This paper proposes the use of two transmit and two receive antennas spaced at roughly the width of a human body to improve communication quality in the presence of shadowing by a human body in the 60GHz band. In the proposed method, the transmit power is divided between the two transmit antennas, and the receive antenna that provides the maximum receive level is then chosen. Although the receive level is reduced by 3dB, the maximum attenuation caused by human body shadowing is totally suppressed. The relationship between the antenna element spacing and the theoretical spacing based on the 1st. Fresnel zone theory is clarified. Experiments confirm that antenna spacing several centimeters wider than that given by the 1st. Fresnel zone theory is enough to attain a significant performance improvement.

This letter presents the safety confirmation system based on Near Field Communication (NFC) and Ultra High Frequency (UHF) band Radio Frequency IDentification (RFID) tags. Because these RFID tags can operate without the need for internal batteries, the proposed safety confirmation system is effective during large-scale disasters that cause loss of electricity and communication infrastructures. Sharing safety confirmation data between the NFC and UHF band RFID tags was studied to confirm the feasibility of the data sharing. The prototype of the proposed system was fabricated, confirming the feasibility of the proposed safety confirmation system.

In recent years, high-resolution 77 GHz band automotive radar, which is indispensable for autonomous driving, has been extensively investigated. In the future, as vehicle-mounted CS (chirp sequence) radars become more and more popular, intensive inter-radar wideband interference will become a serious problem, which results in undesired miss detection of targets. To address this problem, learning-based wideband interference mitigation method has been proposed, and its feasibility has been validated by simulations. In this paper, firstly we evaluated the trade-off between interference mitigation performance and model training time of the learning-based interference mitigation method in a simulation environment. Secondly, we conducted extensive inter-radar interference experiments by using multiple 77 GHz MIMO (Multiple-Input and Multiple-output) CS radars and collected real-world interference data. Finally, we compared the performance of learning-based interference mitigation method with existing algorithm-based methods by real experimental data in terms of SINR (signal to interference plus noise ratio) and MAPE (mean absolute percentage error).