Time of arrival (TOA) is a widely used wireless cellular network ranging technology. How to perform accurate TOA estimation in multi-path and non-line-of-sight (NLOS) environments and then accurately calculating mobile terminal locations are two critical issues in positioning research. NLOS identification can be performed in the TOA measurement part and the position calculation part. In this paper, for the above two steps, two schemes for mitigating NLOS errors are proposed. First, a TOA ranging method based on clustering theory is proposed to solve the problem of line-of-sight (LOS) path estimation in multi-path channels. We model the TOA range as a Gaussian mixture model and illustrate how LOS and NLOS can be measured and identified based on non-parametric Bayesian methods when the wireless transmission environment is unknown. Moreover, for NLOS propagation channels, this paper proposes a user location estimator based on the maximum a posteriori criterion. Combined with the TOA estimation and user location computation scheme proposed in this paper, the terminal's positioning accuracy is improved. Experiments showed that the TOA measurement and localization algorithms presented in this paper have good robustness in complex wireless environments.

This paper proposes new acoustic feature signatures based on the multiscale fractal dimension (MFD), which are robust against the diversity of environmental sounds, for the content-based similarity search. The diversity of sound sources and acoustic compositions is a typical feature of environmental sounds. Several acoustic features have been proposed for environmental sounds. Among them is the widely-used Mel-Frequency Cepstral Coefficients (MFCCs), which describes frequency-domain features. However, in addition to these features in the frequency domain, environmental sounds have other important features in the time domain with various time scales. In our previous paper, we proposed enhanced multiscale fractal dimension signature (EMFD) for environmental sounds. This paper extends EMFD by using the kernel density estimation method, which results in better performance of the similarity search tasks. Furthermore, it newly proposes another acoustic feature signature based on MFD, namely very-long-range multiscale fractal dimension signature (MFD-VL). The MFD-VL signature describes several features of the time-varying envelope for long periods of time. The MFD-VL signature has stability and robustness against background noise and small fluctuations in the parameters of sound sources, which are produced in field recordings. We discuss the effectiveness of these signatures in the similarity sound search by comparing with acoustic features proposed in the DCASE 2018 challenges. Due to the unique descriptiveness of our proposed signatures, we confirmed the signatures are effective when they are used with other acoustic features.

A method for detecting the timing of photodiode (PD) saturation without using an in-pixel time-to-digital converter (TDC) is proposed. Detecting PD saturation time is an approach to extend the dynamic range of a CMOS image sensor (CIS) without multiple exposures. In addition to accumulated charges in a PD, PD saturation time can be used as a signal related to light intensity. However, in previously reported CISs with detecting PD saturation time, an in-pixel TDC is used to detect and store PD saturation time. That makes the resolution of a CIS lower because an in-pixel TDC requires a large area. As for the proposed pixel circuit, PD saturation time is detected and stored as a voltage in a capacitor. The voltage is read and converted to a digital code by a column ADC after an exposure. As a result, an in-pixel TDC is not required. A signal-processing and calibration method for combining two signals, which are saturation time and accumulated charges, linearly are also proposed. Circuit simulations confirmed that the proposed method extends the dynamic range by 36 dB and its total dynamic range to 95 dB. Effectiveness of the calibration was also confirmed through circuit simulations.

In this paper, we present the transmission characteristics control of a 125 GHz-band split-ring resonator (SRR) bandstop filter by coupling an alignment-free lattice pattern. We demonstrate that the transmission characteristics of the SRR filter can be controlled by coupling the lattice pattern; however, the required accuracy of alignment between the SRR filter and lattice pattern was below 200 µm. Therefore, we designed an alignment-free lattice pattern whose unit cell size is different from that of the SRR unit cell. S21 of the SRR bandstop filter changes from -38.7 to -4.0 dB at 125 GHz by arranging the alignment-free lattice pattern in close proximity to the SRR stopband filter without alignment. A 10 Gbit/s data transmission can be achieved over a 125 GHz-band wireless link by setting the alignment-free lattice pattern substrate just above the SRR bandstop filter.

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.

In this paper, we demonstrate that a formal approach is effective for improving reliability of cooperative robot designs, where the control logics are expressed in concurrent FSMs (Finite State Machines), especially in accordance with the standard FSM4RTC (FSM for Robotic Technology Components), by a case study of cooperative transport robots. In the case study, FSMs are modeled in the formal specification language CSP (Communicating Sequential Processes) and checked by the model-checking tool FDR, where we show techniques for modeling and verification of cooperative robots implemented with the help of the RTM (Robotic Technology Middleware).

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.

