A propagation experiment on an actual channel is conducted to confirm the effectiveness of the 1-tap time domain beamforming (TDBF) technique we proposed in previous work. This technique offers simple beamforming for the millimeter waveband massive multiple-input multiple-output (MIMO) applied wireless backhaul and so supports the rapid deployment of fifth generation mobile communications (5G) small cells. This paper details propagation experiments in the 75GHz band and the characteristics evaluations of 1-tap TDBF as determined from actual channel measurements. The results show that 1-tap TDBF array gain nearly equals the frequency domain maximal ratio combining (MRC) value, which is ideal processing; the difference is within 0.5dB. In addition, 1-tap TDBF can improve on the signal-to-interference power ratio (SIR) by about 13% when space division multiplexing (SDM) is performed assuming existing levels of channel estimation error.

The beamforming (BF) provided by Massive MIMO is a promising technique for the fifth-generation (5G) mobile communication system. In low SHF bands such as 3-6GHz, fully digital Massive MIMO can be a feasible option. Previous works proposed eigenvector zero-forcing (E-ZF) as a digital precoding algorithm to lower the complexity of block diagonalization (BD). On the other hand, another previous work aiming to reduce complexity of BD due to the number of antenna elements proposed digital fixed BF and channel-state-information based precoding (Digital FBCP) with BD whose parameter is the number of beams. Moreover, in order to lower the complexity of the Digital FBCP with BD while retaining the transmission performance, this paper proposes Digital FBCP with E-ZF as a lower complexity digital BF algorithm. The pros and cons of these digital BF algorithms in terms of transmission performance and computational complexity are clarified to select the most appropriate algorithm for the fully digital Massive MIMO. Furthermore, E-ZF can be implemented to 4.5GHz-band fully digital Massive MIMO equipment only when the number of antenna elements is less than or equal to 64, and thus 5G experimental trial employing E-ZF was carried out in Tokyo, Japan where early 5G commercial services will launch. To the best of our knowledge, this was the first outdoor experiment on 4.5GHz-ban Massive MIMO in a dense urban area. An outdoor experiment in a rural area was also carried out. This paper shows both a coverage performance under the single user condition and system throughput performance under a densely deployed four-user condition in the outdoor experimental trials employing the E-ZF algorithm. We reveal that, in the MU-MIMO experiment, the measured system throughput is almost 80% of the maximum system throughput even if users are closely located in the dense urban area thanks to the E-ZF algorithm.

With no need for Road Side Unit (RSU), multi-hop Vehicular Ad Hoc NETworks (VANETs) have drawn more and more attention recently. Considering the safety of vehicles, a Media Access Control (MAC) protocol for reliable transmission is critical for multi-hop VANETs. Most current works need RSU to handle the collisions brought by hidden-terminal problem and the mobility of vehicles. In this paper, we proposed RV-MAC, which is a reliable MAC protocol for multi-hop VANETs based on Time Division Multiple Access (TDMA). First, to address the hidden-terminal under the networks with multi-hop topology, we design a region marking scheme to divide vehicles into different regions. Then a collisions avoidance scheme is proposed to handle the collisions owing to channel competition and the mobility of vehicles. Simulation results show that compared with other protocol, RV-MAC can decrease contention collisions by 30% and encounter collisions by 50% respectively. As a result, RV-MAC achieves higher throughput and lower network delay.

Accurate traffic flow prediction is the precondition for many applications in Intelligent Transportation Systems, such as traffic control and route guidance. Traditional data driven traffic flow prediction models tend to ignore traffic self-features (e.g., periodicities), and commonly suffer from the shifts brought by various complex factors (e.g., weather and holidays). These would reduce the precision and robustness of the prediction models. To tackle this problem, in this paper, we propose a CNN-based multi-feature predictive model (MF-CNN) that collectively predicts network-scale traffic flow with multiple spatiotemporal features and external factors (weather and holidays). Specifically, we classify traffic self-features into temporal continuity as short-term feature, daily periodicity and weekly periodicity as long-term features, then map them to three two-dimensional spaces, which each one is composed of time and space, represented by two-dimensional matrices. The high-level spatiotemporal features learned by CNNs from the matrices with different time lags are further fused with external factors by a logistic regression layer to derive the final prediction. Experimental results indicate that the MF-CNN model considering multi-features improves the predictive performance compared to five baseline models, and achieves the trade-off between accuracy and efficiency.

