A multibeam massive multiple input multiple output (MIMO) configuration employs beam selection with high power in the analog part and executes a blind algorithm such as the independent component analysis (ICA), which does not require channel state information in the digital part. Two-dimensional (2-D) multibeams are considered in actual power losses and beam steering errors regarding the multibeam patterns. However, the performance of these 2-D beams depends on the beam pattern of the multibeams, and they are not optimal multibeam patterns suitable for multibeam massive MIMO configurations. In this study, we clarify the performance difference due to the difference of the multibeam pattern and consider the multibeam pattern suitable for the system condition. Specifically, the optimal multibeam pattern was determined with the element spacing and beamwidth of the element directivity as parameters, and the effectiveness of the proposed method was verified via computer simulations.

In 2015, the Ministry of Land, Infrastructure and Transportation started to provide information on aircraft flying over Japan, called CARATS Open Data, and to promote research on aviation systems actively. The airspace is divided into sectors, which are used for limiting air traffic to control safely and efficiently. Since the demand for air transportation is increasing, new optimization techniques and efficient control have been required to predict and resolve demand-capacity imbalances in the airspace. In this paper, we aim to construct mathematical models of the inter-sector air traffic flow from CARATS Open Data. In addition, we develop methods to predict future sector demand. Accuracy of the prediction is evaluated by comparison between predicted sector demand and the actual data.

A surrogate-based electromagnetic (EM) optimization using neural networks (NNs) is presented for computationally efficient microwave bandpass filter (BPF) design. This paper first describes the forward problem (EM analysis) and the inverse problems (EM design), and the two fundamental issues in BPF designs. The first issue is that the EM analysis is a time-consuming task, and the second one is that EM design highly depends on the structural optimization performed with the help of EM analysis. To accelerate the optimization design, two surrogate models of forward and inverse models are introduced here, which are built with the NNs. As a result, the inverse model can instantaneously guess initial structural parameters with high accuracy by simply inputting synthesized coupling-matrix elements into the NN. Then, the forward model in conjunction with optimization algorithm enables designers to rapidly find optimal structural parameters from the initial ones. The effectiveness of the surrogate-based EM optimization is verified through the structural designs of a typical fifth-order microstrip BPF with multiple couplings.

The colors of objects in natural images are affected by the color of lighting, and accurately estimating an illuminant's color is indispensable in analyzing scenes lit by colored lightings. Recent lighting environments enhance colorfulness due to the spread of light-emitting diode (LED) lightings whose colors are flexibly controlled in a full visible spectrum. However, existing color estimations mainly focus on the single illuminant of normal color ranges. The estimation of multiple illuminants of unusual color settings, such as blue or red of high chroma, has not been studied yet. Therefore, new color estimations should be developed for multiple illuminants of various colors. In this article, we propose a color estimation for LED lightings using Color Line features, which regards the color distribution as a straight line in a local area. This local estimate is suitable for estimating various colors of multiple illuminants. The features are sampled at many small regions in an image and aggregated to estimate a few global colors using supervised learning with a convolutional neural network. We demonstrate the higher accuracy of our method over existing ones for such colorful lighting environments by producing the image dataset lit by multiple LED lightings in a full-color range.

We have fabricated two-tiered heterostructures consisting of phosphorus δ-doped Si quantum dots (Si-QDs) and undoped Si-QDs and studied their electron field emission properties. Electron emission was observed from the P-doped Si-QDs stack formed on the undoped Si-QDs stack by applying a forward bias of ∼6 V, which was lower than that for pure Si-QDs stack. This result is attributed to electric field concentration on the upper P-doped Si-QD layers beneath the layers of the undoped Si-QDs stack due to the introduction of phosphorus atom into the Si-QDs, which was positively charged due to the ionized P donor. The results lead to the development of planar-type electron emission devices with a low-voltage operation.

In this manuscript, we propose a joint channel and power assignment algorithm for an unmanned aerial vehicle (UAV) swarm communication system based on multi-agent deep reinforcement learning (DRL). Regarded as an agent, each UAV to UAV (U2U) link can choose the optimal channel and power according to the current situation after training is successfully completed. Further, a mixing network is introduced based on DRL, where Q values of every single agent are non-linearly mapped, and we call it the QMIX algorithm. As it accesses state information, QMIX can learn to enrich the joint action value function. The proposed method can be used for both unicast and multicast scenarios. Experiments show that each U2U link can be trained to meet the constraints of UAV communication and minimize the interference to the system. For unicast communication, the communication rate is increased up to 15.6% and 8.9% using the proposed DRL method compared with the well-known random and adaptive methods, respectively. For multicast communication, the communication rate is increased up to 6.7% using the proposed QMIX method compared with the DRL method and 13.6% using DRL method compared with adaptive method. Besides, the successful transmission probability can maintain a high level.

