Direction of arrival (DOA) estimation is an antenna array signal processing technique used in, for instance, radar and sonar systems, source localization, and channel state information retrieval. As new applications and use cases appear with the development of next generation mobile communications systems, DOA estimation performance must be continually increased in order to support the nonstop growing demand for wireless technologies. In previous works, we verified that a deep neural network (DNN) trained offline is a strong candidate tool with the promise of achieving great on-grid DOA estimation performance, even compared to traditional algorithms. In this paper, we propose new techniques for further DOA estimation accuracy enhancement incorporating signal-to-noise ratio (SNR) prediction and an end-to-end DOA estimation system, which consists of three components: source number estimator, DOA angular spectrum grid estimator, and DOA detector. Here, we expand the performance of the DOA detector and angular spectrum estimator, and present a new solution for source number estimation based on DNN with very simple design. The proposed DNN system applied with said enhancement techniques has shown great estimation performance regarding the success rate metric for the case of two radio wave sources although not fully satisfactory results are obtained for the case of three sources.

Synthetic aperture radar (SAR) is a device for observing the ground surface and is one of the important technologies in the field of microwave remote sensing. In SAR observation, a platform equipped with a small-aperture antenna flies in a straight line and continuously radiates pulse waves to the ground during the flight. After that, by synthesizing the series of observation data obtained during the flight, one realize high-resolution ground surface observation. In SAR observation, there are two spatial resolutions defined in the range and azimuth directions and they are limited by the bandwidth of the SAR system. The purpose of this study is to improve the resolution of SAR by sparse reconstruction. In particular, we aim to improve the resolution of SAR without changing the frequency parameters. In this paper, we propose to improve the resolution of SAR using the deconvolution iterative shrinkage-thresholding algorithm (ISTA) and verify the proposed method by carrying out an experimental analysis using an actual SAR dataset. Experimental results show that the proposed method can improve the resolution of SAR with low computational complexity.

Network function virtualization (NFV) technology significantly changes the traditional communication network environments by providing network functions as virtual network functions (VNFs) on commercial off-the-shelf (COTS) servers. Moreover, for using VNFs in a pre-determined sequence to provide each network service, service chaining is essential. A VNF can provide multiple service chains with the corresponding network function, reducing the number of VNFs. However, VNFs might be the source or the target of a cyberattack. If the node where the VNF is installed is attacked, the VNF would also be easily attacked because of its security vulnerabilities. Contrarily, a malicious VNF may attack the node where it is installed, and other VNFs installed on the node may also be attacked. Few studies have been done on the security of VNFs and nodes for service chaining. This study proposes a service chain construction with security-level management. The security-level management concept is introduced to built many service chains. Moreover, the cost optimization problem for service chaining is formulated and the heuristic algorithm is proposed. We demonstrate the effectiveness of the proposed method under certain network topologies using numerical examples.

Modulated signal detection has been rapidly advancing in various wireless communication systems as it's a core technology of spectrum sensing. To address the non-Gaussian statistical of noise in radio channels, especially its pulse characteristics in the time/frequency domain, this paper proposes a method based on Information Geometric Difference Mapping (IGDM) to solve the signal detection problem under Alpha-stable distribution (α-stable) noise and improve performance under low Generalized Signal-to-Noise Ratio (GSNR). Scale Mixtures of Gaussians is used to approximate the probability density function (PDF) of signals and model the statistical moments of observed data. Drawing on the principles of information geometry, we map the PDF of different types of data into manifold space. Through the application of statistical moment models, the signal is projected as coordinate points within the manifold structure. We then design a dual-threshold mechanism based on the geometric mean and use Kullback-Leibler divergence (KLD) to measure the information distance between coordinates. Numerical simulations and experiments were conducted to prove the superiority of IGDM for detecting multiple modulated signals in non-Gaussian noise, the results show that IGDM has adaptability and effectiveness under extremely low GSNR.