In this paper, we consider network monitoring techniques to estimate communication qualities in wide-area mobile networks, where an enormous number of heterogeneous components such as base stations, routers, and servers are deployed. We assume that average delays of neighboring base stations are comparable, most of servers have small delays, and delays at core routers are negligible. Under these assumptions, we propose Heterogeneous Delay Tomography (HDT) to estimate the average delay at each network component from end-to-end round trip times (RTTs) between mobile terminals and servers. HDT employs a crowdsourcing approach to collecting RTTs, where voluntary mobile users report their empirical RTTs to a data collection center. From the collected RTTs, HDT estimates average delays at base stations in the Graph Fourier Transform (GFT) domain and average delays at servers, by means of Compressed Sensing (CS). In the crowdsourcing approach, the performance of HDT may be degraded when the voluntary mobile users are unevenly distributed. To resolve this problem, we further extend HDT by considering the number of voluntary mobile users. With simulation experiments, we evaluate the performance of HDT.

The explosive dynamics present in on-line social networks, typically represented by flaming phenomena, can have a serious impact on not only the sustainable operation of information networks but also on activities in the real world. In order to counter the flaming phenomenon, it is necessary to understand the mechanism underlying the generation of the flaming phenomena within an engineering framework. This paper discusses a new model of the generating mechanism of the flaming phenomena. Our previous study has shown that the cause of flaming phenomena can, by reference to an oscillation model on networks, be understood complex eigenvalues of the matrix formed to describe oscillating phenomena. In this paper, we show that the flaming phenomena can occur due to coupling between degenerated oscillation modes even if all the eigenvalues are real numbers. In addition, we investigate the generation process of flaming phenomena with respect to the initial phases of the degenerated oscillation modes.

Massive multiple input and multiple output (Massive MIMO) is a key technique to achieve high system capacity and user data rate for the fifth generation (5G) radio access network (RAN). To implement Massive MIMO in 5G, how much Massive MIMO meets our expectation with various user equipment (UEs) in different environments should be carefully addressed. We focused on using Massive MIMO in the low super-high-frequency (SHF) band, which is expected to be used for 5G commercial bands relatively soon. We previously developed a prototype low-SHF-band centralized-RAN Massive MIMO system that has a flexible active antenna system (AAS)-unit configuration and facilitates advanced radio coordination features, such as coordinated beamforming (CB) coordinated multi-point (CoMP). In this study, we conduct field trials to evaluate downlink (DL) multi-user (MU)-MIMO performance by using our prototype system in outdoor and indoor environments. The results indicate that about 96% of the maximum total DL system throughput can be achieved with 1 AAS unit outdoors and 2 AAS units indoors. We also investigate channel capacity based on the real propagation channel estimation data measured by the prototype system. Compared with without-CB mode, the channel capacity of with-CB mode increases by a maximum of 80% and 104%, respectively, when the location of UEs are randomly selected in the outdoor and indoor environments. Furthermore, the results from the field trial of with-CB mode with eight UEs indicate that the total DL system throughput and user data rate can be significantly improved.

This study proposes a Peak-to-Average Power Ratio (PAPR) reduction method using an adaptive Finite Impulse Response (FIR) filter in Orthogonal Frequency Division Multiplexing systems. At the transmitter, an iterative algorithm that minimizes the p-norm of a transmitted signal vector is used to update the weight coefficients of the FIR filter to reduce PAPR. At the receiver, the FIR filter used at the transmitter is estimated using pilot symbols, and its effect can be compensated for by using an equalizer for proper demodulation. Simulation results show that the proposed method is superior to conventional methods in terms of the PAPR reduction and computational complexity. It also shows that the proposed method has a trade-off between PAPR reduction and bit error rate performance.

In recent years, capsule endoscopy has attracted attention as one of the medical devices that examine internal digestive tracts without burdening patients. Wireless power transmission of the capsule endoscope has been researched now, and the power transmission efficiency can be improved by knowing the capsule location. In this paper, we develop a localization method wireless power transmission. Therefore, a simple algorithm for using received signal strength (RSS) has been developed so that position estimation can be performed in real time, and the performance is evaluated by performing three-dimensional localization with eight receiving antennas.

