Efficient multiplexing of ultra-reliable and low-latency communications (URLLC) and enhanced mobile broadband (eMBB) traffic, as well as ensuring the various reliability requirements of these traffic types in 5G wireless communications, is becoming increasingly important, particularly for vertical services. Interference management techniques, such as coordinated inter-cell scheduling, can enhance reliability in dense cell deployments. However, tight inter-cell coordination necessitates frequent information exchange between cells, which limits implementation. This paper introduces a novel RAN slicing framework based on centralized frequency-domain interference control per slice and link adaptation optimized for URLLC. The proposed framework does not require tight inter-cell coordination but can fulfill the requirements of both the decoding error probability and the delay violation probability of each packet flow. These controls are based on a power-law estimation of the lower tail distribution of a measured data set with a smaller number of discrete samples. As design guidelines, we derived a theoretical minimum radio resource size of a slice to guarantee the delay violation probability requirement. Simulation results demonstrate that the proposed RAN slicing framework can achieve the reliability targets of the URLLC slice while improving the spectrum efficiency of the eMBB slice in a well-balanced manner compared to other evaluated benchmarks.

As a hierarchical network framework, clustering aims to divide nodes with similar mobility characteristics into the same cluster to form a more structured hierarchical network, which can effectively solve the problem of high dynamics of the network topology caused by the high-speed movement of nodes in aeronautical ad hoc networks. Based on this goal, we propose a multi-hop distributed clustering algorithm based on link duration. The algorithm is based on the idea of multi-hop clustering, which ensures the coverage and stability of clustering. In the clustering phase, the link duration is used to accurately measure the degree of stability between nodes. At the same time, we also use the link duration threshold to filter out relatively stable links and use the gravity factor to let nodes set conditions for actively creating links based on neighbor distribution. When selecting the cluster head, we select the most stable node as the cluster head node based on the defined node stability weight. The node stability weight comprehensively considers the connectivity degree of nodes and the link duration between nodes. In order to verify the effectiveness of the proposed method, we compare them with the N-hop and K-means algorithms from four indicators: average cluster head duration, average cluster member duration, number of cluster head changes, and average number of intra-cluster link changes. Experiments show that the proposed method can effectively improve the stability of the topology.

In future deep space communication missions, VLBI (Very Long Baseline Interferometry) based on antenna array technology remains a critical detection method, which urgently requires the improvement of synthesis performance for antenna array signals. Considering this, focusing on optimizing the traditional antenna grouping method applied in the phase estimation algorithm, this letter proposes a “L/2 to L/2” antenna grouping method based on the maximum correlation signal-to-noise ratio (SNR). Following this idea, a phase difference estimation algorithm named “Couple” is presented. Theoretical analysis and simulation verification illustrate that: when ρ ＜ -10dB, the proposed “Couple” has the highest performance; increasing the number of antennas can significantly improve its synthetic loss performance and robustness. The research of this letter indicates a promising potential in supporting the rising deep space exploration and communication missions.

Convolutional neural network (CNN) is widely used in acoustic scene classification (ASC) tasks. In most cases, local convolution is utilized to gather time-frequency information between spectrum nodes. It is challenging to adequately express the non-local link between frequency domains in a finite convolution region. In this paper, we propose a dual-path convolutional neural network based on band interaction block (DCNN-bi) for ASC, with mel-spectrogram as the model’s input. We build two parallel CNN paths to learn the high-frequency and low-frequency components of the input feature. Additionally, we have created three band interaction blocks (bi-blocks) to explore the pertinent nodes between various frequency bands, which are connected between two paths. Combining the time-frequency information from two paths, the bi-blocks with three distinct designs acquire non-local information and send it back to the respective paths. The experimental results indicate that the utilization of the bi-block has the potential to improve the initial performance of the CNN substantially. Specifically, when applied to the DCASE 2018 and DCASE 2020 datasets, the CNN exhibited performance improvements of 1.79% and 3.06%, respectively.

