By incorporating cloud computing capabilities to provide radio access functionalities, Cloud Radio Access Networks (CRANs) are considered to be a key enabling technology of future 5G and beyond communication systems. In CRANs, centralized radio resource allocation optimization is performed over a large number of small cells served by simple access points, the Remote Radio Heads (RRHs). However, the fronthaul links connecting each RRH to the cloud introduce delays and entail imperfect Channel State Information (CSI) knowledge at the cloud processors. In order to satisfy the stringent latency requirements envisioned for 5G applications, the concept of Fog Radio Access Networks (FogRANs) has recently emerged for providing cloud computing at the edge of the network. Although FogRAN may alleviate the latency and CSI quality issues of CRAN, its distributed nature degrades network interference mitigation and global system performance. Therefore, we investigate the design of tailored user pre-scheduling and beamforming for FogRANs. In particular, we propose a hybrid algorithm that exploits both the centralized feature of the cloud for globally-optimized pre-scheduling using imperfect global CSIs, and the distributed nature of FogRAN for accurate beamforming with high quality local CSIs. The centralized phase enables the interference patterns over the global network to be considered, while the distributed phase allows for latency reduction, in line with the requirements of FogRAN applications. Simulation results show that our proposed algorithm outperforms the baseline algorithm under imperfect CSIs, jointly in terms of throughput, energy efficiency, as well as delay.

This paper introduces recent trends in video streaming and four methods proposed by the authors for video streaming. Video traffic dominates the Internet as seen in current trends, and new visual contents such as UHD and 360-degree movies are being delivered. MPEG-DASH has become popular for adaptive video streaming, and machine learning techniques are being introduced in several parts of video streaming. Along with these research trends, the authors also tried four methods: route navigation, throughput prediction, image quality assessment, and perceptual video streaming. These methods contribute to improving QoS/QoE performance and reducing power consumption and storage size.

Controller area network (CAN) has been widely adopted as an in-vehicle communications standard. CAN with flexible data-rate (CAN FD) is defined in the ISO standards to achieve higher data rates than the legacy CAN. A number of CAN nodes can be connected by a single transmission medium, i.e. CAN enables us to constitute cost-effective bus-topology networks. CAN puts carrier sense multiple access with collision resolution (CSMA/CR) into practice by using bit-wise arbitration based on wired logical AND in the physical layer. The most prioritized message is delivered without interruption if two or more CAN nodes transmit messages at the same time due to the bit-wise arbitration. However, the scalability of CAN networks suffers from ringing caused by the signaling mechanism establishing the wired logical AND. We need to reduce networking material in a car in order to reduce the car weight, save the fuel and the cost, and develop a sustainable society by establishing more scalable CAN networks. In this paper, we show a reduced wiring technology for CAN to enhance the network scalability and the cost efficiency.

This paper reviews access system standardization activities and related technologies from the viewpoints of optical-based PON access, mobile access systems including LPWAN, and access network virtualization. Future study issues for the next access systems are also presented.

This paper introduces a method that identifies human activity from the height and Doppler Radar Cross Section (RCS) information detected by Multiple-Input Multiple-Output (MIMO) radar. This method estimates the three-dimensional target location by applying the MUltiple SIgnal Classification (MUSIC) method to the observed MIMO channel; the Doppler RCS is calculated from the signal reflected from the target. A gesture recognition algorithm is applied to the trajectory of the temporal transition of the estimated human height and the Doppler RCS. In experiments, the proposed method achieves over 90% recognition rate (average).

Recently, ZigBee has been attracting attention as a low-power and short-range wireless communication standard. In ZigBee networks, it is necessary to suppress frame transfer load because ZigBee needs to operate within severe capacity constraints and with low power consumption. However, in the typical environments in which ZigBee is used, such as smart home networks, WLAN (Wireless LAN) generally coexists, and radio interference occurs between the two networks. Existing studies focused on only interference avoidance. On the other hand, in this paper, we focus on adaptive cooperation between ZigBee network and WLAN. Specifically, from the viewpoints of WLANs that have wider communication range but have many idle periods in some environments like homes, we propose and study a hop count reduction method of ZigBee frame transfer by partially employing WLAN communication to transfer ZigBee frames. To the best of our knowledge, this is the first paper that considers the adaptive cooperation between ZigBee network and WLAN, where some ZigBee frames are transferred via WLAN to the sink. This is a completely new approach different from existing interference avoidance approaches. Then, we evaluate the hop count reduction by considering the number and the positions of relay points to transfer ZigBee frames to WLAN, and ZigBee tree topology for frame transfer routes. Through the evaluation, two realistic deployment policies of the relay points are derived. Finally, as specific advantages from the hop count reduction, we demonstrate the performance improvement about sink arrival ratio and end-to-end transfer delay of ZigBee frames, and energy consumption.