It becomes possible to prevent accidents beforehand by predicting dangerous riding behavior based on recognition of bicycle behaviors. In this paper, we propose a bicycle behavior recognition method using a three-axis acceleration sensor and three-axis gyro sensor equipped with a smartphone when it is installed on a bicycle handlebar. We focus on the periodic handlebar motions for balancing while running a bicycle and reduce the sensor noises caused by them. After that, we use machine learning for recognizing the bicycle behaviors, effectively utilizing the motion features in bicycle behavior recognition. The experimental results demonstrate that the proposed method accurately recognizes the four bicycle behaviors of stop, run straight, turn right, and turn left and its F-measure becomes around 0.9. The results indicate that, even if the smartphone is installed on the noisy bicycle handlebar, our proposed method can recognize the bicycle behaviors with almost the same accuracy as the one when a smartphone is installed on a rear axle of a bicycle on which the handlebar motion noises can be much reduced.

Due to improvements in hardware and software performance, deep learning algorithms have been used in many areas and have shown good results. In this paper, we propose a noise reduction framework based on a convolutional neural network (CNN) with deconvolution and a modified residual network (ResNet) to remove image noise. Simulation results show that the proposed algorithm is superior to the conventional noise eliminator in subjective and objective performance analyses.

Fifth-generation mobile communication systems (5G) must offer significantly higher system capacity than 4G in order to accommodate the rapidly increasing mobile data traffic. Cell densification has been considered an effective way to increase system capacity. Unfortunately, each user equipment (UE) will be in line-of-sight to many more transmission points (TPs) and the resulting inter-cell interference will degrade system capacity. We propose large-scale coordinated multi-user multiple-input multiple-output (LSC-MU-MIMO), which combines MU-MIMO with joint transmission from all the TPs connected to a centralized baseband unit. We previously investigated the downlink performance of LSC-MU-MIMO by computer simulation and found that it can significantly reduce inter-TP interference and improve the system capacity of high-density small cells. In this paper, we investigate the throughput of LSC-MU-MIMO through an indoor trial where the number of coordinated TPs is up to sixteen by using an experimental system that can execute real-time channel estimation based on TDD reciprocity and real-time data transmission. To clarify the improvement in the system capacity of LSC-MU-MIMO, we compared the throughput measured in the same experimental area with and without coordinated transmission in 4-TP, 8-TP, and 16-TP configurations. The results show that with coordinated transmission the system capacity is almost directly proportional to the number of TPs.

LINE is currently the most popular messaging service in Japan. Communications using LINE are protected by the original encryption scheme, called LINE Encryption, and specifications of the client-to-server transport encryption protocol and the client-to-client message end-to-end encryption protocol are published by the Technical Whitepaper. Though a spoofing attack (i.e., a malicious client makes another client misunderstand the identity of the peer) and a reply attack (i.e., a message in a session is sent again in another session by a man-in-the-middle adversary, and the receiver accepts these messages) to the end-to-end protocol have been shown, no formal security analysis of these protocols is known. In this paper, we show a formal verification result of secrecy of application data and authenticity for protocols of LINE Encryption (Version 1.0) by using the automated security verification tool ProVerif. Especially, since it is claimed that the transport protocol satisfies forward secrecy (i.e., even if the static private key is leaked, security of application data is guaranteed), we verify forward secrecy for client's data and for server's data of the transport protocol, and we find an attack to break secrecy of client's application data. Moreover, we find the spoofing attack and the reply attack, which are reported in previous papers.

The number of Internet-of-Things (IoT) devices will increase rapidly. In next-generation mobile communication systems, a base station (BS) must effectively accommodate massive numbers of IoT devices. To address this problem, we have proposed a novel up-link non-orthogonal multiple access (NOMA) system that can also be utilized for low latency communication. We have developed and evaluated the system through computer simulation. This paper describes experiments conducted on a prototype system in actual environments. The paper shows results of the experiments when 3 fixed user equipments (UEs) and 2 mobile UEs transmitted signals simultaneously to a BS and then the BS separated superimposed signals using successive interference cancellation (SIC). We also evaluated repetition transmission (RT) and space receive diversity (SD) techniques employed to enhance the signal separation performance for NOMA systems. The results of the experiments confirm that the system using neither SD nor RT could separate 3.5 UEs' signals on average while employing either SD or RT could make the number increase to 4.1 and 4.0, respectively. When both SD and RT were employed, the number rose to 4.4.

