Automated tongue segmentation plays a crucial role in the realm of computer-aided tongue diagnosis. The challenge lies in developing algorithms that achieve higher segmentation accuracy and maintain less memory space and swift inference capabilities. To relieve this issue, we propose a novel Pool-unet integrating Pool-former and Multi-task mask learning for tongue image segmentation. First of all, we collected 756 tongue images taken in various shooting environments and from different angles and accurately labeled the tongue under the guidance of a medical professional. Second, we propose the Pool-unet model, combining a hierarchical Pool-former module and a U-shaped symmetric encoder-decoder with skip-connections, which utilizes a patch expanding layer for up-sampling and a patch embedding layer for down-sampling to maintain spatial resolution, to effectively capture global and local information using fewer parameters and faster inference. Finally, a Multi-task mask learning strategy is designed, which improves the generalization and anti-interference ability of the model through the Multi-task pre-training and self-supervised fine-tuning stages. Experimental results on the tongue dataset show that compared to the state-of-the-art method (OET-NET), our method has 25% fewer model parameters, achieves 22% faster inference times, and exhibits 0.91% and 0.55% improvements in Mean Intersection Over Union (MIOU), and Mean Pixel Accuracy (MPA), respectively.

With the emphasis on personal information privacy protection in wireless communications, the new dimension low-interception covert transmission technology represented by the vortex wave with Orbital Angular Momentum (OAM) has received attention from both academia and industry. However, the current OAM low-interception transmission techniques all assume that the eavesdropper can only receive plane wave signals, which is a very ideal situation. Once the eavesdropper is configured with an OAM sensor, the so-called mode covert channel will be completely exposed. To solve this problem, this paper proposes a vortex microwave photon low-interception transmission method. The proposed method utilizes the differential operation between plane and vortex microwave photons signals to construct the covert differential channel, which can hide the user data in the mode domain. Compared with the traditional spread spectrum transmission, our proposed covert differential channel schemes need less transmitted power to achieve reliable transmission, which means less possibility of being intercepted by the eavesdropper.

To address the challenge of target signals being completely submerged by ionospheric clutter during typhoon passages, this letter proposes a chaotic detection method for target signals in the background of ionospheric noise under typhoon excitation. Experimental results demonstrate the effectiveness of the proposed method in detecting target signals with harmonic characteristics from strong ionospheric clutter during typhoon passages.

In this letter, we propose a method to introduce tabu search into Edge Assembly Crossover (EAX), which is an effective crossover method in solving the traveling salesman problem (TSP) using genetic algorithms. The proposed method, called EAX-tabu, archives the edges that have been exchanged over the past few generations into the tabu list for each individual and excludes them from the candidate edges to be exchanged when generating offspring by the crossover, thereby increasing the diversity of edges in the offspring. The effectiveness of the proposed method is demonstrated through numerical experiments on medium-sized instances of TSPLIB and VLSI TSP.

To fully exploit the attribute information in graphs and dynamically fuse the features from different modalities, this letter proposes the Attributed Graph Clustering Network with Adaptive Feature Fusion (AGC-AFF) for graph clustering, where an Attribute Reconstruction Graph Autoencoder (ARGAE) with masking operation learns to reconstruct the node attributes and adjacency matrix simultaneously, and an Adaptive Feature Fusion (AFF) mechanism dynamically fuses the features from different modules based on node attention. Extensive experiments on various benchmark datasets demonstrate the effectiveness of the proposed method.

Recently, trace representation of a class of balanced quaternary sequences of period p from the classical cyclotomic classes was given by Yang et al. (Cryptogr. Commun.,15 (2023): 921-940). In this letter, based on the generalized cyclotomic classes, we define a class of balanced quaternary sequences of period pn, where p = ef + 1 is an odd prime number and satisfies e ≡ 0 (mod 4). Furthermore, we calculate the defining polynomial of these sequences and obtain the formula for determining their trace representations over ℤ4, by which the linear complexity of these sequences over ℤ4 can be determined.

