing transcription. The results show that the proposed system significantly outperforms other systems including the state-of-the-art systems.

Key fabrication technology for the Pt/TiO2-x/TiO2/TiO2+x/Pt nano-film memristor is investigated, including preparing platinum (Pt) electrodes and TiO2-x/TiO2/TiO2+x nano-films. The effect of oxygen flow rate and deposition rate during fabrication on O:Ti ratio of thin films is demonstrated. The fabricated nano-films with different oxygen concentration are validated by the analyzed results from X-ray photoelectron spectroscopy (XPS). The obtained memristor device shows the typical resistive switching behavior and nonvolatile memory effects. An analytical device model for Pt/TiO2-x/TiO2/TiO2+x/Pt nano-film memristor is developed based on the fundamental linear relationships between drift-diffusion velocity and the electric field, and boundary conditions are also incorporated in this model. This model is able to predict the relation between variables in the form of explicit formula, which is very critical in memristor-based circuit designs. The measurement results from real devices validate the proposed analytical device model. Some deviations of the model from the measured data are also analyzed and discussed.

In this letter, we propose a Hadoop-based Video Transcoding System (HVTS), which is designed to run on all major cloud computing services. HVTS is highly adapted to the structure and policies of Hadoop, thus it has additional capacities for transcoding, task distribution, load balancing, and content replication and distribution. To evaluate, our proposed system, we carry out two performance tests on our local testbed, transcoding and robustness to data node and task failures. The results confirmed that our system delivers satisfactory performance in facilitating seamless streaming services in cloud computing environments.

To ensure secure mobile communication, the communicating entities must know their mutual identities. The entities which need to be identified in a mobile communication system are mobile devices and the network. Third Generation Partnership Project (3GPP) has specified Evolved Packet System Authentication and Key Agreement (EPS AKA) procedure for the mutual authentication of user and the Long Term Evolution (LTE) network. EPS AKA certainly overcomes most of the vulnerabilities in the Global System for Mobile Communications (GSM) and Universal Mobile Telecommunication System (UMTS) access procedures. However, the LTE access procedure still has security weaknesses against some of the sophisticated security threats, such as, Denial-of-Service (DoS) attacks, Man-in-the-Middle (MitM) attacks, rogue base station attacks and fails to ensure privacy protection for some of the important parameters. This paper proposes an improved security framework for the LTE access procedure by ensuring the confidentiality protection of International Mobile Subscriber Identity (IMSI) and random-challenge RAND. Also, our proposed system is designed to reduce the impact of DoS attacks which try to overwhelm the network with useless computations. We use a one-time shared key with a short lifetime between the UE and MME to protect IMSI and RAND privacy. Finally, we explore the parameters design for the proposed system which leads to satisfy the requirements imposed on computational load and latency as well as security strength.

Device-to-device (D2D) communication enables two local users to communicate with each other directly instead of relaying through a third party, e.g., base station. In this paper, we study a subchannel sharing strategy underlaying multichannel cellular network for D2D pairs and existing cellular users (CUs). In the investigated scenario, we try to improve the spectrum efficiency of D2D pairs, but inevitably brings cross interference between two user groups. To combat interference, we attempt to assign each D2D pair with appropriate subchannels, which may belong to different CUs, and manipulate transmission power of all users so as to maximize the sum rate of all D2D pairs, while assuring each CU with a minimum data rate on its subchannel set. The formulated problem is a nonconvex problem and thus, obtaining its optimal solution is a tough task. However, we can find optimal power and subchannel assignment for a special case by setting an independent data rate constraint on each subchannel. Then we find an efficient method to calculate a gradient for our original problem. Finally, we propose a gradient-based search method to address the problem with coupled minimum data rate constraint. The performance of our proposed subchannel sharing strategy is illustrated via extensive simulation results.

Wi-Fi Direct is a promising and available technology for device-to-device (D2D) proximity communications. To improve the performances of Wi-Fi Direct communication, optimized radio resource allocations are important. This paper proposes network assisted Wi-Fi Direct (NAWD), which operates based on the media independent services framework of IEEE 802.21 standard, for optimizing radio resource allocations. The NAWD is enhanced Wi-Fi Direct with the assistance of infrastructure networks (e.g., cellular network) and allocates radio resources (e.g., frequency channels and transmit power) to reduce radio interferences among Wi-Fi Direct devices (e.g., smart phones and set-top boxes). The NAWD includes mechanisms for gathering configuration information (e.g., location information and network connection information) of Wi-Fi Direct devices and allocating optimized radio resources (e.g., frequency channels and transmit power) to reduce radio interferences among Wi-Fi Direct devices. Simulation results show that the proposed NAWD increases significantly SINR, power efficiency, and areal capacity compared to legacy Wi-Fi Direct, where areal capacity is total traffic throughput per unit area.

