6G research has been extensively conducted by individual organizations as well as pre-competitive joint research initiatives. One of the joint initiatives is the Hexa-X European 6G flagship project. This paper shares the up-to-date deliverables through which Hexa-X is envisioning the 6G era. The Hexa-X deliverables presented in this paper encompass the overall 6G vision, use cases and technical enablers. The latest deliverables on tenets of 6G architectural design and central pillars of technical enablers are presented. In conclusion, the authors encourage joint research and PoC collaboration with Japanese industry, academia and research initiatives for the potential technical enablers presented in this paper, aimed at global harmonization towards 6G standards.

Technology for sixth-generation (6G) mobile communication system is now being widely studied. A sub-Terahertz band is expected to play a great role in 6G to enable extremely high data-rate transmission. This paper has two goals. (1) Introduction of 6G concept and propagation characteristics of sub-Terahertz-band radio waves. (2) Performance evaluation of intelligent reflecting surfaces (IRSs) based on beamforming in a sub-Terahertz band for smart radio environments (SREs). We briefly review research on SREs with reconfigurable intelligent surfaces (RISs), and describe requirements and key features of 6G with a sub-Terahertz band. After that, we explain propagation characteristics of sub-Terahertz band radio waves. Important feature is that the number of multipath components is small in a sub-Terahertz band in indoor office environments. This leads to an IRS control method based on beamforming because the number of radio waves out of the optimum beam is very small and power that is not used for transmission from the IRS to user equipment (UE) is little in the environments. We use beams generated by a Butler matrix or a DFT matrix. In simulations, we compare the received power at a UE with that of the upper bound value. Simulation results show that the proposed method reveals good performance in the sense that the received power is not so lower than the upper bound value.

With the rapid increase in the amount of data communication in 5G networks, there is a strong demand to reduce the power of the entire network, so the use of highly power-efficient millimeter-wave (mm-wave) networks is being considered. However, while mm-wave communication has high power efficiency, it has strong straightness, so it is difficult to secure stable communication in an environment with blocking. Especially when considering use cases such as autonomous driving, continuous communication is required when transmitting streaming data such as moving images taken by vehicles, it is necessary to compensate the blocking problem. For this reason, the authors examined an optimum radio access technology (RAT) selection scheme which selects mm-wave communication when mm-wave can be used and select wide-area macro-communication when mm-wave may be blocked. In addition, the authors implemented the scheme on a prototype device and conducted field tests and confirmed that mm-wave communication and macro communication were switched at an appropriate timing.

This paper proposes a multiple code block transmission scheme using hierarchical modulation (HM) for a broadcast channel in the orthogonal frequency division multiplexing (OFDM) downlink. We investigate the average bit error rate (BER) performance of two-layer HM using 16 quadrature amplitude modulation (QAM) and three-layer HM using 64QAM in multipath Rayleigh fading channels. In multiple code block transmission using HM, the basic information bits are demodulated and decoded to all users within a cell that satisfy the bit error rate (BER) requirement. Hence, we investigate non-uniform QAM constellations to find one that suppresses the loss in the average BER of the basic information bits for HM to a low level compared to that using the original constellation in which only the basic information bits are transmitted while simultaneously minimizing the loss in the average BER of the secondary and tertiary information bits from the original constellations in which the information bits of the respective layers are transmitted alone. Based on the path loss equations in the Urban Macro and Rural Macro scenarios, we also investigate the maximum distance from a base station (BS) for the information bits of each layer to attain the required average received signal-to-noise power ratio (SNR) that achieves the average BER of 10-3.

We experimentally evaluated transmission characteristics of 120-GHz-band close-proximity wireless link that employs a split-ring resonator (SRR) millimeter-wave (MMW) absorber integrated on planar slot antennas in 120-GHz-band close-proximity wireless links. We fabricated the SRR MMW absorber made of a 0.28-μm-thick TaN film on a quartz substrate, and integrated it on planar single slot antennas. When the TaN SRRs are not integrated on the planar slot antennas, multiple reflections between the two antennas occur, and a >10-dB fluctuation of S21 at 100-140GHz is observed. When the TaN SRRs are integrated on the planar antennas, the fluctuation of S21 is suppressed to be 3.5dB at 100-140GHz. However, the transmittance of the close-proximity wireless link decreases by integrating TaN SRRs on the planar slot antenna because of reflection at the quartz substrate surface. The integration of the radiator that is composed of single SRR with two capacitors just above the slot antenna increased S21 by 3.5dB at 125GHz. We conducted a data transmission experiment over a close-proximity wireless link that employs radiator-and-TaN-SRR-integrated slot antennas for Tx and Rx, and succeeded to transmit 10-Gbit/s data over the close-proximity wireless link for the first time.