To realize an information-centric networking, IPFS (InterPlanetary File System) generates a unique ContentID for each content by applying a cryptographic hash to the content itself. Although it could improve the security against attacks such as falsification, it makes difficult to realize a similarity search in the framework of IPFS, since the similarity of contents is not reflected in the proximity of ContentIDs. To overcome this issue, we propose a method to apply a locality sensitive hash (LSH) to feature vectors extracted from contents as the key of indexes stored in IPFS. By conducting experiments with 10,000 random points corresponding to stored contents, we found that more than half of randomly given queries return a non-empty result for the similarity search, and yield an accurate result which is outside the σ confidence interval of an ordinary flooding-based method. Note that such a collection of random points corresponds to the worst case scenario for the proposed scheme since the performance of similarity search could improve when points and queries follow an uneven distribution.

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.

This paper proposes relay selection techniques for XOR physical layer network coding with MMSE based non-linear precoding in MIMO bi-directional wireless relaying networks. The proposed selection techniques are derived on the different assumption about characteristics of the MMSE based non-linear precoding in the wireless network. We show that the signal to noise power ratio (SNR) is dependent on the product of all the eigenvalues in the channels from the terminals to relays. This paper shows that the best selection techniques in all the proposed techniques is to select a group of the relays that maximizes the product. Therefore, the selection technique is called “product of all eigenvalues (PAE)” in this paper. The performance of the proposed relay selection techniques is evaluated in a MIMO bi-directional wireless relaying network where two terminals with 2 antennas exchange their information via relays. When the PAE is applied to select a group of the 2 relays out of the 10 relays where an antenna is placed, the PAE attains a gain of more than 13dB at the BER of 10-3.

For improving the fifth-generation mobile communication system, a highly efficient power amplifier must be designed for the base station. An outphasing amplifier is expected to be a solution for achieving high efficiency. We designed a combiner, one of the key components of the outphasing amplifier, using a serial Chireix combiner and fabricated an amplifier with a GaN HEMT, achieving 70% or more high efficiency up to 9 dB back-off power in an 800 MHz band. We also fabricated a 2 GHz-band outphasing amplifier with the same design. We applied digital predistortion (DPD) to control the balance of amplifying units in this amplifier and achieved an average efficiency of 65% under a 20 MHz modulation bandwidth.

A practical Doherty amplifier design method has been developed based on an asymmetric configuration scheme. By embedding a load modulation function into matching circuits of a carrier amplifier (CA) and a peaking amplifier (PA) in the Doherty amplifier, an issue of the Doherty amplifier design is boiled down to the CA and PA matching circuit design. The method can be applied to transistors with unknown parasitic elements if optimum termination impedance conditions for the transistor are obtained from a source-/load-pull technique in simulation or measurement. The design method was applied to GaN HEMT Doherty amplifier MMICs. The fabricated 4.5-GHz-band GaN HEMT Doherty amplifier MMIC exhibited a maximum drain efficiency of 66% and a maximum power-added efficiency (PAE) of 62% at 4.1GHz, with a saturation output power of 36dBm. In addition, PAE of 50% was achieved at 4.1GHz on a 7.2-dB output back-off (OBO) condition. The fabricated 8.5-GHz-band GaN HEMT Doherty amplifier MMIC exhibited a maximum drain efficiency of 53% and a maximum PAE of 44% at 8.6GHz, with a saturation output power of 36dBm. In addition, PAE of 35% was achieved at 8.6GHz on a 6.7-dB (OBO). And, the fabricated 12-GHz-band GaN HEMT Doherty amplifier MMIC exhibited a maximum drain efficiency of 57% and a maximum PAE of 52% at 12.4GHz, with a saturation output power of 34dBm. In addition, PAE of 32% was achieved at 12.4GHz on a 9.5-dB (OBO) condition.

With the advent of 5G and external pressure to reduce greenhouse gas emissions, wireless transceivers with low power consumption are strongly desired for future cellular systems. At the same time, increased modulation order due to the evolution of cellular systems will force power amplifiers to operate at much larger output power back-off to prevent EVM degradation. This paper begins with an analysis of load modulation and asymmetrical Doherty amplifiers. Measurement results will show an apparent 60% efficiency plateau for modulated signals with a large peak-to-average power ratio (PAPR). To exceed this efficiency limitation, the second part of this paper focuses on a new amplification topology based on the amalgamation between Doherty and outphasing. Measurement results of the proposed Doherty-outphasing power amplifier (DOPA) will confirm the feasibility of the approach with a modulated efficiency greater than 70% measured at 10 dB output power back-off.