Using deep learning (DL) to achieve direction-of-arrival (DOA) estimation is an open and meaningful exploration. Existing DL-based methods achieve DOA estimation by spectrum regression or multi-label classification task. While, both of them face the problem of off-grid errors. In this paper, we proposed a cascaded deep neural network (DNN) framework named as off-grid network (OGNet) to provide accurate DOA estimation in the case of off-grid. The OGNet is composed of an autoencoder consisted by fully connected (FC) layers and a deep convolutional neural network (CNN) with 2-dimensional convolutional layers. In the proposed OGNet, the off-grid error is modeled into labels to achieve off-grid DOA estimation based on its sparsity. As compared to the state-of-the-art grid-based methods, the OGNet shows advantages in terms of precision and resolution. The effectiveness and superiority of the OGNet are demonstrated by extensive simulation experiments in different experimental conditions.

High altitude platform (HAP), known as line-of-sight dominated communications, effectively enhance the spectral efficiency of wireless networks. However, the line-of-sight links, particularly in urban areas, may be severely deteriorated due to the complex communication environment. The reconfigurable intelligent surface (RIS) is employed to establish the cascaded-link and improve the quality of communication service by smartly reflecting the signals received from HAP to users without direct-link. Motivated by this, the joint precoding scheme for a novel RIS-aided beamspace HAP with non-orthogonal multiple access (HAP-NOMA) system is investigated to maximize the minimum user signal-to-leakage-plus-noise ratio (SLNR) by considering user fairness. Specifically, the SLNR is utilized as metric to design the joint precoding algorithm for a lower complexity, because the isolation between the precoding obtainment and power allocation can make the two parts be attained iteratively. To deal with the formulated non-convex problem, we first derive the statistical upper bound on SLNR based on the random matrix theory in large scale antenna array. Then, the closed-form expressions of power matrix and passive precoding matrix are given by introducing auxiliary variables based on the derived upper bound on SLNR. The proposed joint precoding only depends on the statistical channel state information (SCSI) instead of instantaneous channel state information (ICSI). NOMA serves multi-users simultaneously in the same group to compensate for the loss of spectral efficiency resulted from the beamspace HAP. Numerical results show the effectiveness of the derived statistical upper bound on SLNR and the performance enhancement of the proposed joint precoding algorithm.

In this paper, we investigate a method for clustering user equipment (UE)-specific transmission access points (APs) in downlink cell-free multiple-input multiple-output (MIMO) assuming that the APs distributed over the system coverage know only part of the instantaneous channel state information (CSI). As a beamforming (BF) method based on partial CSI, we use a layered partially non-orthogonal zero-forcing (ZF) method based on channel matrix muting, which is applicable to the case where different transmitting AP groups are selected for each UE under partial CSI conditions. We propose two AP clustering methods. Both proposed methods first tentatively determine the transmitting APs independently for each UE and then iteratively update the transmitting APs for each UE based on the estimated throughput considering the interference among the UEs. One of the two proposed methods introduces a UE cluster for each UE into the iterative updates of the transmitting APs to balance throughput performance and scalability. Computer simulations show that the proposed methods achieve higher geometric-mean and worst user throughput than those for the conventional methods.

We propose a novel peak-to-average power ratio (PAPR) reduction method based on a peak cancellation (PC) signal vector that considers the variance in the average signal power among transmitter antennas for massive multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) signals using the null space in a MIMO channel. First, we discuss the conditions under which the PC signal vector achieves a sufficient PAPR reduction effect after its projection onto the null space of the MIMO channel. The discussion reveals that the magnitude of the correlation between the PC signal vector before projection and the transmission signal vector should be as low as possible. Based on this observation and the fact that to reduce the PAPR it is helpful to suppress the variation in the transmission signal power among antennas, which may be enhanced by beamforming (BF), we propose a novel method for generating a PC signal vector. The proposed PC signal vector is designed so that the signal power levels of all the transmitter antennas are limited to be between the maximum and minimum power threshold levels at the target timing. The newly introduced feature in the proposed method, i.e., increasing the signal power to be above the minimum power threshold, contributes to suppressing the transmission signal power variance among antennas and to improving the PAPR reduction capability after projecting the PC signal onto the null space in the MIMO channel. This is because the proposed method decreases the magnitude of the correlation between the PC signal vectors before its projection and the transmission signal vectors. Based on computer simulation results, we show that the PAPR reduction performance of the proposed method is improved compared to that for the conventional method and the proposed method reduces the computational complexity compared to that for the conventional method for achieving the same target PAPR.