Artificial intelligence and the introduction of Internet of Things technologies have benefited from technological advances and new automated computer system technologies. Eventually, it is now possible to integrate them into a single offline industrial system. This is accomplished through machine-to-machine communication, which eliminates the human factor. The purpose of this article is to examine security systems for machine-to-machine communication systems that rely on identification and authentication algorithms for real-time monitoring. The article investigates security methods for quickly resolving data processing issues by using the Security operations Center’s main machine to identify and authenticate devices from 19 different machines. The results indicate that when machines are running offline and performing various tasks, they can be exposed to data leaks and malware attacks by both the individual machine and the system as a whole. The study looks at the operation of 19 computers, 7 of which were subjected to data leakage and malware attacks. AnyLogic software is used to create visual representations of the results using wireless networks and algorithms based on previously processed methods. The W76S is used as a protective element within intelligent sensors due to its built-in memory protection. For 4 machines, the data leakage time with malware attacks was 70 s. For 10 machines, the duration was 150 s with 3 attacks. Machine 15 had the longest attack duration, lasting 190 s and involving 6 malware attacks, while machine 19 had the shortest attack duration, lasting 200 s and involving 7 malware attacks. The highest numbers indicated that attempting to hack a system increased the risk of damaging a device, potentially resulting in the entire system with connected devices failing. Thus, illegal attacks by attackers using malware may be identified over time, and data processing effects can be prevented by intelligent control. The results reveal that applying identification and authentication methods using a protocol increases cyber-physical system security while also allowing real-time monitoring of offline system security.

Emerging data-intensive services in distribution grid impose requirements of high-concurrency access for massive internet of things (IoT) devices. However, the lack of effective high-concurrency access management results in severe performance degradation. To address this challenge, we propose a cloud-edge-device collaborative high-concurrency access management algorithm based on multi-timescale joint optimization of channel pre-allocation and load balancing degree. We formulate an optimization problem to minimize the weighted sum of edge-cloud load balancing degree and queuing delay under the constraint of access success rate. The problem is decomposed into a large-timescale channel pre-allocation subproblem solved by the device-edge collaborative access priority scoring mechanism, and a small-timescale data access control subproblem solved by the discounted empirical matching mechanism (DEM) with the perception of high-concurrency number and queue backlog. Particularly, information uncertainty caused by externalities is tackled by exploiting discounted empirical performance which accurately captures the performance influence of historical time points on present preference value. Simulation results demonstrate the effectiveness of the proposed algorithm in reducing edge-cloud load balancing degree and queuing delay.

In recent years, measuring biomagnetic fields in the Earth’s field by differential measurements of scalar-mode OPMs have been actively attempted. In this study, the sensitivity of the scalar-mode OPMs under the geomagnetic environment in the laboratory was studied by numerical simulation. Although the noise level of the scalar-mode OPM in the laboratory environment was calculated to be 104 pT/$\sqrt{\mathrm{Hz}}$, the noise levels using the first-order and the second-order differential configurations were found to be 529 fT/cm/$\sqrt{\mathrm{Hz}}$ and 17.2 fT/cm2/$\sqrt{\mathrm{Hz}}$, respectively. This result indicated that scalar-mode OPMs can measure very weak magnetic fields such as MEG without high-performance magnetic shield roomns. We also studied the operating conditions by varying repetition frequency and temperature. We found that scalar-mode OPMs have an upper limit of repetition frequency and temperature, and that the repetition frequency should be set below 4 kHz and the temperature should be set below 120°C.

Despite the appealing advantages of reconfigurable intelligent surfaces (RIS) aided mmWave communications, there remain practical issues that need to be addressed before the large-scale deployment of RISs in future wireless networks. In this study, we jointly consider the non-neglectable practical issues in a multi-RIS-aided mmWave system, which can significantly affect the secrecy performance, including the high computational complexity, imperfect channel state information (CSI), and finite resolution of phase shifters. To solve this non-convex challenging stochastic optimization problem, we propose a robust and low-complexity algorithm to maximize the achievable secrete rate. Specially, by combining the benefits of fractional programming and the stochastic successive convex approximation techniques, we transform the joint optimization problem into some convex ones and solve them sub-optimally. The theoretical analysis and simulation results demonstrate that the proposed algorithms could mitigate the joint negative effects of practical issues and yielded a tradeoff between secure performance and complexity/overhead outperforming non-robust benchmarks, which increases the robustness and flexibility of multiple RIS deployments in future wireless networks.