This paper presents an analysis-based design method for designing the class-Φ22 wireless power transfer (WPT) system, taking its subsystems as a whole into account. By using the proposed design method, it is possible to derive accurate design values which can make sure the class-E Zero-Voltage-Switching/Zero-Derivative-Switching (ZVS/ZDS) to obtain without applying any tuning processes. Additionally, it is possible to take the effects of the switch on resistance, diode forward voltage drop, and equivalent series resistances (ESRs) of all passive elements on the system operations into account. Furthermore, design curves for a wide range of parameters are developed and organized as basic data for various applications. The validities of the proposed design procedure and derived design curves are confirmed by LTspice simulation and circuit experiment. In the experimental measurements, the class-Φ22 WPT system achieves 78.8% power-transmission efficiency at 6.78MHz operating frequency and 7.96W output power. Additionally, the results obtained from the LTspice simulation and laboratory experiment show quantitative agreements with the analytical predictions, which indicates the accuracy and validity of the proposed analytical method and design curves given in this paper.

Non-orthogonal multipe access based multiple-input multiple-output system (MIMO-NOMA) has been widely used in improving user's achievable rate of millimeter wave (mmWave) communication. To meet different requirements of each user in multi-user beams, this paper proposes a power allocation algorithm to satisfy the quality of service (QoS) of head user while maximizing the minimum rate of edge users from the perspective of max-min fairness. Suppose that the user who is closest to the base station (BS) is the head user and the other users are the edge users in each beam in this paper. Then, an optimization problem model of max-min fairness criterion is developed under the constraints of users' minimum rate requirements and the total transmitting power of the BS. The bisection method and Karush-Kuhn-Tucher (KKT) conditions are used to solve this complex non-convex problem, and simulation results show that both the minimum achievable rates of edge users and the average rate of all users are greatly improved significantly compared with the traditional MIMO-NOMA, which only consider max-min fairness of users.

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.

This paper proposes and evaluates machine learning (ML)-based compensation methods for the transmit (Tx) weight matrices of actual singular value decomposition (SVD)-multiple-input and multiple-output (MIMO) transmissions. These methods train ML models and compensate the Tx weight matrices by using a large amount of training data created from statistical distributions. Moreover, this paper proposes simplified channel metrics based on the channel quality of actual SVD-MIMO transmissions to evaluate compensation performance. The optimal parameters are determined from many ML parameters by using the metrics, and the metrics for this determination are evaluated. Finally, a comprehensive computer simulation shows that the optimal parameters improve performance by up to 7.0dB compared with the conventional method.

Measurements of contact discharge current waveforms from an ESD generator with a test voltage of 4kV are conducted with the IEC specified arrangement of a 2m long return current cable in different three calibration environments that all comply with the IEC calibration standard to identify the occurrence source of damped oscillations (ringing), which has remained unclear since contact discharge testing was first adopted in 1989 IEC publication 801-2. Their frequency spectra are analyzed comparing with the spectrum calculated from the ideal contact discharge current waveform without ringing (IEC specified waveform) offered in IEC 61000-4-2 and the spectra derived from a simplified equivalent circuit based on the IEC standard in combination with the measured input impedances of one-ended grounding return current cable with the same arrangement in the same calibration environment as those for the current measurements. The results show that the measured contact discharge waveforms have ringing around the IEC specified waveform after the falling edge of the peak, causing their spectra from 20MHz to 200MHz, but the spectra from 40MHz to 200MHz significantly differ depending on the calibration environments even for the same cable arrangement, which do not almost affect the spectra from 20MHz to 40MHz and over 200MHz. In the calibration environment under the cable arrangement close to the reference ground, the spectral shapes of the measured contact discharge currents and their frequencies of the multiple peaks and dips roughly correspond to the spectral distributions calculated from the simplified equivalent circuit using the measured cable input impedances. These findings reveal that the root cause of ringing is mainly due to the resonances of the return current cable, and calibration environment under the cable arrangement away from the reference ground tends to mitigate the cable resonances.