GaN microwave monolithic integrated circuit (MMIC) power amplifiers (PAs) technologies for millimeter-wave (mm-wave) applications are reviewed in this paper. In the mm-wave band, GaN PAs have achieved high-output power as much as traveling wave tube amplifiers used in satellite communications. Additionally, GaN PAs have been integrated enough to be used for 5G and Beyond-5G. In this paper, a high accuracy large-signal GaN-HEMT modeling technique including the trapping effects is introduced in mm-waves. The prototyped PAs designed with the novel modeling technique have achieved RF performance comparable to that of the state-of-the-art GaN PAs in mm-wave.

Logical matrices are binary matrices often used to represent relations. In the map folding problem, each folded state corresponds to a unique partial order on the set of squares and thus could be described with a logical matrix. The logical matrix representation is powerful than graphs or other common representations considering its association with category theory and homology theory and its generalizability to solve other computational problems. On the application level, such representations allow us to recognize map folding intuitively. For example, we can give a precise mathematical description of a folding process using logical matrices so as to solve problems like how to represent the up-and-down relations between all the layers according to their adjacency in a flat-folded state, how to check self-penetration, and how to deduce a folding process from a given order of squares that is supposed to represent a folded state of the map in a mathematical and natural manner. In this paper, we give solutions to these problems and analyze their computational complexity.

Couplers in a film-type capacitive wireless power charging (CWC) system for an implantable medical device were designed and analyzed in this work. Due to the high conductivity of the human body, two paths contribute to the power transmission, namely a high-frequency current and an electric field. This was confirmed by an equivalent circuit of the system. During analysis of the system, we used pig skin with subcutaneous fat, which has a high affinity with the human body, to search for a highly efficient electrode shape. Subsequently, we fabricated the designed coupler and measured ηmax. An ηmax of 56.6% was obtained for a half-circular coupler with a radius of 20 mm and a distance of 10 mm between adjacent couplers. This study will contribute to the realization of implantable devices that can be recharged during breaks or while sleeping at home and is expected to significantly reduce the burden on patients.

This paper proposes a topology of high power, MHz-frequency, half-bridge resonant inverter ideal for low-loss Gallium Nitride high electron mobility transistor (GaN-HEMT). General GaN-HEMTs have drawback of low drain-source breakdown voltage. This property has prevented conventional high-frequency series resonant inverters from delivering high power to high resistance loads such as 50Ω, which is typically used in radio frequency (RF) systems. High resistance load causes hard-switching also and reduction of power efficiency. The proposed topology overcomes these difficulties by utilizing a proposed ‘L-S network’. This network is effective combination of a simple impedance converter and a series resonator. The proposed topology provides not only high power for high resistance load but also arbitrary design of output wattage depending on impedance conversion design. In addition, the current through the series resonator is low in the L-S network. Hence, this series resonator can be designed specifically for harmonic suppression with relatively high quality-factor and zero reactance. Low-distortion sinusoidal 3kW output is verified in the proposed inverter at 13.56MHz by computer simulations. Further, 99.4% high efficiency is achieved in the power circuit in 471W experimental prototype.

In this paper, we propose a new algorithm to generate Speech-like Emotional Sound (SES). Emotional expressions may be the most important factor in human communication, and speech is one of the most useful means of expressing emotions. Although speech generally conveys both emotional and linguistic information, we have undertaken the challenge of generating sounds that convey emotional information alone. We call the generated sounds “speech-like,” because the sounds do not contain any linguistic information. SES can provide another way to generate emotional response in human-computer interaction systems. To generate “speech-like” sound, we propose employing WaveNet as a sound generator conditioned only by emotional IDs. This concept is quite different from the WaveNet Vocoder, which synthesizes speech using spectrum information as an auxiliary feature. The biggest advantage of our approach is that it reduces the amount of emotional speech data necessary for training by focusing on non-linguistic information. The proposed algorithm consists of two steps. In the first step, to generate a variety of spectrum patterns that resemble human speech as closely as possible, WaveNet is trained with auxiliary mel-spectrum parameters and Emotion ID using a large amount of neutral speech. In the second step, to generate emotional expressions, WaveNet is retrained with auxiliary Emotion ID only using a small amount of emotional speech. Experimental results reveal the following: (1) the two-step training is necessary to generate the SES with high quality, and (2) it is important that the training use a large neutral speech database and spectrum information in the first step to improve the emotional expression and naturalness of SES.

We introduce a new type of exponentiation algorithm in GF(2m) using Euclidean inversion. Our approach is based on the fact that Euclidean inversion cost much less logic gates than ordinary multiplication in GF(2m). By applying signed binary form of the exponent instead of classic binary form, the proposed algorithm can reduce the number of operations further compared with the classic algorithms.

