When a failure occurs in a network element, such as switch, router, and server, network operators need to recognize the service impact, such as time to recovery from the failure or severity of the failure, since service impact is essential information for handling failures. In this paper, we propose Deep learning based Service Impact Prediction system (DeepSIP), which predicts the service impact of network failure in a network element using a temporal multimodal convolutional neural network (CNN). More precisely, DeepSIP predicts the time to recovery from the failure and the loss of traffic volume due to the failure in a network on the basis of information from syslog messages and traffic volume. Since the time to recovery is useful information for a service level agreement (SLA) and the loss of traffic volume is directly related to the severity of the failure, we regard the time to recovery and the loss of traffic volume as the service impact. The service impact is challenging to predict, since it depends on types of network failures and traffic volume when the failure occurs. Moreover, network elements do not explicitly contain any information about the service impact. To extract the type of network failures and predict the service impact, we use syslog messages and past traffic volume. However, syslog messages and traffic volume are also challenging to analyze because these data are multimodal, are strongly correlated, and have temporal dependencies. To extract useful features for prediction, we develop a temporal multimodal CNN. We experimentally evaluated DeepSIP in terms of accuracy by comparing it with other NN-based methods by using synthetic and real datasets. For both datasets, the results show that DeepSIP outperformed the baselines.

This paper demonstrates that a 360° radio-frequency phase detector consisting of a combination of symmetrical mixers and 45° phase shifters with tunable devices can achieve a low phase-detection error over a wide frequency range. It is shown that the phase detection error does not depend on the voltage gain of the 45° phase shifter. This allows the usage of tunable devices as 45° phase shifters for a wide frequency range with low phase-detection errors. The fabricated phase detector having tunable low-pass filters as the tunable device demonstrates phase detection errors lower than 2.0° rms in the frequency range from 3.0 GHz to 10.5 GHz.

In this paper, a stochasic geometry analysis of the inversely proportional setting (IPS) of carrier sense threshold (CST) and transmission power for densely deployed wireless local area networks (WLANs) is presented. In densely deployed WLANs, CST adjustment is a crucial technology to enhance spatial reuse, but it can starve surrounding transmitters due to an asymmetric carrier sensing relationship. In order for the carrier sensing relationship to be symmetric, the IPS of the CST and transmission power is a promising approach, i.e., each transmitter jointly adjusts its CST and transmission power in order for their product to be equal to those of others. This setting is used for spatial reuse in IEEE 802.11ax. By assuming that the set of potential transmitters follows a Poisson point process, the impact of the IPS on throughput is formulated based on stochastic geometry in two scenarios: an adjustment at a single transmitter and an identical adjustment at all transmitters. The asymptotic expression of the throughput in dense WLANs is derived and an explicit solution of the optimal CST is achieved as a function of the number of neighboring potential transmitters and signal-to-interference power ratio using approximations. This solution was confirmed through numerical results, where the explicit solution achieved throughput penalties of less than 8% relative to the numerically evaluated optimal solution.

Binary sequence pairs with optimal periodic correlation have important applications in many fields of communication systems. In this letter, four new families of binary sequence pairs are presented based on the generalized cyclotomy over Z5q, where q ≠ 5 is an odd prime. All these binary sequence pairs have optimal three-level correlation values {-1, 3}.

Crowd flow prediction in high density urban scenes is involved in a wide range of intelligent transportation and smart city applications, and it has become a significant topic in urban computing. In this letter, a CNN-based framework called Pyramidal Spatio-Temporal Network (PSTNet) for crowd flow prediction is proposed. Spatial encoding is employed for spatial representation of external factors, while prior pyramid enhances feature dependence of spatial scale distances and temporal spans, after that, post pyramid is proposed to fuse the heterogeneous spatio-temporal features of multiple scales. Experimental results based on TaxiBJ and MobileBJ demonstrate that proposed PSTNet outperforms the state-of-the-art methods.