360-degree video delivery in Virtual Reality is very challenging due to the fact that 360-degree videos require much higher bandwidth than conventional videos. To overcome this problem, viewport-adaptive streaming has been introduced. In this study, we propose a new adaptation method for tiling-based viewport-adaptive streaming of 360-degree videos. For content preparation, the Cubemap projection format is used, where faces or parts of a face are encoded as tiles. Also, the problem is formulated as an optimization problem, in which each visible tile is weighted based on how that tile overlaps with the viewport. To solve the problem, an approximation algorithm is proposed in this study. An evaluation of the proposed method and reference methods is carried out under different tiling schemes and bandwidths. Experiments show that the Cubemap format with tiling provides a lot of benefits in terms of storage, viewport quality across different viewing directions and bandwidths, and tolerance to prediction errors.

This paper proposed an iterative soft interference canceller (IC) referred to as turbo equalizer for the self-coherent detection, and extrinsic information transfer (EXIT) chart based irregular low density parity check (LDPC) code optimization for the turbo equalizer in optical fiber short-reach transmissions. The self-coherent detection system is capable of linear demodulation by a single photodiode receiver. However, the self-coherent detection suffers from the interference induced by signal-signal beat components, and the suppression of the interference is a vital goal of self-coherent detection. For improving the error-free signal detection performance of the self-coherent detection, we proposed an iterative soft IC with the aid of forward error correction (FEC) decoder. Furthermore, typical FEC code is no longer appropriate for the iterative detection of the turbo equalizer. Therefore, we designed an appropriate LDPC code by using EXIT chart aided code design. The validity of the proposed turbo equalizer with the appropriate LDPC is confirmed by computer simulations.

In this paper, we propose a novel group formation scheme which is integrated with an EMGC protocol in order to cope with dynamic group change. It uses a link expiration time and residual energy to form a stable link in a group. It also has a group merging procedure to decrease the number of groups. Furthermore, we develop two additional functions for the protocol, i.e., GL rotation and a stay connection procedure to diminish energy consumption of sensor nodes in the network. Simulation results show that the proposed protocol outperforms MBC, EMGCwoh, and EMGC protocols in terms of data delivery, network lifetime, and energy dissipation per round with various group change probabilities and percentages of groups.

In December 2018, satellite broadcasting for 4K/8K ultra-high-definition television (UHDTV) will begin in Japan. It will be provided in the 12-GHz (11.7 to 12.75GHz) band with right- and left-hand circular polarizations. BSAT-4a, a satellite used for broadcasting UHDTV, was successfully launched in September 2017. This satellite has not only 12-GHz-band right- and left-hand circular polarization transponders but also a 21-GHz-band experimental transponder. The 21-GHz (21.4 to 22.0GHz) band has been allocated as the downlink for broadcasting satellite service in ITU-R Regions 1 (Europe, Africa) and 3 (Asia Pacific). To receive services provided over these two frequency bands and with dual-polarization, we implement and evaluated a dual-band and dual-circularly polarized parabolic reflector antenna fed by 12- and 21-GHz-band microstrip antenna arrays with a multilayer structure. The antenna is used to receive 12- and 21-GHz-band signals from in-orbit satellites. The measured and experimental results prove that the proposed antenna performs as a dual-polarized antenna in those two frequency bands and has sufficient performance to receive satellite broadcasts.

Spectrum sensing is a fundamental requirement for cognitive radio, and it is a challenging problem in impulsive noise modeled by symmetric alpha-stable (SαS) distributions. The Gaussian kernelized energy detector (GKED) performs better than the conventional detectors in SαS distributed noise. However, it fails to detect the DC signal and has high computational complexity. To solve these problems, this paper proposes a more efficient and robust detector based on a Gaussian function (GF). The analytical expressions of the detection and false alarm probabilities are derived and the best parameter for the statistic is calculated. Theoretical analysis and simulation results show that the proposed GF detector has much lower computational complexity than the GKED method, and it can successfully detect the DC signal. In addition, the GF detector performs better than the conventional counterparts including the GKED detector in SαS distributed noise with different characteristic exponents. Finally, we discuss the reason why the GF detector outperforms the conventional counterparts.

This paper presents a conifer and broad-leaf tree classification scheme that processes high resolution polarimetric synthetic aperture data above X-band. To validate the proposal, fully polarimetric measurements are conducted in a precisely controlled environment to examine the difference between the scattering mechanisms of conifer and broad-leaf trees at 15GHz. With 3.75cm range resolution, scattering matrices of two tree types were measured by a vector network analyzer. Polarimetric analyses using the 4-component scattering power decomposition and alpha-bar angle of eigenvalue decomposition yielded clear distinction between the two tree types. This scheme was also applied to an X-band Pi-SAR2 data set. The results confirm that it is possible to distinguish between tree types using fully polarimetric and high-resolution data above X-band.