The r-th nonlinearity of Boolean functions is an important cryptographic criterion associated with higher order linearity attacks on stream and block ciphers. In this paper, we tighten the lower bound of the second-order nonlinearity of a class of Boolean function over finite field F2n, fλ(x)=Tr(λxd), where λ∈F*2r, d=22r+2r+1 and n=7r. This bound is much better than the lower bound of Iwata-Kurosawa.

S-box is one of the core components of symmetric cryptographic algorithms, but differential distribution table (DDT) is an important tool to research some properties of S-boxes to resist differential attacks. In this paper, we give a relationship between the sum-of-squares of DDT and the sum-of-squares indicator of (n, m)-functions based on the autocorrelation coefficients. We also get some upper and lower bounds on the sum-of-squares of DDT of balanced (n, m)-functions, and prove that the sum-of-squares of DDT of (n, m)-functions is affine invariant under affine affine equivalent. Furthermore, we obtain a relationship between the sum-of-squares of DDT and the signal-to-noise ratio of (n, m)-functions. In addition, we calculate the distributions of the sum-of-squares of DDT for all 3-bit S-boxes, the 4-bit optimal S-boxes and all 302 balanced S-boxes (up to affine equivalence), data experiments verify our results.

This paper studies generalized variants of the MAXIMUM INDEPENDENT SET problem, called the MAXIMUM DISTANCE-d INDEPENDENT SET problem (MaxDdIS for short). For an integer d≥2, a distance-d independent set of an unweighted graph G=(V, E) is a subset S⊆V of vertices such that for any pair of vertices u, v∈S, the number of edges in any path between u and v is at least d in G. Given an unweighted graph G, the goal of MaxDdIS is to find a maximum-cardinality distance-d independent set of G. In this paper, we analyze the (in)approximability of the problem on r-regular graphs (r≥3) and planar graphs, as follows: (1) For every fixed integers d≥3 and r≥3, MaxDdIS on r-regular graphs is APX-hard. (2) We design polynomial-time O(rd-1)-approximation and O(rd-2/d)-approximation algorithms for MaxDdIS on r-regular graphs. (3) We sharpen the above O(rd-2/d)-approximation algorithms when restricted to d=r=3, and give a polynomial-time 2-approximation algorithm for MaxD3IS on cubic graphs. (4) Finally, we show that MaxDdIS admits a polynomial-time approximation scheme (PTAS) for planar graphs.

We studied whether a statement similar to the Ghouila-Houri's theorem might hold for alternating orientations of cocomparability graphs. In this paper, we give the negative answer. We prove that it is NP-complete to decide whether a cocomparability graph has an orientation that is alternating and acyclic. Hence, cocomparability graphs with an acyclic alternating orientation form a proper subclass of alternately orientable cocomparability graphs. We also provide a separating example, that is, an alternately orientable cocomparability graph such that no alternating orientation is acyclic.

A grid drawing of a plane graph G is a drawing of G on the plane so that all vertices of G are put on plane grid points and all edges are drawn as straight line segments between their endpoints without any edge-intersection. In this paper we give a linear-time algorithm to find a grid drawing of any given 5-connected plane graph G with five or more vertices on the outer face. The size of the drawing satisfies W + H≤n - 2, where n is the number of vertices in G, W is the width and H is the height of the grid drawing.

The Graph Coloring Problem (GCP) is a fundamental combinatorial optimization problem that has many practical applications. Degree of SATURation (DSATUR) and Recursive Largest First (RLF) are well known as typical solution construction algorithms for GCP. It is necessary to update the vertex degree in the subgraph induced by uncolored vertices when selecting vertices to be colored in both DSATUR and RLF. There is an issue that the higher the edge density of a given graph, the longer the processing time. The purposes of this paper are to propose a degree updating method called Adaptive Degree Updating (ADU for short) that improves the issue, and to evaluate the effectiveness of ADU for DSATUR and RLF on DIMACS benchmark graphs as well as random graphs having a wide range of sizes and densities. Experimental results show that the construction algorithms with ADU are faster than the conventional algorithms for many graphs and that the ADU method yields significant speed-ups relative to the conventional algorithms, especially in the case of large graphs with higher edge density.

Hierarchical ID-based authenticated key exchange (HID-AKE) is a cryptographic protocol to establish a common session key between parties with authentication based on their IDs with the hierarchical delegation of key generation functionality. All existing HID-AKE schemes are selective ID secure, and the only known standard model scheme relies on a non-standard assumption such as the q-type assumption. In this paper, we propose a generic construction of HID-AKE that is adaptive ID secure in the HID-eCK model (maximal-exposure-resilient security model) without random oracles. One of the concrete instantiations of our generic construction achieves the first adaptive ID secure HID-AKE scheme under the (standard) k-lin assumption in the standard model. Furthermore, it has the advantage that the computational complexity of pairing and exponentiation operations and the communication complexity do not depend on the depth of the hierarchy. Also, the other concrete instantiation achieves the first HID-AKE scheme based on lattices (i.e., post-quantum).