Realizing frequency rectangular characteristics using a planar circuit made of a normal conductor material such as a printed circuit board (PCB) is difficult. The reason is that the corners of the frequency response are rounded by the effect of the low unloaded quality factors of the resonators. Rectangular frequency characteristics are generally realized by a low-noise amplifier (LNA) with flat gain characteristics and a high-order bandpass filter (BPF) with resonators having high unloaded quality factors. Here, we use an LNA and a fourth-order flat passband BPF made of a PCB to realize the desired characteristics. We first calculate the signal and noise powers to confirm any effects from insertion loss caused by the BPF. Next, we explain the design and fabrication of an LNA, since no proper LNAs have been developed for this research. Finally, the rectangular frequency characteristics are shown by a circuit combining the fabricated LNA and the fabricated flat passband BPF. We show that rectangular frequency characteristics can be realized using a flat passband BPF technique.

Linear programming (LP) decoding based on the alternating direction method of multipliers (ADMM) has proved to be effective for low-density parity-check (LDPC) codes. However, for high-density parity-check (HDPC) codes, the ADMM-LP decoder encounters two problems, namely a high-density check matrix in HDPC codes and a great number of pseudocodewords in HDPC codes' fundamental polytope. The former problem makes the check polytope projection extremely complex, and the latter one leads to poor frame error rates (FER) performance. To address these issues, we introduce the even vertex algorithm (EVA) into the ADMM-LP decoding algorithm for HDPC codes, named as HDPC-EVA. HDPC-EVA can reduce the complexity of the projection process and improve the FER performance. We further enhance the proposed decoder by the automorphism groups of codes, creating diversity in the parity-check matrix. The simulation results show that the proposed decoder is capable of cutting down the average decoding time for each iteration by 30%-60%, as well as achieving near maximum likelihood (ML) performance on some BCH codes.

Long-range radars (LRRs) for higher level autonomous driving (AD) will require more antennas than simple driving assistance. The point at issue here is 50-60% of the LRR module area is used for antennas. To miniaturize LRR modules, we use horn and lens antenna with highly efficient gain. In this paper, we propose two high-density implementation techniques for radio-frequency (RF) front-end using horn and lens antennas. In the first technique, the gap between antennas was eliminated by taking advantage of the high isolation performance of horn and lens antennas. In the second technique, the RF front-end including micro-strip-lines, monolithic microwave integrated circuits, and peripheral parts is placed in the valley area of each horn. We fabricated a prototype LRR operating at 77 GHz with only one printed circuit board (PCB). To detect vehicles horizontally and vertically, this LRR has a minimum antenna configuration of one Tx antenna and four Rx antennas placed in 2×2 array, and 30 mm thickness. Evaluation results revealed that vehicles could be detected up to 320 m away and that the horizontal and vertical angle error was less than +/- 0.2 degrees, which is equivalent to the vehicle width over 280 m. Thus, horn and lens antennas implemented using the proposed techniques are very suitable for higher level AD LRRs.

Service composition optimization is a classic NP-hard problem. How to quickly select high-quality services that meet user needs from a large number of candidate services is a hot topic in cloud service composition research. An efficient second-order beetle swarm optimization is proposed with a global search ability to solve the problem of cloud service composition optimization in this study. First, the beetle antennae search algorithm is introduced into the modified particle swarm optimization algorithm, initialize the population bying using a chaotic sequence, and the modified nonlinear dynamic trigonometric learning factors are adopted to control the expanding capacity of particles and global convergence capability. Second, modified secondary oscillation factors are incorporated, increasing the search precision of the algorithm and global searching ability. An adaptive step adjustment is utilized to improve the stability of the algorithm. Experimental results founded on a real data set indicated that the proposed global optimization algorithm can solve web service composition optimization problems in a cloud environment. It exhibits excellent global searching ability, has comparatively fast convergence speed, favorable stability, and requires less time cost.