Low signal power and susceptibility to interference cause difficulties for traditional global navigation satellite system (GNSS) receivers in tracking weak signals. Extending coherent integration time is a common approach for enhancing signal gain. However, coherent integration time cannot be indefinitely increased owing to navigation bit sign transition, receiver dynamics, and clock noises. This study proposes a cross-correlation phase combining (CPC) algorithm suitable for distributed multi-antenna receivers to improve carrier-tracking performance in weak GNSS signal conditions. This algorithm cross-correlates each antenna’s intermediate frequency (IF) signal and local carrier to detect the phase differences. Subsequently, the IF signals are weighted to achieve phase alignment and coherently combined. The carrier-to-noise ratio (CNR) and carrier phase equation of the combined signal were derived for the CPC algorithm. Global positioning system (GPS) signals received by distributed antenna array with six elements were used to validate the performance of the algorithm. The results demonstrated that the CPC algorithm could effectively achieve signal phase alignment at 32 dB-Hz, resulting in a combined-signal CNR enhancement of 6 dB. The phase-tracking error variance was reduced by 72% at 30 dB-Hz compared with that of a single-antenna signal. The algorithm exhibited low phased array calibration requirements, overcoming the limitations associated with coherent integration time and effectively enhancing tracking performance in weak-signal environments.

An unmanned aerial vehicle (UAV) can be used for wireless communication and localization, among many other things. When terrestrial networks are either damaged or non-existent, and the area is GPS-denied, the UAV can be quickly deployed to provide communication and localization services to ground terminals in a specific target area. In this study, we propose an UAV operation model for unified communication and localization using reinforcement learning (UCL-RL) in a suburban environment which has no cellular communication and GPS connectivity. First, the UAV flies to the target area, moves in a circular fashion with a constant turning radius and sends navigation signals from different positions to the ground terminals. This provides a dynamic environment that includes the turning radius, the navigation signal transmission points, and the height of the unmanned aerial vehicle as well as the location of the ground terminals. The proposed model applies a reinforcement learning algorithm where the UAV continuously interacts with the environment and learns the optimal height that provides the best communication and localization services to the ground terminals. To evaluate the terminal position accuracy, position dilution of precision (PDOP) is measured, whereas the maximum allowable path loss (MAPL) is measured to evaluate the communication service. The simulation result shows that the proposed model improves the localization of the ground terminals while guaranteeing the communication service.

Nonradiative dielectric waveguide is a transmission medium for millimeter-wave integrated circuits, invented in Japan. This transmission line is characterized by low transmission loss and non-radiating nature in bends and discontinuities. It has been actively researched from 1980 to 2000, primarily at Tohoku University. This paper explains the fundamental characteristics, including passive and active circuits, and provides an overview of millimeter-wave systems such as gigabit-class ultra-high-speed data transmission applications and various radar applications. Furthermore, the performance in the THz frequency band, where future applications are anticipated, is also discussed.

There has been a growing interest in the application of radar technology to the monitoring of humans and animals and their positions, motions, activities, and vital signs. Radar can be used, for example, to remotely measure vital signs such as respiration and heartbeat without contact. Radar-based human sensing is expected to be adopted in a variety of fields, such as medicine, healthcare, and entertainment, but what can be realized by radar-based animal sensing? This paper reviews the latest research trends in the noncontact sensing of animals using radar systems. We also present examples of our past radar experiments for the respiratory measurement of monkeys and the heartbeat measurement of chimpanzees. The trends in this field are reviewed in terms of the target animal species, type of vital sign, and radar type and selection of frequencies.

Japan encounters an urgent issue of “Carbon Neutrality” as a member of the international world and is required to make the action plans to accomplish this issue, i.e., the zero emission of CO2 by 2050. Our world must change the industries to adapt to the electrification based on the renewable powers. Microwave chemistry is a candidate of electrification of industries for the carbon neutrality on the conditions of usage of renewable energy power generation. This invited paper shows an example of “Microwave Pidgeon process” for smelting magnesium in which heating with burning fossil coals can be replaced with microwave energy for discussing how microwave technology should be developed for that purpose from both the academic and industrial sides.

GaN solid state power amplifiers (SSPA) for wireless power transfer and microwave heating have been reviewed. For wireless power transfer, 9 W output power with 79% power added efficiency at 5.8 GHz has been achieved. For microwave heating, 450 W output power with 70% drain efficiency at 2.45 GHz has been achieved. Microwave power concentration and uniform microwave heating by phase control of multiple SSPAs are demonstrated.