This paper proposes a multibeam digital predistorter (DPD) that suppresses intercarrier interference caused by nonlinear distortions of power amplifiers (PAs) while reducing the power consumption of a multibeam array antenna transmitter. The proposed DPD reduces power consumption by allowing the final PAs of the array antenna transmitter to operate in a highly efficient nonlinear mode and compensating for the nonlinear distortions of the PAs with a unified dedicated DPD per subarray. Additionally, it provides the required high-quality signal transmission for high throughputs, such as realizing a 256-quadrature amplitude modulation (QAM) transmission instead of a 64-QAM transmission. Specifically, it adds an inverse-component signal to cancel the interference from an adjacent carrier of another beam. Consequently, it can suppress the intercarrier interference in the beam direction and improve the error vector magnitude (EVM) during the multibeam transmission, in which the frequency bands of the beams are adjacent. The experimental results obtained for two beams at 28.0 and 28.4GHz demonstrate that, compared with the previous single-beam DPD, the proposed multibeam DPD can improve the EVM. Also, they demonstrate that the proposed DPD can achieve an EVM value of <3%, which completely satisfies the 3GPP requirements for a 256-QAM transmission.

To localize an unknown wave source in non-line-of-sight environments, a wave source localization scheme using multiple unmanned-aerial-vehicles (UAVs) is proposed. In this scheme, each UAV estimates the direction-of-arrivals (DoAs) of received signals and the wave source is localized from the estimated DoAs by means of maximum likelihood estimation. In this study, by extending the concept of this scheme, we propose a novel wave source localization scheme using a single UAV. In the proposed scheme, the UAV moves on the path comprising multiple measurement points and the wave source is sequentially localized from DoA distributions estimated at these measurement points. At each measurement point, with a moving path planning algorithm, the UAV determines the next measurement point from the estimated DoA distributions and measurement points that the UAV has already visited. We consider two moving path planning algorithms, and validate the proposed scheme through simulation experiments.

Frame synchronization detection before data transmission is an important module which directly affects the lifetime and coexistence of underwater acoustic communication (UAC) networks, where linear frequency modulation (LFM) is a frame preamble signal commonly used for synchronization. Unlike terrestrial wireless communications, strong bursty noise frequently appears in UAC. Due to the long transmission distance and the low signal-to-noise ratio, strong short-distance bursty noise will greatly reduce the accuracy of conventional fractional fourier transform (FrFT) detection. We propose a multi-segment verification fractional fourier transform (MFrFT) preamble detection algorithm to address this challenge. In the proposed algorithm, 4 times of adjacent FrFT operations are carried out. And the LFM signal identifies by observing the linear correlation between two lines connected in pair among three adjacent peak points, called ‘dual-line-correlation mechanism’. The accurate starting time of the LFM signal can be found according to the peak frequency of the adjacent FrFT. More importantly, MFrFT do not result in an increase in computational complexity. Compared with the conventional FrFT detection method, experimental results show that the proposed algorithm can effectively distinguish between signal starting points and bursty noise with much lower error detection rate, which in turn minimizes the cost of retransmission.

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.

This letter presents a dual-band load-modulated sequential amplifier (LMSA). The proposed amplifier changed the attenuator terminated at the isolation port of the four-port combiner of the traditional sequential power amplifier (SPA) architecture into a reactance modulation network (RMN) for load modulation. The impedance can be maintained pure resistance by designing RMN, thus realizing high efficiency and a good portion of the output power in the multiple bands. Compared to the dual-band Doherty power amplifier with a complex dual-band load modulation network (LMN), the proposed LMSA has advantages as maintaining high output power back-off (OBO) efficiency, wide bandwidth and simple construction. A 10-watt dual-band LMSA is simulated and measured in 1.7-1.9GHz and 2.4-2.6GHz with saturated efficiencies 61.2-69.9% and 54.4-70.8%, respectively. The corresponding 9dB OBO efficiency is 46.5-57.1% and 46.4-54.4%, respectively.