Cooperative Communication is one of the most effective techniques to improve the desired signal quality of the typical user. This paper studies an indoor cellular network system that deploys the Reconfigurable Intelligent Surfaces (RIS) at the position of BSs to enable the cooperative features. To evaluate the network performance, the coverage probability expression of the typical user in the indoor wireless environment with presence of walls and effects of Rayleigh fading is derived. The analytical results shows that the RIS-assisted system outperforms the regular one in terms of coverage probability.

Direct-current biased optical orthogonal frequency division multiplexing (DCO-OFDM) converts bipolar OFDM signals into unipolar non-negative signals by introducing a high DC bias, which satisfies the requirement that the signal transmitted by intensity modulated/direct detection (IM/DD) must be positive. However, the high DC bias results in low power efficiency of DCO-OFDM. An adaptively biased optical OFDM was proposed, which could be designed with different biases according to the signal amplitude to improve power efficiency in this letter. The adaptive bias does not need to be taken off deliberately at the receiver, and the interference caused by the adaptive bias will only be placed on the reserved subcarriers, which will not affect the effective information. Moreover, the proposed OFDM uses Hartley transform instead of Fourier transform used in conventional optical OFDM, which makes this OFDM have low computational complexity and high spectral efficiency. The simulation results show that the normalized optical bit energy to noise power ratio (Eb(opt)/N0) required by the proposed OFDM at the bit error rate (BER) of 10-3 is, on average, 7.5 dB and 3.4 dB lower than that of DCO-OFDM and superimposed asymmetrically clipped optical OFDM (ACO-OFDM), respectively.

The concepts of programmable switches and software-defined networking (SDN) give developers flexible and deep control over the behavior of switches. We expect these concepts to dramatically improve the functionality of switches. In this paper, we focus on the concept of Deeply Programmable Networks (DPN), where data planes are programmable, and application switches based on DPN. We then propose a method to improve the performance of a key-value store (KVS) through an application switch. First, we explain the DPN and application switches. The DPN is a network that makes not only control planes but also data planes programmable. An application switch is a switch that implements some functions of network applications, such as database management system (DBMS). Second, we propose a method to improve the performance of Cassandra, one of the most popular key-value based DBMS, by implementing a caching function in a switch in a dedicated network such as a data center. The proposed method is expected to be effective even though it is a simple and traditional way because it is in the data path and the center of the network application. Third, we implement a switch with the caching function, which monitors the accessed data described in packets (Ethernet frames) and dynamically replaces the cached data in the switch, and then show that the proposed caching switch can significantly improve the KVS transaction performance with this implementation. In the case of our evaluation, our method improved the KVS transaction throughput by up to 47%.

Previously a method was reported to determine the mathematical representation of the microwave oscillator admittance by using numerical calculation. When analyzing the load characteristics and synchronization phenomena by using this formula, the analysis results meet with the experimental results. This paper describes a method to determine the mathematical representation manually.

An optical mode multiplexer was newly designed and fabricated using LiNbO3 waveguides. The multiplexer consists of an asymmetric directional coupler capable of achieving the phase-matching condition by the voltage adjustment. The mode conversion efficiency between TM0 and TM1 modes was quantitatively measured to be 0.86 at maximum.

An efficient optical power splitter constructed by a metal-dielectric-metal plasmonic waveguide with a resonator structure has been analyzed. The method of solution is the finite difference time domain (FD-TD) method with the piecewise linear recursive convolution (PLRC) method. The resonator structure consists of input/output waveguides and a narrow waveguide with a T-junction. The power splitter with the resonator structure is expressed by an equivalent transmission-line circuit. We can find that the transmittance and reflectance calculated by the FD-TD method and the equivalent circuit are matched when the difference in width between the input/output waveguides and the narrow waveguide is small. It is also shown that the transmission wavelength can be adjusted by changing the narrow waveguide lengths that satisfy the impedance matching condition in the equivalent circuit.

