The fifth generation mobile communication system (5G) is designed to have new radio capabilities to support not only conventional enhanced Mobile Broadband (eMBB) communications but also new machine type communications such as Ultra-Reliable Low-Latency communications (URLLC) and massive Machine Type communications (m-MTC). In such new areas of URLLC and m-MTC, mobile operators need to explore new use cases and/or applications together with vertical industries, the industries which are potential users of 5G, in order to fully exploit the new 5G capabilities. Intelligent Transport System (ITS), including automated driving, is one of the most promising application areas of 5G since it requires both ultra-reliable and low-latency communications. We are actively working on the research and development of truck platooning as a new 5G application. We have developed a field trial system for vehicular-to-network (V2N) communications using 5G prototype equipment and actual large-size trucks in order to assess 5G capabilities, including ultra-low-latency, in automotive test courses in the field. This paper discusses the fundamental performance evaluation required for vehicular communications between platooning trucks, such as low-latency message communication for vehicle control and low-latency video monitoring of following platooning truck vehicles. The paper also addresses the field evaluation results of 5G V2N communications in a rural area. It clarifies the fundamental radio propagation issues at the leading and the following vehicles in truck platooning for V2N communications, and discusses the impact of the radio propagation over a road to the over-the-air transmission performance of 5G V2N communications.

In fifth-generation mobile communications systems (5G), grant-free non-orthogonal multiple access (NOMA) schemes have been considered as a way to accommodate the many wireless connections required for Internet of Things (IoT) devices. In NOMA schemes, both system capacity enhancement and transmission protocol simplification are achieved, and an overload test of more than one hundred percent of the transmission samples over conducted. Multi-user shared multiple access (MUSA) has been proposed as a representative scheme for NOMA. However, the performance of MUSA has not been fully analyzed nor compared to other NOMA or orthogonal multiple access schemes. Therefore, in this study, we theoretically and numerically analyze the performance of MUSA in uplink fading environments and compare it with orthogonal frequency division multiple access (OFDMA), space division multiple access-based OFDMA, low-density signature, and sparse code multiple access. The characteristics and superiority of MUSA are then clarified.

This paper proposes a computationally efficient offline semi-supervised algorithm that yields a more accurate prediction than the label propagation algorithm, which is commonly used in online graph-based semi-supervised learning (SSL). Our proposed method is an offline method that is intended to assist online graph-based SSL algorithms. The efficacy of the tool in creating new learning algorithms of this type is demonstrated in numerical experiments.

This paper evaluates a variety of key 5G technologies such as base station (BS) massive multiple-input multiple-output (MIMO) antennas, beamforming and tracking, intra-baseband unit (BBU) hand over (HO), and coverage. This is done in different interesting 5G areas with a variety of radio conditions such as an indoor office building lobby, an outdoor parking area, and a realistic urban deployment of a 5G radio access system with BSs installed in buildings to deploy a 5G trial area in the Tokyo Odaiba waterfront area. Experimental results show that throughput exceeding 10Gbps is achieved in a 730MHz bandwidth using 8 component carriers, and distributed MIMO throughput gain is achieved in various transmission point deployments in the indoor office building lobby and outdoor parking area using two radio units (RUs). In particular, in the outdoor parking area, a distinct advantage from distributed MIMO is expected and the distributed MIMO gain in throughput of 60% is achieved. The experimental results also clarify the downlink performance in an urban deployment. The experimental results show that throughput exceeding 1.5Gbps is achieved in the area and approximately 200 Mbps is achieved at 500m away from the BS. We also confirm that the beam tracking and intra-BBU HO work well compensating for high path loss at 28-GHz, and achieve coverage 500m from the BS. On the other hand, line of sight (LoS) and non-line-of sight (N-LoS) conditions are critical to 5G performance in the 28-GHz band, and we observe that 5G connections are sometimes dropped behind trees, buildings, and under footbridges.

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.

This paper describes the results of outdoor mobility measurements and high-speed vehicle tests that clarify the 4-by-8 multiple-input multiple-output (MIMO) throughput performance when applying distributed MIMO with narrow antenna-beam tracking in a 28-GHz frequency band in the downlink of a 5G cellular radio access system. To clarify suitable transmission point (TP) deployment for mobile stations (MS) moving at high speed, we examine two arrangements for 3TPs. The first sets all TPs in a line along the same side of the path traversed by the MS, and the other sets one TP on the other side of the path. The experiments in which the MS is installed on a moving wagon reveal that the latter deployment case enables a high peak data rate and high average throughput performance exhibiting the peak throughput of 15Gbps at the vehicle speed of 3km/h. Setting the MS in a vehicle travelling at 30km/h yielded the peak throughput of 13Gbps. The peak throughput of 11Gbps is achieved at the vehicle speed of 100km/h, and beam tracking and intra-baseband unit hand over operation are successfully demonstrated even at this high vehicle speed.

