The novel optical path routing architecture named flexible waveband routing networks is reviewed in this paper. The nodes adopt a two-stage path routing scheme where wavelength selective switches (WSSs) bundle optical paths and form a small number of path groups and then optical switches without wavelength selectivity route these groups to desired outputs. Substantial hardware scale reduction can be achieved as the scheme enables us to use small scale WSSs, and even more, share a WSS by multiple input cores/fibers through the use of spatially-joint-switching. Furthermore, path groups distributed over multiple bands can be switched by these optical switches and thus the adaptation to multi-band transmission is straightforward. Network-wide numerical simulations and transmission experiments that assume multi-band transmission demonstrate the validity of flexible waveband routing.

Transcatheter renal denervation (RDN) is a novel treatment to reduce blood pressure in patients with resistant hypertension using an energy-based catheter, mostly radio frequency (RF) current, by eliminating renal sympathetic nerve. However, several inconsistent RDN treatments were reported, mainly due to RF current narrow heating area, and the inability to confirm a successful nerve ablation in a deep area. We proposed microwave energy as an alternative for creating a wider ablation area. However, confirming a successful ablation is still a problem. In this paper, we designed a prediction method for deep renal nerve ablation sites using hybrid numerical calculation-driven machine learning (ML) in combination with a microwave catheter. This work is a first-step investigation to check the hybrid ML prediction capability in a real-world situation. A catheter with a single-slot coaxial antenna at 2.45 GHz with a balloon catheter, combined with a thin thermometer probe on the balloon surface, is proposed. Lumen temperature measured by the probe is used as an ML input to predict the temperature rise at the ablation site. Heating experiments using 6 and 8 mm hole phantom with a 41.3 W excited power, and 8 mm with 36.4 W excited power, were done eight times each to check the feasibility and accuracy of the ML algorithm. In addition, the temperature on the ablation site is measured for reference. Prediction by ML algorithm agrees well with the reference, with a maximum difference of 6°C and 3°C in 6 and 8 mm (both power), respectively. Overall, the proposed ML algorithm is capable of predicting the ablation site temperature rise with high accuracy.

Quantum key distribution or secret key distribution (SKD) has been studied to deliver a secrete key for secure communications, whose security is physically guaranteed. For practical deployment, such systems are desired to be overlaid onto existing wavelength-multiplexing transmission systems, without using a dedicated transmission line. This study analytically investigates the feasibility of the intensity-modulation/direction-detection (IM/DD) SKD scheme being wavelength-multiplexed with conventional wavelength-division-multiplexed (WDM) signals, concerning spontaneous Raman scattering light from conventional optical signals. Simulation results indicate that IM/DD SKD systems are not degraded when they are overlaid onto practically deployed dense WDM transmission systems in the C-band, owing to the feature of the IM/DD SKD scheme, which uses a signal light with an intensity level comparable to conventional optical signals unlike conventional quantum key distribution schemes.

This paper introduces heuristic approaches and a deep reinforcement learning approach to solve a joint virtual network function deployment and scheduling problem in a dynamic scenario. We formulate the problem as an optimization problem. Based on the mathematical description of the optimization problem, we introduce three heuristic approaches and a deep reinforcement learning approach to solve the problem. We define an objective to maximize the ratio of delay-satisfied requests while minimizing the average resource cost for a dynamic scenario. Our introduced two greedy approaches are named finish time greedy and computational resource greedy, respectively. In the finish time greedy approach, we make each request be finished as soon as possible despite its resource cost; in the computational resource greedy approach, we make each request occupy as few resources as possible despite its finish time. Our introduced simulated annealing approach generates feasible solutions randomly and converges to an approximate solution. In our learning-based approach, neural networks are trained to make decisions. We use a simulated environment to evaluate the performances of our introduced approaches. Numerical results show that the introduced deep reinforcement learning approach has the best performance in terms of benefit in our examined cases.

In this paper, we investigate a wireless-powered relays assisted batteryless IoT network based on the non-linear energy harvesting model, where there exists an energy service provider constituted by the hybrid access point (HAP) and an IoT service provider constituted by multiple clusters. The HAP provides energy signals to the batteryless devices for information backscattering and the wireless-powered relays for energy harvesting. The relays are deployed to assist the batteryless devices with the information transmission to the HAP by using the harvested energy. To model the energy interactions between the energy service provider and IoT service provider, we propose a Stackelberg game based framework. We aim to maximize the respective utility values of the two providers. Since the utility maximization problem of the IoT service provider is non-convex, we employ the fractional programming theory and propose a block coordinate descent (BCD) based algorithm with successive convex approximation (SCA) and semi-definite relaxation (SDR) techniques to solve it. Numerical simulation results confirm that compared to the benchmark schemes, our proposed scheme can achieve larger utility values for both the energy service provider and IoT service provider.