In this study, the edge diffraction of a TM-polarized electromagnetic plane wave by two-dimensional dielectric wedges has been analyzed. An asymptotic solution for the radiation field has been derived from equivalent electric and magnetic currents which can be determined by the geometrical optics (GO) rays. This method may be regarded as an extended version of physical optics (PO). The diffracted field has been represented in terms of cotangent functions whose singularity behaviors are closely related to GO shadow boundaries. Numerical calculations are performed to compare the results with those by other reference solutions, such as the hidden rays of diffraction (HRD) and a numerical finite-difference time-domain (FDTD) simulation. Comparisons of the diffraction effect among these results have been made to propose additional lateral waves in the denser media.

The very high path loss caused by molecular absorption becomes the biggest problem in Terahertz (THz) wireless communications. Recently, the multi-band ultra-massive multi-input multi-output (UM-MIMO) system has been proposed to overcome the distance problem. In UM-MIMO systems, the impact of mutual coupling among antennas on the system performance is unable to be ignored because of the dense array. In this letter, a channel model of UM-MIMO communication system is developed which considers coupling effect. The effect of mutual coupling in the subarray on the functionality of the system has been investigated through simulation studies, and reliable results have been derived.

In interdependent systems, such as electric power systems, entities or components mutually depend on each other. Due to these interdependencies, a small number of initial failures can propagate throughout the system, resulting in catastrophic system failures. This paper addresses the problem of finding the set of entities whose failures will have the worst effects on the system. To this end, a two-phase algorithm is developed. In the first phase, the tight bound on failure propagation steps is computed using a Boolean Satisfiablility (SAT) solver. In the second phase, the problem is formulated as an Integer Linear Programming (ILP) problem using the obtained step bound and solved with an ILP solver. Experimental results show that the algorithm scales to large problem instances and outperforms a single-phase algorithm that uses a loose step bound.

In cyber-physical systems (CPSs) that interact between physical and information components, there are many sensors that are connected through a communication network. In such cases, the reduction of communication costs is important. Event-triggered control that the control input is updated only when the measured value is widely changed is well known as one of the control methods of CPSs. In this paper, we propose a design method of output feedback controllers with decentralized event-triggering mechanisms, where the notion of uniformly ultimate boundedness is utilized as a control specification. Using this notion, we can guarantee that the state stays within a certain set containing the origin after a certain time, which depends on the initial state. As a result, the number of times that the event occurs can be decreased. First, the design problem is formulated. Next, this problem is reduced to a BMI (bilinear matrix inequality) optimization problem, which can be solved by solving multiple LMI (linear matrix inequality) optimization problems. Finally, the effectiveness of the proposed method is presented by a numerical example.

In this paper, we consider a distributed stochastic nonconvex optimization problem for multiagent systems. We propose a distributed stochastic gradient-tracking method with event-triggered communication. A group of agents cooperatively finds a critical point of the sum of local cost functions, which are smooth but not necessarily convex. We show that the proposed algorithm achieves a sublinear convergence rate by appropriately tuning the step size and the trigger threshold. Moreover, we show that agents can effectively solve a nonconvex optimization problem by the proposed event-triggered algorithm with less communication than by the existing time-triggered gradient-tracking algorithm. We confirm the validity of the proposed method by numerical experiments.

L-type LC/CL matching circuits are well known for their simple analytical solutions and have been applied to many radio-frequency (RF) circuits. When actually constructing a circuit, parasitic elements are added to inductors and capacitors. Therefore, each L and C element has a self-resonant frequency, which affects the characteristics of the matching circuit. In this paper, the parallel parasitic capacitance to the inductor and the series parasitic inductor to the capacitance are taken up as parasitic elements, and the details of the effects of the self-resonant frequency of each element on the S11, voltage standing wave ratio (VSWR) and S21 characteristics are reported. When a parasitic element is added, each characteristic basically tends to deteriorate as the self-resonant frequency decreases. However, as an interesting feature, we found that the combination of resonant frequencies determines the VSWR and passband characteristics, regardless of whether it is the inductor or the capacitor.