Denser infrastructures can reduce terminal-to-infrastructure distance and thus improve the link budget in mobile communication systems. One such infrastructure, relaying can reduce the distance between the donor evolved node B (eNB) and user equipment (UE). However, conventional relaying suffers from geographical constraints, i.e., installation site, and difficulty in simultaneous transmission and reception on the same carrier frequency. Therefore, we propose a new type of fiber-optic relaying in which the antenna facing the eNB is geographically separated from the antenna facing the UE, and the two antennas are connected by an optical fiber. This structure aims to extend coverage to heavily shadowed areas. Our primary objective is to establish a design method for the proposed fiber-optic relaying in the presence of self-interference, which is the interference between the backhaul and access links, when the backhaul and access links simultaneously operate on the same carrier frequency. In this paper, we present the performance of the fiber-optic relaying in the presence of intra- and inter-cell interferences as well as self-interference. The theoretical desired-to-undesired-signal ratio for both uplink and downlink is investigated as parameters of the optical fiber length. We demonstrate the possibility of fiber-optic relaying with simultaneous transmission and reception on the same carrier frequency for the backhaul and access links. We validate the design method for the proposed fiber-optic relay system using these results.

We have already proposed synchronized spread spectrum code division multiple access (SS-CDMA) for the Quasi-Zenith Satellite System (QZSS) safety confirmation system to be used in times of great disaster. In this system, the satellite reception timings of all uplink signals are synchronized using a transmission timing control method in order to realize high-density user multiple access. An issue that should be addressed in order for this system to be viable is the error that can occur in the satellite reception timing. This error occurs due to the terminal time deviation and the error in calculating the propagation delay to the satellite. In this paper, we measure the terminal time deviation and the propagation delay calculation error at the same time by using the same receivers and evaluate the satellite reception timing error of the uplink signal. By this measurement, it is shown that satellite reception timing error within 50ns can be realized in 99.98% of mobile terminals. This shows that the synchronized SS-CDMA with the transmission timing control method has a potential to realize the QZSS short message system with high-density user multiple access.

This paper presents a theoretical analysis of a tunable resonator using a coupled line and switches for the first time. The tunable resonator has the capability to tune its resonant frequency and bandwidth. The resonator has two suitable features on its tunable capability. The first feature is that the resonator retains its resonant frequency during bandwidth tuning. The second feature is that the on-state switch for tuning the bandwidth does not affect the insertion loss at the resonant frequency. These features are theoretically confirmed by its mathematically derived input impedance. The results from electromagnetic simulation and measurement of the fabricated tunable resonator also confirm these features. The fabricated tunable resonator changes the resonant frequency from 2.6 GHz to 6.4 GHz and bandwidth between 9% and 55%.

This paper presents recognition of anomalously deformed Kana sequences in Japanese historical documents, for which a contest was held by IEICE PRMU 2017. The contest was divided into three levels in accordance with the number of characters to be recognized: level 1: single characters, level 2: sequences of three vertically written Kana characters, and level 3: unrestricted sets of characters composed of three or more characters possibly in multiple lines. This paper focuses on the methods for levels 2 and 3 that won the contest. We basically follow the segmentation-free approach and employ the hierarchy of a Convolutional Neural Network (CNN) for feature extraction, Bidirectional Long Short-Term Memory (BLSTM) for frame prediction, and Connectionist Temporal Classification (CTC) for text recognition, which is named a Deep Convolutional Recurrent Network (DCRN). We compare the pretrained CNN approach and the end-to-end approach with more detailed variations for level 2. Then, we propose a method of vertical text line segmentation and multiple line concatenation before applying DCRN for level 3. We also examine a two-dimensional BLSTM (2DBLSTM) based method for level 3. We present the evaluation of the best methods by cross validation. We achieved an accuracy of 89.10% for the three-Kana-character sequence recognition and an accuracy of 87.70% for the unrestricted Kana recognition without employing linguistic context. These results prove the performances of the proposed models on the level 2 and 3 tasks.

We present an OpenACC-based parallelization implementation of stochastic algorithms for simulating biochemical reaction networks on modern GPUs (graphics processing units). To investigate the effectiveness of using OpenACC for leveraging the massive hardware parallelism of the GPU architecture, we carefully apply OpenACC's language constructs and mechanisms to implementing a parallel version of stochastic simulation algorithms on the GPU. Using our OpenACC implementation in comparison to both the NVidia CUDA and the CPU-based implementations, we report our initial experiences on OpenACC's performance and programming productivity in the context of GPU-accelerated scientific computing.