Physical contact (PC) optical connectors realize long-term stability by maintaining contact with the optical fiber even during temperature fluctuations caused by the microscopic displacement of the ferrule endface. With multicore fiber (MCF) connectors, stable PC connection conditions need to be newly investigated because MCFs have cores other than at the center. In this work, we investigated the microscopic displacement of connected ferrule endfaces using the finite element method (FEM). As a result, by using MCF connectors with an apex offset, we found that the allowable fiber undercut where all the cores make contact is slightly smaller than that of single-mode fiber (SMF) connectors. Therefore, we propose a new equation for determining the allowable fiber undercut of MCF connectors. We also fabricated MCF connectors with an allowable fiber undercut and confirmed their reliability using the composite temperature/humidity cyclic test.

The ideal point scattering model requires that each scattering center is isotropic, the position of the scattering center corresponding to the target remains unchanged, and the backscattering amplitude and phase of the target do not change with the incident frequency and incident azimuth. In fact, these conditions of the ideal point scattering model are difficult to meet, and the scattering models are not ideal in most cases. In order to understand the difference between non-ideal scattering center and ideal scattering center, this paper takes a metal plate as the research object, carries out two-dimensional imaging of the metal plate, compares the difference between the imaging position and the theoretical target position, and compares the shape of the scattering center obtained from two-dimensional imaging of the plate from different angles. From the experimental results, the offset between the scattering center position and the theoretical target position corresponding to the two-dimensional imaging of the plate under the non-ideal point scattering model is less than the range resolution and azimuth resolution. The deviation between the small angle two-dimensional imaging position and the theoretical target position using the ideal point scattering model is small, and the ideal point scattering model is still suitable for the two-dimensional imaging of the plate. In the imaging process, the ratio of range resolution and azimuth resolution affects the shape of the scattering center. The range resolution is equal to the azimuth resolution, the shape of the scattering center is circular; the range resolution is not equal to the azimuth resolution, and the shape of the scattering center is elliptic. In order to obtain more accurate two-dimensional image, the appropriate range resolution and azimuth resolution can be considered when using the ideal point scattering model for two-dimensional imaging. The two-dimensional imaging results of the plate at different azimuth and angle can be used as a reference for the study of non-ideal point scattering model.

In this paper, multi-input multi-output (MIMO) signal detection with random walk along a gradient descent direction using an intermediate search point is presented. As a low complexity MIMO signal detection schemes, a gradient descent algorithm with Metropolis-Hastings (MH) methods has been proposed. Random walk along a gradient descent direction speeds up the MH based search using the gradient of a least-squares cost function. However, the gradient vector may be discarded through QAM constellation quantization in some cases. For further performance improvement, this paper proposes an improved search scheme in which the gradient vector is stored for the next search iteration to generate an intermediate search point. The performance of the proposed scheme improves with higher order modulation symbols as compared with that of a conventional scheme. Numerical results obtained through computer simulation show that a bit error rate (BER) performance improves by 5dB at a BER of 10-3 for 64QAM symbols in a 16×16 MIMO system.

In this paper, a circuit based on a field programmable analog array (FPAA) is proposed for three types of chaotic spiking oscillator (CSO). The input/output conversion characteristics of a specific element in the FPAA can be defined by the user. By selecting the proper characteristics, three types of CSO are realized without changing the structure of the circuit itself. Chaotic attractors are observed in a hardware experiment. It is confirmed that the dynamics of the CSOs are consistent with numerical simulations.

With the gradually increase of the application of new energy in microgrids, Electric Spring (ES), as a new type of distributed compensation power electronic device has been widely studied. The Generalized Electric Spring (G-ES) is an improved topology, and the space limitation problem in the traditional topology is solved. Because of the mode of G-ES use in the power grid, a reasonable solution to the voltage loss of the critical section feeder is needed. In this paper, the voltage balance equation based on the feedforward compensation coefficient is established, and a two cascade control strategy based on the equation is studied. The first stage of the two cascade control strategy is to use communication means to realize the allocation of feedforward compensation coefficients, and the second stage is to use the coefficients to realize feedforward fixed angle control. Simulation analysis shows that the proposed control strategy does not affect the control accuracy of the critical load (CL), and effectively improves the operational range of the G-ES.