With the growing global demand for seafood, sustainable aquaculture is attracting more attention than conventional natural fishing, which causes overfishing and damage to the marine environment. However, a major problem facing the aquaculture industry is the cost of feeding, which accounts for about 60% of a fishing expenditure. Excessive feeding increases costs, and the accumulation of residual feed on the seabed negatively impacts the quality of water environments (e.g., causing red tides). Therefore, the importance of raising fishes efficiently with less food by optimizing the timing and quantity of feeding becomes more evident. Thus, we developed a system to quantitate the amount of fish activity for the optimal feeding time and feed quantity based on the images taken. For quantitation, optical flow that is a method for tracking individual objects was used. However, it is difficult to track individual fish and quantitate their activity in the presence of many fishes. Therefore, all fish in the filmed screen were considered as a single school and the amount of change in an entire screen was used as the amount of the school activity. We divided specifically the entire image into fixed regions and quantitated by vectorizing the amount of change in each region using optical flow. A vector represents the moving distance and direction. We used the numerical data of a histogram as the indicator for the amount of fish activity by dividing them into classes and recording the number of occurrences in each class. We verified the effectiveness of the indicator by quantitating the eating and not eating movements during feeding. We evaluated the performance of the quantified indicators by the support vector classification, which is a form of machine learning. We confirmed that the two activities can be correctly classified.

This paper first takes IoT as an example to provide the motivation for eliminating the single point of trust (SPOT) in a CA-based private PKI. It then describes a distributed public key certificate-issuing infrastructure that eliminates the SPOT and its limitation derived from generating signing keys. Finally, it proposes a method to address its limitation by all certificate issuers.

Aiming at the problem of low classification accuracy of surface defects of lithium battery pole pieces by traditional classification methods, an image classification algorithm for surface defects of lithium battery pole piece based on deep learning is proposed in this paper. Firstly, Wavelet Threshold and Histogram Equalization are used to preprocess the detect image to weaken influence of noise in non-defect regions and enhance defect features. Secondly, a VGG-InceptionV2 network with better performance is proposed by adding InceptionV2 structure to the improved VGG network structure. Then the original data set is expanded by rotating, flipping and contrast adjustment, and the optimal value of the model hyperparameters is determined by experiments. Finally, the model in this paper is compared with VGG16 and GoogLeNet to realize the recognition of defect types. The results show that the accuracy rate of the model in this paper for the surface pole piece defects of lithium batteries is 98.75%, and the model parameters is only 1.7M, which has certain significance for the classification of lithium battery surface pole piece defects in industry.

In human-computer interaction, acoustic scene classification (ASC) is one of the relevant research domains. In real life, the recorded audio may include a lot of noise and quiet clips, making it hard for earlier ASC-based research to isolate the crucial scene information in sound. Furthermore, scene information may be scattered across numerous audio frames; hence, selecting scene-related frames is crucial for ASC. In this context, an integrated convolutional neural network with a fusion attention mechanism (ICNN-FA) is proposed for ASC. Firstly, segmented mel-spectrograms as the input of ICNN can assist the model in learning the short-term time-frequency correlation information. Then, the designed ICNN model is employed to learn these segment-level features. In addition, the proposed global attention layer may gather global information by integrating these segment features. Finally, the developed fusion attention layer is utilized to fuse all segment-level features while the classifier classifies various situations. Experimental findings using ASC datasets from DCASE 2018 and 2019 indicate the efficacy of the suggested method.