Heterogeneous networks (HetNets) are emerging as an inevitable method to tackle the capacity crunch of the cellular networks. Due to the complicated network environment and a large number of configured parameters, coverage and capacity optimization (CCO) is a challenging issue in heterogeneous cellular networks. By combining the self-optimizing algorithm for radio frequency (RF) parameters with the power control mechanism of small cells, the CCO problem of self-organizing network is addressed in this paper. First, the optimization of RF parameters is solved based on reinforcement learning (RL), where the base station is modeled as an agent that can learn effective strategies to control the tunable parameters by interacting with the surrounding environment. Second, the small cell can autonomously change the state of wireless transmission by comparing its distance from the user equipment with the virtual cell size. Simulation results show that the proposed algorithm can achieve better performance on user throughput compared to different conventional methods.

In an amusement park, an attraction-visiting route considering the waiting time and traveling time improves visitors' satisfaction and experience. We focus on Ising machines to solve the problem, which are recently expected to solve combinatorial optimization problems at high speed by mapping the problems to Ising models or quadratic unconstrained binary optimization (QUBO) models. We propose a mapping of the visiting-route recommendation problem in amusement parks to a QUBO model for solving it using Ising machines. By using an actual Ising machine, we could obtain feasible solutions one order of magnitude faster with almost the same accuracy as the simulated annealing method for the visiting-route recommendation problem.

Applications of continuous-time (CT) comparator include relaxation oscillators, pulse width modulators, and so on. CT comparator receives a differential input and outputs a strobe ideally when the differential input crosses zero. Unlike the DT comparators with positive feedback circuit, amplifiers consuming static power must be employed in CT comparators to amplify the input signal. Therefore, minimization of comparator delay under the constraint of power consumption often becomes an issue. This paper analyzes transient behavior of a CT comparator. Using “constant delay approximation”, the comparator delay is derived as a function of input slew rate, number of stages of the preamplifier, and device parameters in each block. This paper also discusses optimum design of the CT comparator. The condition for minimum comparator delay is derived with keeping power consumption constant. The results include that the optimum DC gain of the preamplifier is e∼e3 per stage depending on the element which dominates load capacitance of the preamplifier.

To achieve highly efficient spectrum usage, dynamic sharing of scarce spectrum resources has recently become the subject of intense discussion. The technologies of dynamic spectrum sharing (DSS) have already been adopted or are scheduled to be adopted in a number of countries, and Japan is no exception. The authors and organizations collaborating in the research and development project being undertaken in Japan have studied a novel DSS system positioned between the fifth-generation mobile communication system (5G system) and different incumbent radio systems. Our DSS system has three characteristics. (1) It detects dynamically unused sharable spectrums (USSs) of incumbent radio systems for the space axis by using novel propagation models and estimation of the transmitting location with radio sensor information. (2) It manages USSs for the time axis by interference calculation with propagation parameters, fair assignment and future usage of USSs. (3) It utilizes USSs for the spectrum axis by using methods that decrease interference for lower separation distances. In this paper, we present an overview and the technologies of our DSS system and its applications in Japan.

We propose a useful formulation for ill-posed inverse problems in Hilbert spaces with nonlinear clipping effects. Ill-posed inverse problems are often formulated as optimization problems, and nonlinear clipping effects may cause nonconvexity or nondifferentiability of the objective functions in the case of commonly used regularized least squares. To overcome these difficulties, we present a tractable formulation in which the objective function is convex and differentiable with respect to optimization variables, on the basis of the Bregman divergence associated with the primitive function of the clipping function. By using this formulation in combination with the representer theorem, we need only to deal with a finite-dimensional, convex, and differentiable optimization problem, which can be solved by well-established algorithms. We also show two practical examples of inverse problems where our theory can be applied, estimation of band-limited signals and time-harmonic acoustic fields, and evaluate the validity of our theory by numerical simulations.