This paper presents a comprehensive design approach to load-independent radio frequency (RF) power amplifiers. We project the zero-voltage-switching (ZVS) and zero-voltage-derivative-switching (ZVDS) load impedances onto a Smith chart, and find that their loci exhibit geodesic arcs. We exploit a two-port reactive network to convert the geodesic locus into another geodesic. This is named geodesic-to-geodesic (G2G) impedance conversion, and the power amplifier that employs G2G conversion is called class-G2G amplifier. We comprehensively explore the possible circuit topologies, and find that there are twenty G2G networks to create class-G2G amplifiers. We also find out that the class-G2G amplifier behaves like a transformer or a gyrator converting from dc to RF. The G2G design theory is verified via a circuit simulation. We also verified the theory through an experiment employing a prototype 100 W amplifier at 6.78 MHz. We conclude that the presented design approach is quite comprehensive and useful for the future development of high-efficiency RF power amplifiers.

This study introduces a novel single-diode rectenna, enhancing the rf-dc conversion efficiency using harmonic control of the antenna impedance. We employ source-pull simulations encompassing the fundamental frequency and the harmonics to achieve a highly efficient rectenna. The results of the source-pull simulations delineate the source-impedance ranges required for enhanced efficiency at each harmonic. Based on the source-pull simulation results, we designed two inverted-F antenna with input impedances within and without these identified source impedance ranges. Experimental results show that the proposed rectenna has a maximum rf-dc conversion efficiency of 75.9% at the fundamental frequency of 920 MHz, an input power of 10.8 dBm, and a load resistance of 1 kΩ, which is higher than that of the comparative rectenna without harmonic control of the antenna impedance. This study demonstrates that the proposed rectenna achieves high efficiency through the direct connection of the antenna and the single diode, along with harmonic control of the antenna impedance.

This paper proposes a novel configuration for a wideband single-carrier transmitter using a sub-terahertz frequency. For wideband single-carrier transmission over a bandwidth of several gigahertz, the frequency response non-flatness derived from transmitter components in an operating band seriously deteriorates the transmission quality due to inter-symbol interference. A promising approach to address this problem is equalizing the frequency response non-flatness at the transmitter. The proposed novel configuration has a feedback route for calculating the inverse frequency response and multiplying it with a transmission signal spectrum in the frequency domain. Moreover, we verify that employing the proposed transmitter configuration simplifies the receiver configuration by lowering the calculation complexity to minimize the inter-symbol interference to meet the signal-to-interference-and-noise ratio requirements. To confirm the feasibility of the proposed configuration, the transmission quality obtained using the proposed configuration is measured and evaluated. Experimental results confirm that the proposed configuration improves the error vector magnitude value to over 5 dB for a 10 Gbaud transmission and the transmission data rate of 25 Gbps.

We propose microwave heating via electromagnetic coupling using zeroth-order resonators (ZORs) to extend the uniform heating area. ZORs can generate resonant modes with a wavenumber of 0, which corresponds to an infinite guide wavelength. Under this condition, uniform heating is expected because the resulting standing waves would not have nodes or antinodes. In the design proposed in this paper, two ZORs fabricated on dielectric substrates are arranged to face each other for electromagnetic coupling, and a sample placed between the resonators is heated. A single ZOR was investigated using a 3D electromagnetic simulator, and the resonant frequency and electric field distribution of the simulated ZOR were confirmed to be in good agreement with those of the fabricated ZOR. Simulations of two ZORs facing each other were then conducted to evaluate the performance of the proposed system as a heating apparatus. It was found that a resonator spacing of 25 mm was suitable for uniform heating. Heating simulations of SiC and Al2O3 sheets were performed with the obtained structure. The heating uniformity was evaluated by the width L50% over which the power loss distribution exceeds half the maximum value. This evaluation index was equal to 0.397λ0 for SiC and 0.409λ0 for Al2O3, both of which exceed λ0/4, the distance between a neighboring node and antinode of a standing wave, where λ0 is the free-space wavelength. Therefore, the proposed heating apparatus is effective for uniform microwave heating. Because of the different electrical parameters of the heated materials, SiC can be easily heated, whereas Al2O3 heats little. Finally, heating experiments were performed on each of these materials. Good uniformity in temperature was obtained for both SiC and Al2O3 sheets.