DoA Estimation for FMCW Radar by 3D-CNN.

A method of direction-of-arrival (DoA) estimation for FMCW (Frequency Modulated Continuous Wave) radar is presented. In addition to MUSIC, which is the popular high-resolution DoA estimation algorithm, deep learning has recently emerged as a very promising alternative. It is proposed in this paper to use a 3D convolutional neural network (CNN) for DoA estimation.

Effects of Thermal Annealing on the Properties of Zirconium-Doped MgZnO Films Obtained through Radio-Frequency Magnetron Sputtering.

Zirconium-doped MgZnO (Zr-doped MZO) mixed-oxide films were investigated, and the temperature sensitivity of their electric and optical properties was characterized. Zr-doped MZO films were deposited through radio-frequency magnetron sputtering using a 4-inch ZnO/MgO/ZrO (75/20/5 wt%) target. Hall measurement, X-ray diffraction (XRD), transmittance, and X-ray photoelectron spectroscopy (XPS) data were obtained.

Mode Selection and Spectrum Allocation in Coexisting D2D and Cellular Networks with Cooperative Precoding.

In this paper, we investigate the mode selection strategies for a new device-to-device (D2D) pair becoming active in a network with a number of existing D2D sensors or users coexisting with cellular users in a D2D-enabled heterogeneous network. Specifically, we propose two selection rules, the signal-to-interference-plus-noise-ratio (SINR)-based and the capacity-based, combined with two sets of different precoding schemes and discuss their impacts on the system under a variety of scenarios. While the cooperative block diagonalization (BD) among the cellular users combined with the zero-forcing (ZF) precoding among D2D users can eliminate interference observed at the new D2D receiving sensor, the maximum signal-to-leakage-and-noise-ratio (SLNR) precoding is often a preferred option due to low-complexity implementations and comparable performance.