Optical code-division multiple-access (CDMA) techniques provide multi-user data transmission services in optical wireless and fiber communication systems. Several signature codes, such as modified prime sequence codes (MPSCs), generalized MPSCs (GMPSCs) and modified pseudo-orthogonal M-sequence sets, have been proposed for synchronous optical CDMA systems. In this paper, a new scheme is proposed for synchronous optical CDMA to increase the number of users and, consequently, to increase the total data rate without increasing the chip rate. The proposed scheme employs a GMPSC and an extended bi-orthogonal code which is a unipolar code generated from a bipolar Walsh code. Comprehensive comparisons between the proposed scheme and several conventional schemes are shown. Moreover, bit error rate performance and energy efficiency of the proposed scheme are evaluated comparing with those of the conventional optical CDMA schemes under atmospheric propagation environment.

Redactable signature allows anyone to remove parts of a signed message without invalidating the signature. The need to prove the validity of digital documents issued by governments is increasing. When governments disclose documents, they must remove private information concerning individuals. Redactable signature is useful for such a situation. However, in most redactable signature schemes, to remove parts of the signed message, we need pieces of information for each part we want to remove. If a signed message consists of ℓ elements, the number of elements in an original signature is at least linear in ℓ. As far as we know, in some redactable signature schemes, the number of elements in an original signature is constant, regardless of the number of elements in a message to be signed. However, these constructions have drawbacks in that the use of the random oracle model or generic group model. In this paper, we construct an efficient redactable signature to overcome these drawbacks. Our redactable signature is obtained by combining set-commitment proposed in the recent work by Fuchsbauer et al. (JoC 2019) and digital signatures.

The extended visual cryptography scheme (EVCS) proposed by Ateniese et al. is one of variations of the visual cryptography scheme such that a secret image is recovered by superimposition of certain qualified collections of shares, where cover images are visible on respective shares. In this paper, we give a new definition of the EVCS for improving visibility of the recovered secret image as well as the cover images. We formulate the problem to construct the basis matrices of the EVCS with the minimum pixel expansion as an integer programming problem. We solve the integer programming problem for general access structures with less than or equal to five participants and show that basis matrices with a smaller pixel expansion can be obtained for certain cases. We also analyze security of the EVCS meeting the new definition from an information-theoretic viewpoint. We give a condition under which any forbidden collection of shares does not reveal any additional information on not only a secret image but also the cover images that are not visible on the other shares.

In this paper, we examine techniques for improving the throughput of unlicensed radio systems such as wireless LANs (WLANs) to take advantage of multi-radio access to mobile broadband, which will be important in 5G evolution and beyond. In WLANs, throughput is reduced due to mixed standards and the degraded quality of certain frequency channels, and thus control techniques and an architecture that provide efficient control over WLANs are needed to solve the problem. We have proposed a technique to control the terminal connection dynamically by using the multi-radio of the AP. Furthermore, we have proposed a new control architecture called WiSMA for efficient control of WLANs. Experiments show that the proposed method can solve those problems and improve the WLAN throughput.

In this letter, we give a recursive construction of q-ary almost periodic complementary pairs (APCPs) based on an interleaving technique of sequences and Kronercker product. Based on this construction, we obtain new quaternary APCPs with new lengths.

Iterative block decision feedback equalization with hard-decision feedback (HD-IBDFE) was proposed for single-carrier transmission with frequency-domain equalization (SC-FDE). The detection performance hinges upon not only error propagation, but also the accuracy of estimating the parameters used to re-compute the equalizer coefficients at each iteration. In this paper, we use the erasure zone (EZ) to de-emphasize the feedback values when the hard decisions are not reliable. EZ use also enables a more accurate, and yet computationally more efficient, parameter estimation method than HD-IBDFE. We show that the resulting equalizer coefficients share the same mathematical form as that of the HD-IBDFE, thereby preserving the merit of not requiring matrix inverse operations in calculating the equalizer coefficients. Simulations show that, by using the EZ and the proposed parameter estimation method, a significant performance improvement over the conventional HD-IBDFE can be achieved, but with lower complexity.