Due to progressing process technology, yield of chips is reduced by timing violation caused by delay variation of gates and wires in fabrication. Recently, post-silicon delay tuning, which inserts programmable delay elements (PDEs) into clock trees before the fabrication and adjusts the delays of the PDEs to recover the timing violation after the fabrication, is promising to improve the yield. Although post-silicon delay tuning improves the yield, it increases circuit area and power consumption since the PDEs are inserted. In this paper, a PDE structure is taken into consideration to reduce the circuit area and the power consumption. Moreover, a delay selection algorithm, and a clustering method, in which some PDEs are merged into a PDE and the PDE is inserted for multiple registers, are proposed to reduce the circuit area and the power consumption. In computational experiments, the proposed method reduced the circuit area and the power consumption in comparison with an existing method.

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.

VLSIs that perform signal processing near infrared sensors cooled to ultra-low temperature are demanded. Delay test of those chips must be executed at ultra-low temperature while functional test could be performed at room temperature as long as hold timing errors do not occur. In this letter, we focus on the hold timing violation and evaluate the feasibility of functional test of ultra-low temperature circuits at room temperature. Experimental evaluation with a case study shows that the functional test at room temperature is possible.

The symbol flipping decoding algorithms based on prediction (SFDP) for non-binary LDPC codes perform well in terms of error performances but converge slowly when compared to other symbol flipping decoding algorithms. In order to improve the convergence rate, we design new flipping rules with two phases for the SFDP algorithms. In the first phase, two or more symbols are flipped at each iteration to allow a quick increase of the objective function. While in the second phase, only one symbol is flipped to avoid the oscillation of the decoder when the objective function is close to its maximum. Simulation results show that the SFDP algorithms with the proposed flipping rules can reduce the average number of iterations significantly, whereas having similar performances when compared to the original SFDP algorithms.

In secret sharing schemes for general access structures, an important issue is the number of shares distributed to each participant. However, in general, the existing schemes are impractical in this respect when the size of the access structure is very large. In 2015, a secret sharing scheme that can reduce the number of shares distributed to specified participants was proposed (the scheme A of T15). In this scheme, we can select a subset of participants and reduce the number of shares distributed to any participant who belongs to the selected subset though this scheme cannot reduce the number of shares distributed to every participant. In other words, this scheme cannot reduce the number of shares distributed to each participant who does not belong to the selected subset. In this paper, we modify the scheme A of T15 and propose a new secret sharing scheme realizing general access structures. The proposed scheme can reduce the number of shares distributed to each participant who does not belong to the selected subset as well. That is, the proposed scheme is more efficient than the scheme A of T15.

A high-rate coding scheme that polar codes are concatenated with low density generator matrix (LDGM) codes is proposed in this paper. The scheme, referred to as polar-LDGM (PLG) codes, can boost the convergence speed of polar codes and eliminate the error floor behavior of LDGM codes significantly, while retaining the low encoding and decoding complexity. With a sensibly designed Gaussian approximation (GA), we can accurately predict the theoretical performance of PLG codes. The numerical results show that PLG codes have the potential to approach the capacity limit and avoid error floors effectively. Moreover, the encoding complexity is lower than the existing LDPC coded system. This motives the application of powerful PLG codes to satellite communications in which message transmission must be extremely reliable. Therefore, an adaptive relaying protocol (ARP) based on PLG codes for the relay satellite system is proposed. In ARP, the relay transmission is selectively switched to match the channel conditions, which are determined by an error detector. If no errors are detected, the relay satellite in cooperation with the source satellite only needs to forward a portion of the decoded message to the destination satellite. It is proved that the proposed scheme can remarkably improve the error probability performance. Simulation results illustrate the advantages of the proposed scheme

We have fabricated multiple-stacked Si quantum dots (QDs) with and without Ge core embedded in a SiO2 network on n-Si(100) and studied their field electron emission characteristics under DC bias application. For the case of pure Si-QD stacks with different dot-stack numbers, the average electric field in dot-stacked structures at which electron emission current appeared reached minimum value at a stack number of 11. This can be attributed to optimization of the electron emission due to enhanced electric field concentration in the upper layers of the dot-stacked structures and reduction of the electron injection current from the n-Si substrate, with an increased stack number. We also found that, by introducing Ge core into Si-QDs, the average electric field for the electron emission can be reduced below that from pure Si-QDs-stacked structures. This result implies that the electric field is more concentrated in the upper Si-QDs with Ge core layers due to deep potential well for holes in the Ge core.