In the Robot Operating System (ROS), a major middleware for robots, the Transform Library (TF) is a mandatory package that manages transformation information between coordinate systems by using a directed forest data structure and providing methods for registering and computing the information. However, the structure has two fundamental problems. The first is its poor scalability: since it accepts only a single thread at a time due to using a single giant lock for mutual exclusion, the access to the tree is sequential. Second, there is a lack of data freshness: it retrieves non-latest synthetic data when computing coordinate transformations because it prioritizes temporal consistency over data freshness. In this paper, we propose methods based on transactional techniques. This will allow us to avoid anomalies, achieve high performance, and obtain fresh data. These transactional methods show a throughput of up to 429 times higher than the conventional method on a read-only workload and a freshness of up to 1276 times higher than the conventional one on a read-write combined workload.

One of the performance bottlenecks of a processor is the front-end that supplies instructions. Various techniques, such as cache replacement algorithms and hardware prefetching, have been investigated to facilitate smooth instruction supply at the front-end and to improve processor performance. In these approaches, one of the most important factors has been the reduction in the number of instruction cache misses. By using the number of instruction cache misses or derived factors, previous studies have explained the performance improvements achieved by their proposed methods. However, we found that the number of instruction cache misses does not always explain performance changes well in modern processors. This is because the front-end in modern processors handles subsequent instruction cache misses in overlap with earlier ones. Based on this observation, we propose a novel factor: the number of miss regions. We define a region as a sequence of instructions from one branch misprediction to the next, while we define a miss region as a region that contains one or more instruction cache misses. At the boundary of each region, the pipeline is flushed owing to a branch misprediction. Thus, cache misses after this boundary are not handled in overlap with cache misses before the boundary. As a result, the number of miss regions is equal to the number of cache misses that are processed without overlap. In this paper, we demonstrate that the number of miss regions can well explain the variation in performance through mathematical models and simulation results. The results show that the model explains cycles per instruction with an average error of 1.0% and maximum error of 4.1% when applying an existing prefetcher to the instruction cache. The idea of miss regions highlights that instruction cache misses and branch mispredictions interact with each other in processors with a decoupled front-end. We hope that considering this interaction will motivate the development of fast performance estimation methods and new microarchitectural methods.

Annealing computation has recently attracted attention as it can efficiently solve combinatorial optimization problems using an Ising spin-glass model. Stochastic cellular automata annealing (SCA) is a promising algorithm that can realize fast spin-update by utilizing its parallel computing capability. However, in SCA, pinning effect control to suppress the spin-flip probability is essential, making escaping from local minima more difficult than serial spin-update algorithms, depending on the problem. This paper proposes a novel approach called APC-SCA (Autonomous Pinning effect Control SCA), where the pinning effect can be controlled autonomously by focusing on individual spin-flip. The evaluation results using max-cut, N-queen, and traveling salesman problems demonstrate that APC-SCA can obtain better solutions than the original SCA that uses pinning effect control pre-optimized by a grid search. Especially in solving traveling salesman problems, we confirm that the tour distance obtained by APC-SCA is up to 56.3% closer to the best-known compared to the conventional approach.

The Order/Radix Problem (ORP) is an optimization problem that can be solved to find an optimal network topology in distributed memory systems. It is important to find the optimum number of switches in the ORP. In the case of a regular graph, a good estimation of the preferred number of switches has been proposed, and it has been shown that simulated annealing (SA) finds a good solution given a fixed number of switches. However, generally the optimal graph does not necessarily satisfy the regular condition, which greatly increases the computational costs required to find a good solution with a suitable number of switches for each case. This study improved the new method based on SA to find a suitable number of switches. By introducing neighborhood searches in which the number of switches is increased or decreased, our method can optimize a graph by changing the number of switches adaptively during the search. In numerical experiments, we verified that our method shows a good approximation for the best setting for the number of switches, and can simultaneously generate a graph with a small host-to-host average shortest path length, using instances presented by Graph Golf, an international ORP competition.