In this study, an overloaded large-scale distributed antenna network is considered, for which the number of active users is larger than that of antennas distributed in a base station coverage area (called a cell). To avoid overload, users in each cell are divided into multiple user groups, and, to reduce the computational complexity required for multi-user multiple-input and multiple-output (MU-MIMO), users in each user group are grouped into multiple user clusters so that cluster-wise distributed MU-MIMO can be performed in parallel in each user group. However, as the network size increases, conventional computational methods may not be able to solve combinatorial optimization problems, such as user scheduling and user clustering, which are required for performing cluster-wise distributed MU-MIMO in a finite amount of time. In this study, we apply quantum computing to solve the combinatorial optimization problems of user scheduling and clustering for an overloaded distributed antenna network and propose a quantum computing-based user scheduling and clustering method. The results of computer simulations indicate that as the technology of quantum computers and their related algorithms evolves in the future, the proposed method can realize large-scale dense wireless systems and realize real-time optimization with a short optimization execution cycle.

This paper extends our previously reported non-orthogonal multiple access (NOMA)-based highly-efficient and low-latency hybrid automatic repeat request (HARQ) method for ultra-reliable low latency communications (URLLC) to the case with inter-base station cooperation. In the proposed method, delay-sensitive URLLC packets are preferentially multiplexed with best-effort enhanced mobile broadband (eMBB) packets in the same channel using superposition coding to reduce the transmission latency of the URLLC packet while alleviating the throughput loss in eMBB. Although data transmission to the URLLC terminal is conducted by multiple base stations based on inter-base station cooperation, the proposed method allocates radio resources to URLLC terminals which include scheduling (bandwidth allocation) and power allocation at each base station independently to achieve the short transmission latency required for URLLC. To avoid excessive radio resource assignment to URLLC terminals due to independent resource assignment at each base station, which may result in throughput degradation in eMBB terminals, we employ an adaptive path-loss-dependent weighting approach in the scheduling-metric calculation. This achieves appropriate radio resource assignment to URLLC terminals while reducing the packet error rate (PER) and transmission delay time thanks to the inter-base station cooperation. We show that the proposed method significantly improves the overall performance of the system that provides simultaneous eMBB and URLLC services.

Radar-based sensing and concealed weapon detection technologies have been attracting attention as a measure to enhance security screening in public facilities and various venues. For these applications, the security check must be performed without impeding the flow of people, with minimum human effort, and in a non-contact manner. We developed technologies for a high-throughput walk-through security screening called Invisible Sensing (IVS) and implemented them in a prototype system. The IVS system consists of dual planar radar panels facing each other and carries out an inspection based on a multi-region screening approach as a person walks between the panels. Our imaging technology constructs a high-quality radar image that compensates for motion blur caused by a person's walk. Our detection technology takes multi-view projected images across the multiple regions as input to enable real-time whole-body screening. The IVS system runs its functions by pipeline processing to achieve real-time screening operation. This paper presents our IVS system along with these key technologies and demonstrates its empirical performance.

Precision microwave measurement systems require highly stable oscillators with both excellent long-term and short-term stability. Compared to components used in laboratory instruments, dielectric resonator oscillators (DRO) offer low phase noise with greatly reduced mechanical complexity. To further enhance performance, phase-locked loop (PLL) stabilization can be used to eliminate drift and provide precise frequency control. In this work, the design of a low-cost DRO concept is presented and its performance is evaluated through simulations and measurements. An open-loop phase noise of -107.2 dBc/Hz at 10 kHz offset frequency and 12.8 GHz output frequency is demonstrated. Drift and phase noise are reduced by a PLL, so that a very low jitter of under 29.6 fs is achieved over the entire operating bandwidth.

Indoor free space optical (FSO) communication technology that provides high-speed connectivity to edge users is expected to be introduced in the near future mobile communication system, where the silicon photonics solid-state beam scanning device is a promising tool because of its low cost, long-term reliability, and other beneficial properties. However, the current two-dimensional beam scanning devices using grating coupler arrays have difficulty in increasing the transmission capacity because of bandwidth regulation. To solve the problem, we have introduced a broadband surface optical coupler, “elephant coupler,” which has great potential for combining wavelength and spatial division multiplexing technologies into the beam scanning device, as an alternative to grating couplers. The prototype port-selective silicon beam scanning device fabricated using a 300 mm CMOS pilot line achieved broadband optical beam emission with a 1 dB-loss bandwidth of 40 nm and demonstrated beam scanning using an imaging lens. The device has also exhibited free-space signal transmission of non-return-to-zero on-off-keying signals at 10 Gbps over a wide wavelength range of 60 nm. In this paper, we present an overview of the developed beam scanning device. Furthermore, the theoretical design guidelines for indoor mobile FSO communication are discussed.

An interconnection network is an inevitable component for constructing parallel computers. It connects computation nodes so that the nodes can communicate with each other. As a parallel computation essentially requires inter-node communication according to a parallel algorithm, the interconnection network plays an important role in terms of communication performance. This paper focuses on the collective communication that is frequently performed in parallel computation and this paper addresses the Cup-Stacking method that is proposed in our preceding work. The key issues of the method are splitting a large packet into slices, re-shaping the slice, and stacking the slices, in a genetic algorithm (GA) manner. This paper discusses extending the Cup-Stacking method by introducing additional items (genes) and proposes the extended Cup-Stacking method. Furthermore, this paper places comprehensive discussions on the drawbacks and further optimization of the method. Evaluation results reveal the effectiveness of the extended method, where the proposed method achieves at most seven percent improvement in duration time over the former Cup-Stacking method.