With the recent commercialization of fifth-generation mobile communication systems (5G), wireless communications are being used in various fields. Accordingly, the number of situations in which sensitive information, such as personal data is handled in wireless communications is increasing, and so is the demand for confidentiality. To meet this demand, we proposed a chaos-based radio-encryption modulation that combines physical layer confidentiality and channel coding effects, and we have demonstrated its effectiveness through computer simulations. However, there are no demonstrations of performances using real signals. In this study, we constructed a transmission system using Universal Software Radio Peripheral, a type of software-defined radio, and its control software LabVIEW. We conducted wired transmission experiments for the practical use of radio-frequency encrypted modulation. The results showed that a gain of 0.45dB at a bit error rate of 10-3 was obtained for binary phase-shift keying, which has the same transmission efficiency as the proposed method under an additive white Gaussian noise channel. Similarly, a gain of 10dB was obtained under fading conditions. We also evaluated the security ability and demonstrated that chaos modulation has both information-theoretic security and computational security.

The design and adjustment of the divergence in audio applications using nonnegative matrix factorization (NMF) is still open problem. In this study, to deal with this problem, we explore a representation of the divergence using neural networks (NNs). Instead of the divergence, our approach extends the multiplicative update algorithm (MUA), which estimates the NMF parameters, using NNs. The design of the extended MUA incorporates NNs, and the new algorithm is referred to as the deep MUA (DeMUA) for NMF. While the DeMUA represents the algorithm for the NMF, interestingly, the divergence is obtained from the incorporated NN. In addition, we propose theoretical guides to design the incorporated NN such that it can be interpreted as a divergence. By appropriately designing the NN, MUAs based on existing divergences with a single hyper-parameter can be represented by the DeMUA. To train the DeMUA, we applied it to audio denoising and supervised signal separation. Our experimental results show that the proposed architecture can learn the MUA and the divergences in sparse denoising and speech separation tasks and that the MUA based on generalized divergences with multiple parameters shows favorable performances on these tasks.

Visible light communication (VLC) and visible light ranging are applicable techniques for intelligent transportation systems (ITS). They use every unique light-emitting diode (LED) on roads for data transmission and range estimation. The simultaneous VLC and ranging can be applied to improve the performance of both. It is necessary to achieve rapid data rate and high-accuracy ranging when transmitting VLC data and estimating the range simultaneously. We use the signal modulation method of pulse-width modulation (PWM) to increase the data rate. However, when using PWM for VLC data transmission, images of the LED transmitters are captured at different luminance levels and are easily saturated, and LED saturation leads to inaccurate range estimation. In this paper, we establish a novel simultaneous visible light communication and ranging system for ITS using PWM. Here, we analyze the LED saturation problems and apply bicubic interpolation to solve the LED saturation problem and thus, improve the communication and ranging performance. Simultaneous communication and ranging are enabled using a stereo camera. Communication is realized using maximal-ratio combining (MRC) while ranging is achieved using phase-only correlation (POC) and sinc function approximation. Furthermore, we measured the performance of our proposed system using a field trial experiment. The results show that error-free performance can be achieved up to a communication distance of 55 m and the range estimation errors are below 0.5m within 60m.

We have developed and evaluated a prototype micro-pump for a new form of medication that is driven by a chemical reaction. The chemical reaction between citric acid and sodium bicarbonate produces carbon dioxide, the pressure of which pushes the medication out. This micropump is smaller in size than conventional diaphragm-type micropumps and is suitable for swallowing.

In the massive machine-type communication scenario, aiming at the problems of active user detection and channel estimation in the grant-free non-orthogonal multiple access (NOMA) system, new sets of non-orthogonal spreading sequences are proposed by using the zero/low correlation zone sequence set with low correlation among multiple sets. The simulation results show that the resulting sequence set has low coherence, which presents reliable performance for channel estimation and active user detection based on compressed sensing. Compared with the traditional Zadoff-Chu (ZC) sequences, the new non-orthogonal spreading sequences have more flexible lengths, and lower peak-to-average power ratio (PAPR) and smaller alphabet size. Consequently, these sequences will effectively solve the problem of high PAPR of time domain signals and are more suitable for low-cost devices in massive machine-type communication.

In this paper, we present a novel discriminative dictionary learning (DDL) method for image classification. The local structural relationship between samples is first built by the Laplacian eigenmaps (LE), and then integrated into the basic DDL frame to suppress inter-class ambiguity in the feature space. Moreover, in order to improve the discriminative ability of the dictionary, the category label information of training samples is formulated into the objective function of dictionary learning by considering the discriminative promotion term. Thus, the data points of original samples are transformed into a new feature space, in which the points from different categories are expected to be far apart. The test results based on the real dataset indicate the effectiveness of this method.