In this paper, we propose a new dynamic load balancing scheme according to load threshold adjustment and incentives mechanism. The proposed scheme adjusts the load threshold of a node by comparing it with a mean threshold of adjacent nodes, thereby increasing the threshold evenly. We also assign the incentives and penalties to each node through a comparison of the mean threshold of all the nodes in order to increase autonomous load balancing participation.

This paper presents an ultra-low-power class-AB bulk-driven operational transconductance amplifier operating in the subthreshold region. Employing the partial positive feedback in current mirrors, the effective transconductance and output voltage swing are enhanced considerably without additional power consumption and layout area. Both traditional and proposed OTAs are designed and simulated for a 180 nm CMOS process. They dissipate an ultra low power of 192 nW. The proposed OTA features not only a DC gain enhancement of 14 dB but also a slew rate improvement of 200%. In addition, the improved gain leads to a 5.3 times wider unity-gain bandwidth than that of the traditional OTA.

To solve the low accuracy problem of the recommender system for long term users, in this paper, we propose a top-N-balanced sequential recommendation based on recurrent neural network. We postulated and verified that the interactions between users and items is time-dependent in the long term, but in the short term, it is time-independent. We balance the top-N recommendation and sequential recommendation to generate a better recommender list by improving the loss function and generation method. The experimental results demonstrate the effectiveness of our method. Compared with a state-of-the-art recommender algorithm, our method clearly improves the performance of the recommendation on hit rate. Besides the improvement of the basic performance, our method can also handle the cold start problem and supply new users with the same quality of service as the old users.

We propose a method for extracting multi-view images from a light field (plenoptic) camera that accurately handles the physical pixel arrangement of this camera. We use a Lytro Illum camera to obtain 4D light field data (a set of multi-viewpoint images) through a micro-lens array. The light field data are multiplexed on a single image sensor, and thus, the data is first demultiplexed into a set of multi-viewpoint (sub-aperture) images. However, the demultiplexing process usually includes interpolation of the original data such as demosaicing for a color filter array and pixel resampling for the hexagonal pixel arrangement of the original sub-aperture images. If this interpolation is performed, some information is added or lost to/from the original data. In contrast, we preserve the original data as faithfully as possible, and use them directly for the super resolution reconstruction, where the super-resolved image and the corresponding depth map are alternatively refined. We experimentally demonstrate the effectiveness of our method in resolution enhancement through comparisons with Light Field Toolbox and Lytro Desktop Application. Moreover, we also mention another type of light field cameras, a Raytrix camera, and describe how it can be handled to extract high-quality multi-view images.

A novel Nyquist Folding Receiver (NYFR) based passive localization algorithm with Sparse Bayesian Learning (SBL) is proposed to estimate the position of a spaceborne Synthetic Aperture Radar (SAR).Taking the geometry and kinematics of a satellite into consideration, this paper presents a surveillance geometry model, which formulates the localization problem into a sparse vector recovery problem. A NYFR technology is utilized to intercept the SAR signal. Then, a convergence algorithm with SBL is introduced to recover the sparse vector. Furthermore, simulation results demonstrate the availability and performance of our algorithm.

Blind nonlinear compensation for RF receivers is an important research topic in 5G mobile communication, in which higher level modulation schemes are employed more often to achieve high capacity and ultra-broadband services. Since nonlinear compensation circuits must handle intermodulation bandwidths that are more than three times the signal bandwidth, reducing the sampling frequency is essential for saving power consumption. This paper proposes a novel blind nonlinear compensation technique that employs sub-Nyquist sampling analog-to-digital conversion. Although outband distortion spectrum is folded in the proposed sub-Nyquist sampling technique, determination of compensator coefficients is still possible by using the distortion power. Proposed technique achieves almost same compensation performance in EVM as the conventional compensation scheme, while reducing sampling speed of analog to digital convertor (ADC) to less than half the normal sampling frequency. The proposed technique can be applied in concurrent dual-band communication systems and adapt to flat Rayleigh fading environments.

Quasi cyclic LDPC (QC-LDPC) codes consisting of circulant permutation matrices (CPM-QC-LDPC) are one of the most attractive types of LDPC codes due to their many advantages. In this paper, we mainly do some research on CPM-QC-LDPC codes. We first propose a two-stage decoding scheme mainly based on parity check matrix transform (MT), which can efficiently improve the bit error rate performance. To optimize the tradeoff between hardware implementation complexity and decoding performance, an improved method that combines our proposed MT scheme with the existing CPM-RID decoding scheme is presented. An experiment shows that both schemes can improve the bit error rate (BER) performance. Finally, we show that the MT decoding mechanism can be applied to other types of LDPC codes. We apply the MT scheme to random LDPC codes and show that it can efficiently lower the error floor.