This letter presents a global feature-based method for evaluating the no reference quality of scanning electron microscopy (SEM) contrast-distorted images. Based on the characteristics of SEM images and the human visual system, the global features of SEM images are extracted as the score for evaluating image quality. In this letter, the texture information of SEM images is first extracted using a low-pass filter with orientation, and the amount of information in the texture part is calculated based on the entropy reflecting the complexity of the texture. The singular values with four scales of the original image are then calculated, and the amount of structural change between different scales is calculated and averaged. Finally, the amounts of texture information and structural change are pooled to generate the final quality score of the SEM image. Experimental results show that the method can effectively evaluate the quality of SEM contrast-distorted images.

The configurable Ring oscillator Physical unclonable function (CRO PUF) is the newly proposed strong PUF based on classic RO PUF, which can generate exponential Challenge-Response Pairs (CRPs) and has good uniqueness and reliability. However, existing proposals have low hardware utilization and vulnerability to modeling attacks. In this paper, we propose a Novel Configurable Dual State (CDS) PUF with lower overhead and higher resistance to modeling attacks. This structure can be flexibly transformed into RO PUF and TERO PUF in the same topology according to the parity of the Hamming Weight (HW) of the challenge, which can achieve 100% utilization of the inverters and improve the efficiency of hardware utilization. A feedback obfuscation mechanism (FOM) is also proposed, which uses the stable count value of the ring oscillator in the PUF as the updated mask to confuse and hide the original challenge, significantly improving the effect of resisting modeling attacks. The proposed FOM-CDS PUF is analyzed by building a mathematical model and finally implemented on Xilinx Artix-7 FPGA, the test results show that the FOM-CDS PUF can effectively resist several popular modeling attack methods and the prediction accuracy is below 60%. Meanwhile it shows that the FOM-CDS PUF has good performance with uniformity, Bit Error Rate at different temperatures, Bit Error Rate at different voltages and uniqueness of 53.68%, 7.91%, 5.64% and 50.33% respectively.

As an efficient classical machine learning classifier, the Softmax regression uses cross-entropy as the loss function. Therefore, it has high accuracy in classification. However, when there is inconsistency between the distribution of training samples and test samples, the performance of traditional Softmax regression models will degrade. A transfer discriminant Softmax regression model called Transfer Discriminant Softmax Regression with Weighted MMD (TDS-WMMD) is proposed in this paper. With this method, the Weighted Maximum Mean Divergence (WMMD) is introduced into the objective function to reduce the marginal distribution and conditional distribution between domains both locally and globally, realizing the cross domain transfer of knowledge. In addition, to further improve the classification performance of the model, Linear Discriminant Analysis (LDA) is added to the label iteration refinement process to improve the class separability of the designed method by keeping the same kind of samples together and the different kinds of samples repeling each other. Finally, after conducting classification experiments on several commonly used public transfer learning datasets, the results verify that the designed method can enhance the knowledge transfer ability of the Softmax regression model, and deliver higher classification performance compared with other current transfer learning classifiers.

In this article, a new Beamforming Network (BFN) realized in Broadside Coupled Stripline (BCS) is proposed to feed 1×4 and 2×2 arrays antenna at 28 GHZ-Band. The new BFN is composed only of couplers and phase shifters. It doesn't require any crossover compared to the conventional Butler Matrix (BM) which requires two crossovers. The tight coupling and low loss characteristics of the BCS allow a design of a compact and wideband BFN. The new BFN produces the phase differences of (±90°) and (±45°, ±135°) respectively in x- and y-directions. Its integration with a 1×4 linear array antenna reduces the array area by 70% with an improvement of the gain performance compared with the conventional array. The integration with a 2×2 array allows the realization of a full 2-D beam scanning. The proposed concept has been verified experimentally by measuring the fabricated prototypes of the BFN, the 1-D and 2-D patch arrays antennas. The measured 11.5 dBi and 11.3 dBi maximum gains are realized in θ0 = 14° and (θ0, φ0) = (45°,345°) directions respectively for the 1-D and 2-D patch arrays. The physical area of the fabricated BFN is only (0.37λ0×0.3λ0×0.08λ0), while the 1-D array and 2-D array antennas areas without feeding transmission lines are respectively (0.5λ0×2.15λ0×0.08λ0) and (0.9λ0×0.8λ0×0.08λ0).