Takahiro Hayashi's research while affiliated with KDDI Research and other places
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Publications (37)
In this paper, we propose a method for predicting radio wave propagation using a correlation graph convolutional neural network (C-Graph CNN). We examine what kind of parameters are suitable to be used as system parameters in C-Graph CNN. Performance of the proposed method is evaluated by the path loss estimation accuracy and the computational cost...
In this letter, we propose a learning-based method that uses building map images as spatial data to predict radio wave propagation. We previously proposed a prediction method that uses images around a transmitter (Tx), a receiver (Rx), and their midpoint. The method was accurate but was missing regions between the Tx and the Rx when the distance be...
To realize dynamic spectrum sharing, it is necessary to avoid interference from the secondary system to the primary system. Technical information such as the position of the radio station and the antenna specification of the primary system are required to estimate interference to the primary system accurately, but these specifications are not gener...
In order to improve the efficiency of spectrum use, systems that share spectrum while avoiding interference between different systems are being investigated. In the millimeter-wave band, which is expected to be utilized in the future, the received power fluctuates due to quasi-static obstructions such as people and vehicles, but such temporal varia...
For the efficient use of frequency resources, dynamic spectrum allocation (DSA) between different radio systems is promising. In DSA, our approach is to allow different mobile network operators to use the same shared channel without the inter base station (BS) interference. However, this approach is computationally very expensive. Therefore, we for...
In this paper, we propose a radio propagation prediction method using machine learning and building occupancy estimation. There have been learning-based researches using aerial photographs and building occupancy images as spatial information. However, the availability of building occupancy images are often limited to urban areas. We assume the situ...
A reflectarray with upper sidelobe level (SLL) suppression is proposed for the fifth generation (5G) wireless communications in this letter. A unit cell of the reflectarray is composed of a crossed-dipole element to realize dual-polarized operation. In order to validate the improvement of upper SLL, a 45 degree-beam-steering reflectarray, comprisin...
This paper presents a novel 3-D cuboid array configuration which enables high resolution 2-D DOA estimation. The authors have already proposed a 3-D array configuration which improves the elevation estimation accuracy, but the array configuration cannot estimate DOAs of correlated waves. The proposed cuboid array configuration has almost the same D...
This paper presents a method of synthesizing covariance matrix elements of array input signal for high resolution 2-D Direction-Of-Arrival (DOA) estimation via antenna (sensor) switching. Antenna array generally has the same number of array elements and receiver modules which often leads large receiver hardware cost. Two of the authors have already...
This paper presents a method of synthesizing covariance matrix elements of array input signal for high resolution 2-D Direction-Of- Arrival (DOA) estimation via antenna (sensor) switching. Antenna array generally has the same number of array elements and receiver modules which often leads large receiver hardware cost. Two of the authors have alread...
In this paper, a novel pyramidal shaped antenna configuration for two-dimensional direction-of-arrival estimation is presented. The proposed antenna consists of four sub-arrays and a top antenna for phase reference, and uses four antenna elements in DOA estimation with 4-channel receiver. The performance of 2D-DOA estimation based on sub-arrays of...
This paper presents a simple 3-D array configuration for high-resolution 2-D Direction-Of-Arrival (DOA) estimation. Planar array structures like Uniform Rectangular Array (URA) or Uniform Circular Array (UCA) often well estimate azimuth angle but cannot well estimate elevation angle because of short antenna aperture in elevation direction. One may...
Citations
... We see which feature parameter extracted from spatial data is more appropriate for the path loss estimation. Performance of the proposed method is evaluated in comparison with the FNN-only version of our previous work [11]- [13], using Kokura and Tsudanuma datasets in the propagation database provided by IEICE Technical Committee of Antennas and Propagation [15]. ...
... Maps. An extension to three dimensions can be achieved by directly incorporating the building height or elevation into the CNN input channel [37]. In this context, also the fusion of different input modalities has been studied extensively [38]. ...
... Specifically, the centroid method based on the received signal strength indication (RSSI) of the radio source [6], a method using the angle of arrival and arrival time of the sound source [7], and the location fingerprinting method [8], which utilizes the spatial peculiarity of ripple effects such as the heat source for enlarging the temperature and the radio source for enlarging the RSSI, have been proposed. In these methods, many sensors that measure characteristics such as the strength of the ripple effect are placed uniformly within the observation range in advance, and they inform the sensing data to the data center station via wireless sensor networks (WSN). ...
... As shown in Fig. 1, two types of relay systems for 5G communication have been previously introduced. The first one is based on metasurface reflectors [7], [8]. The reflectors can establish NLoS communication by reflecting the received radio waves toward the user equipment (UE), bypassing the obstacles in the LoS link path. ...
... Procedure of using USS with DSS part of planning, the operator of a 5G system will know "when and where" a USS can be used. In the R&D project, we are studying this technology to forecast future spectrum usage in each location by adopting machine learning [16]. The forecasting is based on measured data obtained from radio sensors and calculation from the propagation model as described in Section 3.2. ...
... This approach enables to manage the inter-base station interference and improves the spectrum efficiency, but the computational complexity increases exponentially with the number of base stations. The other approach is for largescale assignment: grouping is applied to the optimization problem based on the assumption that there is no interference between base stations [23]. This approach can reduce the calculation size of decision variables even if the number of base stations becomes large. ...
... This high value leads to a higher chance of scheduling of the client, since δ i r,n (k) scales b i r,n (k) in the objective function (9). Similarly, an operator i that has not shared much will tend to have a high value of σ i→j (k) (see 12), and this leads to higher chance of sharing by the operator in subsequent periods, since σ i→j (k) scales S i→j r (k) in the objective function (9). ...
... If cooperation between wireless systems is possible, each system can accurately know the radio resource usage using control signals. In [13], the management system that manages and allocates the radio resources used by each wireless system can realize DSS. However, assuming that a variety of wireless systems will be introduced in the future, not all wireless systems can transmit and receive control signals. ...
... We previously extended KDDI's method to estimate building maps from aerial photographs [10]- [13]. Those methods use spatial data around the Tx-Rx midpoint in addition to the Tx and Rx, and the aforementioned machine learning models use a convolutional neural network (CNN) and a fully-connected neural network (FNN). ...
... Multiscale decomposition prediction method for predicting the propagation loss Observation data based Tatsuya Nagao (2020) [44] Complex radio propagation characteristic in mobile communication Gradient Boosting using a plurality of weak learners Applicable only when urban Area Lina Wu (2020) [45] Wireless network loss prediction and optimization Path loss prediction model based on MLP neural network Applicable only when urban Area T. Imai (2019) [46] Radio propagation prediction model using convolutional neural networks (CNN) ...