Effective communication strategies with a properly designed source precoding matrix (PM) and a properly designed relay beamforming matrix (BM) can significantly improve the spectral efficiency of multiple-input multiple-output (MIMO) relaying broadcast channels (RBCs). In the present paper, we first propose a general communication scheme with non-regenerative relay that can overcome the half-duplex relay constraint of the general MIMO-RBC. Based on the proposed scheme, the robust source PM and relay BM are designed for imperfect channel state information at the transmitter (CSIT). In contrast to the conventional non-regenerative relaying communication scheme for the MIMO-RBC, in the proposed scheme, the source can send information continuously to the relay and users during two phases. Furthermore, in conjunction with the advanced precoding strategy, the proposed scheme can achieve a full-degree-of-freedom (DoF) MIMO-RBC with that each entry in the related channel matrix is considered to an i.i.d. complex Gaussian variable. The robust source PM and relay BM designs were investigated based on both throughput and fairness criteria with imperfect CSIT. However, solving the problems associated with throughput and fairness criteria for the robust source PM and relay BM designs is computationally intractable because these criteria are non-linear and non-convex. In order to address these difficulties, we first set up equivalent optimization problems based on a tight lower bound of the achievable rate. We then decompose the equivalent throughput problem into several decoupled subproblems with tractable solutions. Finally, we obtain the suboptimal solution for the throughput problem by an alternating optimization approach. We solve the fairness problem by introducing an adjusted algorithm according to the throughput problem. Finally, we demonstrate that, in both cases of throughput and fairness criteria, the proposed relaying communication scheme with precoding algorithms outperforms existing methods.

In this paper, Epitaxial (Epi) Junction Termination Extension (JTE) technique for silicon carbide (SiC) power device is presented. Unlike conventional JTE, the Epi-JTE doesn't require high temperature (about 500°C) implantation process. Thus, it doesn't require high temperature (about 1700°C) process for implanted dose activation and surface defect curing. Therefore, the manufacturing cost will be decreased. Also, the fabrication process is very simple because the dose of the JTE is controlled by epitaxy growth. The blocking characteristic is analyzed through 2D-simulation for the proposed Epi-JTE. In addition, the effect was validated by experiment of fabricated SiC device with the Single-Zone-Epi-JTE. As a result, it has blocking capability of 79.4% compared to ideal parallel-plane junction breakdown.

Fuzzy techniques can implement the fine-grained access control of encrypted data in the Cloud because they support error-tolerance. In this system, using biometric attributes such as fingerprints, faces and irises as pubic parameters is advantageous over those systems based on Public Key Infrastructure (PKI). This is because biometric information is unique, unforgettable and non-transferable. However the biometric-attribute measurements are noisy and most of the existing encryption systems can not support the biometric-attribute encryption. Additionally, the previous fuzzy encryption schemes only achieve the selective security which is a weak security model. To overcome these drawbacks, we propose a new fuzzy encryption scheme based on the lattice in this letter. The proposed scheme is based on a hierarchical identity-based encryption with fixed-dimensional private keys space and thus has short public parameters and short private keys, which results in high computation efficiency. Furthermore, it achieves the strong security, i.e., adaptive security. Lastly, the security is reduced to the learning with errors (LWE) problem in the standard model.

This paper first reviews the state-of-the-art noise reduction methods and points out their vulnerability in noise reduction performance and speech quality, especially under the low signal-noise ratios (SNR) environments. Then this paper presents an improved perceptual multiband spectral subtraction (MBSS) noise reduction algorithm (NRA) and a novel robust voice activity detection (VAD) based on the amended sub-band SNR. The proposed SNR-based VAD can considerably increase the accuracy of discrimination between noise and speech frame. The simulation results show that the proposed NRA has better segmental SNR (segSNR) and perceptual evaluation of speech quality (PESQ) performance than other noise reduction algorithms especially under low SNR environments. In addition, a fully operational digital hearing aid chip is designed and fabricated in the 0.13 µm CMOS process based on the proposed NRA. The final chip implementation shows that the whole chip dissipates 1.3 mA at the 1.2 V operation. The acoustic test result shows that the maximum output sound pressure level (OSPL) is 114.6 dB SPL, the equivalent input noise is 5.9 dB SPL, and the total harmonic distortion is 2.5%. So the proposed digital hearing aid chip is a promising candidate for high performance hearing-aid systems.

The translation based language model (TRLM) is state-of-the-art method to solve the lexical gap problem of the question retrieval in the community-based question answering (cQA). Some researchers tried to find methods for solving the lexical gap and improving the TRLM. In this paper, we propose a new dependency based model (DM) for the question retrieval. We explore how to utilize the results of a dependency parser for cQA. Dependency bigrams are extracted from the dependency parser and the language model is transformed using the dependency bigrams as bigram features. As a result, we obtain the significant improved performances when TRLM and DM approaches are effectively combined.

The development of smart devices has led to the growth of Location-Based Social Networking Services (LBSNSs). In this paper, we introduce an l-Close Range Friends query that finds all l-hop friends of a user within a specified range. We also propose a query processing method on Social Grid Index (SGI). Using real datasets, the performance of our method is evaluated.

This paper illustrates various content sharing systems that take advantage of cloud's storage and computational resources as well as their supporting conventional technologies. First, basic technology concepts supporting cloud-based systems from a client-server to cloud computing as well as their relationships and functional linkages are shown. Second, the taxonomy of cloud-based system models from the aspect of multiple clouds' interoperability is explained. Interoperability can be categorized into provider-centric and client-centric scenarios. Each can be further divided into federated clouds, hybrid clouds, multi-clouds and aggregated service by broker. Third, practical cloud-based systems related to contents sharing are reported and their characteristics are discussed. Finally, future direction of cloud-based content sharing is suggested.