Bit error rate (BER) characteristics of Probabilistic Amplitude Shaping system is evaluated with a novel matching improvement operation at an inverse-distribution matcher (DM^-1) using soft information of log-likelihood ratio value as well as an interleaving of multiple BCH (Bose-Chaudhuri-Hocquenghem) codewords used as outer forward error correction (FEC). The obtained results show that the large size interleaver dramatically eliminates BER floor, while the proposed matching improvement operation successfully suppresses the increase in errors due to burst errors occurred in the DM^-1 process and low-density parity-check code (LDPC) process used as an internal FEC.

In this study, we propose a method for generating an angular spectrum using array radar and physiological component analysis. We develop physiological component analysis to separate radar echoes from multiple body positions, where echoes are phase-modulated by propagating pulse waves. Assuming that the pulse wave displacements at multiple body positions are constant multiples of a time-shifted waveform, the method estimates echoes using a simplified mathematical model. We exploit the mainlobe and nulls of the directional patterns of the physiological component analysis to form an angular spectrum. We applied the proposed method to simulated data to demonstrate that it can generate a super-resolution angular spectrum.

When divers rescue people in accidents at sea, they are exposed to dangers such as injuries by obstacles, and so on. If the divers can confirm their position, their rescue activities will become safer. In the previous study, assuming that we specify the positions of the divers performing rescue operations to support their work, we developed a 3D undersea position estimation algorithm communicating between the undersea and the sea surface. However, we did not yet consider the effects and countermeasures of sea waves. In this paper, we indicate the effects of sea waves on the algorithm and investigate wave countermeasures.

LTE-V2X is one of the promising wireless technologies for Vehicle to Everything (V2X), which is expected to enhance the safety of road traffic. In this paper, we propose a radio resource allocation scheme for LTE-V2X Sidelink Mode 3. The reliability of packet transmission is seriously affected by changes in vehicle density. To cope with this issue, our new scheme reuses radio resources efficiently by calculating the range of protection from mutual interference based on the vehicle density. Compared with existing schemes, the proposed scheme successfully maintains a lower error rate of packet transmission regardless of the vehicle density.

A reflectarray with independently controllable beam is proposed for the fifth-generation (5G) communication systems in this letter. A unit cell of the reflectarray is composed of an asymmetrical crossed-dipole element to realize dual-polarized operation. The cross-dipole element is printed by a transparent conductive film on an optically transparent substrate. In order to validate its performance, a 20×10-element (100mm×50mm) reflectarray operating at 28GHz is designed and analyzed numerically. Simulation results demonstrate that the reflectarray can independently control dual-polarized scattering beams and produce expected shaped radiation patterns.

An adaptive decision feedback channel estimation (DFCE) scheme using likelihood value comparisons in single-carrier frequencydomain equalization (SC-FDE) is presented here. Previously, we proposed a DFCE scheme for SC-FDE that realizes adaptive tracking of the channel variations with prior knowledge of the terminal mobilities obtained from moving speed information. However, the adaptive tracking method requires determination of an appropriate forgetting factor of the DFCE using the terminal speed information at the receiver. Thus, in this study, we adaptively control an appropriate forgetting factor that corresponds with the channel variations of the DFCE scheme without prior knowledge of the terminal speed. The novelty of the proposed approach is that the likelihood values for different forgetting factors are calculated from the forward error correction (FEC) decoding results, and the appropriate forgetting factor is then chosen by comparing the likelihood values to adjust to either noise-dominant or time-selectivity-dominant channel. The effectiveness of the proposed scheme is further demonstrated via computer simulations by comparisons with the traditional DFCE using the terminal speed information.

This paper proposes a technique called “Cyclic path switching (CPS)” to improve the transmission performance of iterative linear receivers assisted with the lattice reduction in overloaded MIMO channels. The proposed CPS applies different parameters to the LLL algorithm, one of algorithms for the lattice reduction, in order to prepare two paths in the iterative linear receivers. The CPS cyclically switches the paths in the iteration process of the receiver, which is expected to randomize error bits and to improve the decoding performance in the proposed receiver. The CPS enables the iterative receiver to attain a gain of about 0.5dB at the packet error rate (PER) of 10^-2in a 6×2 MIMO system with the 64 QAM, when the reception process is iterated 50 times, even though the CPS is implemented with little additional computational complexity.

We consider the determination of three-dimensional maps of received signal strength (3D-RSS maps) for disaster-recovery networks enabled by unmanned aerial vehicles (UAVs). In this paper, we extend the existing tensor completion based estimator to propose an efficient new 3D-RSS map estimator. To reduce the sensing route length for the UAV, the proposed method utilizes two approaches for estimating the RSS maps (the tensor completion-based and path-loss-based approaches), depending upon the number of high buildings. We show by simulation experiments that the proposed method can achieve a data-collection time comparable to those of existing methods with a shorter sensing route.

New services can use fog nodes to distribute Internet of Things (IoT) data. To distribute IoT data, we apply the publish/subscribe messaging model to a fog computing system. However, there is a possibility that the user’s private data are distributed without their permission. In this paper, we propose a Table-based Access Control List to protect unnecessary private data distribution. The evaluation results show that the bandwidth usage is reduced by about 40% and the queuing delay of a service fog node is reduced by about 60%.

In this paper, we investigate estimating readers’ emotions during reading comics from bio-signals of brainwave, heartbeat, pupil diameter and gazing point. We collect the bio-signals from 11 subjects while they are reading comics, and ask them to answer a questionnaire after reading comics on raised emotions in seven categories including “pleased”, “excited”, “astonished”, “afraid”, “frustrated”, “sad” and “calm”. For the analysis, we use DNN (Deep Neural Network) as a supervised learning method as well as AE (Autoencoder) as an unsupervised one. The questionnaire responses are taken as the correct labels of the raised emotions for DNN, and used to evaluate the clustering results of them by AE. As the results of the analysis, we obtain a high F-score for each emotion estimation by DNN, and find several clusters dominantly including a particular emotion by AE. It suggests that comic readers’ emotions can be estimated from the bio-signals by both supervised and unsupervised learnings.