In this paper, we propose a heuristic planning method to efficiently accommodate dynamic multilayer path (MLP) demand in multilayer networks consisting of a Time Division Multiplexing (TDM) layer and a Wavelength Division Multiplexing (WDM) layer; the goal is to achieve the flexible accommodation of increasing capacity and diversifying path demands. In addition to the grooming of links at the TDM layer and the route and frequency slots for the elastic optical path to be established, MLP requires the selection of an appropriate operational mode, consisting of a combination of modulation formats and symbol rates supported by digital coherent transceivers. Our proposed MLP planning method defines a planning policy for each of these parameters and embeds the values calculated by combining these policies in an auxiliary graph, which allows the planning parameters to be calculated for MLP demand requirements in a single step. Simulations reveal that the choice of operational mode significantly reduces the blocking probability and demonstrate that the edge weights in the auxiliary graph allow MLP planning with characteristics tailored to MLP demand and network requirements. Furthermore, we quantitatively evaluate the impact of each planning policy on the MLP planning results.

In this study, vertically aligned carbon nanotubes (VA-CNTs) were grown from filler-added LB films with accumulated AlFe2O4 nanoparticles and palmitic acid (C16) as the filler molecule after different hydrogen reduction temperatures of 500°C and 750°C, and the grown VA-CNTs were compared and evaluated. As a result, VA-CNTs were approximately doubled in length after 500°C hydrogen reduction compared to 750°C hydrogen reduction when AlFe2O4 NPs were used. On the other hand, when the catalyst area ratio was decreased by using palmitic acid, i.e., the distance between CNTs was increased, VA-CNTs rapidly shortened after 500°C hydrogen reduction, and VA-CNTs were no longer obtained even in the range where VA-CNTs were obtained in 750°C hydrogen reduction. The inner and outer diameters of VA-CNTs decreased with decreasing catalyst area ratio at 750°C hydrogen reduction and tended to increase at 500°C hydrogen reduction. The morphology of the catalyst nanoparticles after CVD was observed to change significantly depending on the hydrogen reduction temperature and catalyst area ratio. These observations indicate that the state of the catalyst nanoparticles immediately before the CNT growth process greatly affects the physical properties of the CNTs.

We investigated the photochemical stability of an electro-optic (EO) polymer under laser irradiation at 1310nm to reveal photodegradation mechanisms. It was found that one-photon absorption excitation assisted with the thermal energy at the temperature is involved in the photodegradation process, in contrast to our previous studies at a wavelength of 1550nm where two-photon absorption excitation is involved in the photodegradation process. Thus, both the excitation wavelength and the thermal energy strongly affect to the degradation mechanism. In any cases, the photodegradation of EO polymers is mainly related to the generation of exited singlet oxygen.

Incorporating a tool for administering medication, such as a syringe, is required in microneedles (MNs) for medical use. This renders it easier for non-medical personnel to administer medication. Because it is difficult to fabricate a hollow MN, we fabricated a capillary groove on an MN and its substrate to enable the administration of a higher dosage. MN grooving is difficult to accomplish via the conventional injection molding method used for polylactic acid. Therefore, biodegradable polyacid anhydride was selected as the material for the MN. Because polyacid anhydride is a low-viscosity liquid at room temperature, an MN can be grooved using a processing method similar to vacuum casting. This study investigated the performance of the capillary force of the MN and the optimum shape and size of the MN by a puncture test.

Studies on intrinsic Josephson junctions (IJJs) of cuprate superconductors are reviewed. A system consisting of a few IJJs provides phenomena to test the Josephson phase dynamics and its interaction between adjacent IJJs within a nanometer scale, which is unique to cuprate superconductors. Quasiparticle density of states, which provides direct information on the Cooper-pair formation, is also revealed in the system. In contrast, Josephson plasma emission, which is an electromagnetic wave radiation in the sub-terahertz frequency range from an IJJ stack, arises from the synchronous phase dynamics of hundreds of IJJs coupled globally. This review summarizes a wide range of physical phenomena in IJJ systems having capacitive and inductive couplings with different nanometer and micrometer length scales, respectively.