High power amplifier technologies for base transceiver stations (BTSs) for the 5th generation (5G) mobile communication systems and so-called beyond 5G (B5G) systems are reviewed. For sub-6, which is categorized into frequency range 1 (FR1) in 5G, wideband Doherty amplifiers are introduced, and a multi-band load modulation amplifier, an envelope tracking amplifier, and a digital power amplifier for B5G are explained. For millimeter wave 5G, which is categorized into frequency range 2 (FR2), GaAs and GaN MMICs operating at around 28GHz are introduced. Finally, future prospect for THz GaN devices is described.

Research on wireless power transmission technology is being actively conducted, and studies on spatial transmission methods such as SSPS are currently underway for applications such as power transfer to the upper part of steel towers and power transfer to flying objects such as drones. To enable such applications, it is necessary to examine the configuration of the power-transfer and power-receiving antennas and to improve the RF-DC conversion efficiency (hereinafter referred to as conversion efficiency) of the rectifier circuit on the power-receiving antenna. To improve the conversion efficiency, various methods that utilize full-wave rectification rather than half-wave rectification have been proposed. However, these come with problems such as a complicated circuit structure, the need for additional capacitors, the selection of components at high frequencies, and a reduction in mounting yield. In this paper, we propose a method to improve the conversion efficiency by loading a high-impedance microstrip line as a feedback line in part of the rectifier circuit. We analyzed a class-F rectifier circuit using circuit analysis software and found that the conversion efficiency of the conventional configuration was 54.2%, but the proposed configuration was 69.3%. We also analyzed a measuring circuit made with a discrete configuration in the 5.8-GHz band and found that the conversion efficiency was 74.7% at 24dBm input.

The need for real-time use of human dynamics data is increasing. The technical requirements for this include improved databases for handling a large amount of data as well as highly accurate sensing of people's movements. A bitmap index format has been proposed for high-speed processing of data that spreads in a two-dimensional space. Using the same format is expected to provide a service that searches queries, reads out desired data, visualizes it, and analyzes it. In this study, we propose a coding format that enables human dynamics data to compress it in the target data size, in order to save data storage for successive increase of real-time human dynamics data. In the proposed method, the spatial population distribution, which is expressed by a probability distribution, is approximated and compressed using the one-pixel one-byte data format normally used for image coding. We utilize two kinds of approximation, which are accuracy of probability and precision of spatial location, in order to control the data size and the amount of information. For accuracy of probability, we propose a non-linear mapping method for the spatial distribution, and for precision of spatial location, we propose spatial scalable layered coding to refine the mesh level of the spatial distribution. Also, in order to enable additional detailed analysis, we propose another scalable layered coding that improves the accuracy of the distribution. We demonstrate through experiments that the proposed data approximation and coding format achieve sufficient approximation of spatial population distribution in the given condition of target data size.

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.

Effective emergency resource allocation is essential to guarantee a successful emergency disposal, and it has become a research focus in the area of emergency management. Emergency event logs are accumulated in modern emergency management systems and can be analyzed to support effective resource allocation. This paper proposes a novel approach for efficient emergency resource allocation by mining emergency event logs. More specifically, an emergency event log with various attributes, e.g., emergency task name, emergency resource type (reusable and consumable ones), required resource amount, and timestamps, is first formalized. Then, a novel algorithm is presented to discover emergency response process models, represented as an extension of Petri net with resource and time elements, from emergency event logs. Next, based on the discovered emergency response process models, the minimum resource requirements for both reusable and consumable resources are obtained, and two resource allocation strategies, i.e., the Shortest Execution Time (SET) strategy and the Least Resource Consumption (LRC) strategy, are proposed to support efficient emergency resource allocation decision-making. Finally, a chlorine tank explosion emergency case study is used to demonstrate the applicability and effectiveness of the proposed resource allocation approach.

Contamination of water resources with pathogenic microorganisms excreted in human feces is a worldwide public health concern. Surveillance of fecal contamination is commonly performed by routine monitoring for a single type or a few types of microorganism(s). To design a feasible routine for periodic monitoring and to control risks of exposure to pathogens, reliable statistical algorithms for inferring correlations between concentrations of microorganisms in water need to be established. Moreover, because pathogens are often present in low concentrations, some contaminations are likely to be under a detection limit. This yields a pairwise left-censored dataset and complicates computation of correlation coefficients. Errors of correlation estimation can be smaller if undetected values are imputed better. To obtain better imputations, we utilize side information and develop a new technique, the asymmetric Tobit model which is an extension of the Tobit model so that domain knowledge can be exploited effectively when fitting the model to a censored dataset. The empirical results demonstrate that imputation with domain knowledge is effective for this task.