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 through simulation.

This letter presents an efficient Signed-Power-of-Two (SPT) term allocation for filter coefficients in order to improve the BER characteristics of digital communication systems. The performance of the present allocation is evaluated by BER characteristics through digital modulation simulations and FPGA-based digital implementation.

This paper presents a simple but high resolution DOA estimation method using second-order differential of MUSIC spectrum. MUSIC method is paid attention as one of "Superresolution" DOA estimation methods because of their brilliant characteristics, however MUSIC also has the problem of estimation accuracy in severe environments like low SNR, small number of snapshots, or incident waves from closely-spaced angles. Especially the case of two or more incident waves from closely-spaced angles, MUSIC often fails in making spectrum peaks that leads inaccurate DOA estimation. We pay attention to the fact that the second-order differential of MUSIC spectrum makes negative peaks around the original DOAs even when MUSIC spectrum does not make peaks there. We try to estimate DOAs not by MUSIC spectrum but by the second-order differential of the MUSIC spectrum, and to find its peaks for being estimated DOAs. The performance of the present method is evaluated in compared with MUSIC and Root-MUSIC methods through computer simulations and experiments.

This paper proposes two accurate source-number estimation methods for array antennas and multi-input multi-output radar. Direction of arrival (DOA) estimation is important in high-speed wireless communication and radar imaging. Most representative DOA estimation methods require the source-number information in advance and often fail to estimate DOAs in severe environments such as those having low signal-to-noise ratio or large transmission-power difference. Received signals are often bandlimited or narrowband signals, so the proposed methods first involves denoising preprocessing by removing undesired components then comparing the original and denoised signal information. The performances of the proposed methods were evaluated through computer simulations.

This paper proposes a novel fast algorithm for the decomposition and reconstruction of two-dimensional (2-D) signals by box splines. The authors have already proposed an algorithm to calculate the discrete box splines which enables the fast reconstruction of 2-D signals (images) from box spline coefficients. The problem still remains in the decomposition process to derive the box spline coefficients from an input image. This paper first investigates the decomposition algorithm which consists of the truncated geometric series of the inverse filter and the steepest descent method with momentum (SDM). The reconstruction process is also developed to correspond to the enlargement of images. The proposed algorithm is tested for the expansion of several natural images. As a result, the peak signal-to-noise ratio (PSNR) of the reconstructed images became more than 50 dB, which can be considered as enough high level. Moreover, the property of box splines are discussed in comparison with 2-D (the tensor product of) B-splines.

This paper presents a framework of multimode fully digital receiver implementation using direct RF-to-digital conversion. In this architecture the entire band including multiple RF systems is directly converted to digital by a wideband high speed ADC, and the RF systems can be easily switched by only digital signal processing with the minimum analog RF components. The digital RF front-end consists of parallel processing blocks for parallel data streams considering practical ADC's configuration. The RF signals are converted into baseband through digital IF stage and the data rates are made down by two steps of decimation. In this paper, a principle investigation into a dualmode system implementation is presented for simplicity. The circuit resource and the robustness to the spurs (spurious outputs) of an NCO (numerically controlled oscillator) in the proposed design will be presented. The proposed architecture was implemented with an FPGA on the developed prototype system and the operations were also verified.

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 studied a way of antenna switching to reduce receiver cost, but it can be applied only for periodic incident signals like sinusoid. In this paper, we propose two simple methods of DOA estimation from sparse data by synthesizing covariance matrix elements of array input signal via antenna switching, which can also be applied to DOA estimation of antiperiodic incident signals. Performance of the proposed approach is evaluated in detail through some computer simulation.

Computing the Eigen Value Decomposition (EVD) of a symmetric matrix is a frequently encountered problem in adaptive (or smart or software) antenna signal processing, for example, super resolution DOA (Direction Of Arrival) estimation algorithms such as MUSIC (MUltiple SIgnal Classification) and ESPRIT (Estimation of Signal Parameters via Rotational Invariance Technique). In this paper the hardware architecture of the fast EVD processor of symmetric correlation matrices for the application of an adaptive antenna technology such as DOA estimation is proposed and the basic idea is also presented. Cyclic Jacobi method is well known for the simplest algorithm and easily implemented but its convergence time is slower than other factorization algorithm like QR-method. But if considering the fast parallel computation of the EVD with a hardware architecture like ASIC (Application Specific Integrated Circuit) or FPGA (Field Programmable Gate Array), the Jacobi method can be a appropriate solution, since it offers a quite higher degree of parallelism and easier implementation than other factorization algorithms. This paper computes the EVD using a Jacobi-type method, where the vector rotations and the angles of the rotations are obtained by CORDIC (COordinate Rotation DIgital Computer). The hardware architecture suitable for ASIC or FPGA with fixed-point arithmetic is presented. Because it consists of only shift and add operations, this hardware friendly feature provides easy and efficient implementation. In this paper, the computational load, the estimate of circuit scale and expected performance are discussed and the validation of fixed-point arithmetic for the practical application to MUSIC DOA estimation is examined.

This paper presents a novel automated microwave filter tuning method based on successive optimization of phase and amplitude characteristics. We develop an optimization procedure to determine how much the adjusting screws of a filter should be rotated. The proposed filter tuning method consists of two stages; coarse and fine tuning stages. In the first stage, called coarse tuning, the phase response error of the target filter is minimized so that the filter roughly approximates almost ideal bandpass characteristics. Then in the second stage, called fine tuning, two different amplitude response errors are minimized in turn and then the resulting filter well approximate the ideal characteristics. Performance of the proposed tuning procedure is evaluated through some experiments of actual filter tuning.