Yasuhiro Oda’s research while affiliated with NTT DOCOMO and other places

Extreme-high-speed communication exceeding 100 Gbps is one requirement for 6G. To satisfy extreme-high-speed-communication, one solution is to utilize terahertz bands above 100 GHz. To determine the new radio-interface technologies and service frequency bands for 6G, terahertz propagation characteristics above 100 GHz need to be understood. In this paper, we introduce our new radio-network topology for 6G and then show the frequency dependency of key propagation phenomena such as the characteristics of path loss in an urban environment, human blockage, and scattering from a rough building surface up to 150 GHz. Human blockage loss increases and the scattering is more diffused as the frequency increases. In the path-loss characteristics, it was found that path-loss frequency dependency is stronger than that given by conventional path-loss model because of scattering effects from a rough building surface.

The super-high-frequency (SHF) band is used in the 5th generation mobile communication system (5G), and the introduction of massive multiple-input multiple-output (MIMO) to 5G is being considered. In an environment with substantial propagation loss, such as that in the case of millimeter waves, massive MIMO can realize beamforming according to the position of terminal stations. Therefore, it is important to understand the direction of arrival of millimeter waves. In this paper, we clarify the relationship between power, delay time, and direction of arrival, while focusing on the horizontal direction, using a 48-element massive array in the 20-GHz band in urban Japan. In addition, we obtain direction of arrival estimation results using an iterative reduction threshold algorithm (ISTA), which is based on compressed sensing. It is shown that the dominant path can be estimated by using the ISTA even with approximately five elements.

In the 5th generation mobile communication system, introduction of small cells using low-height base station is being examined. Small cells are installed in urban street cell environments where mobiles are densely populated. Therefore, actual measurement and complicated modeling of radio wave propagation are necessary to grasp the propagation characteristics. In this paper, a simple propagation delay estimation method is proposed. In the proposed method, neural network using urban area structure parameters is applied. It is shown that the propagation delay time can be easily estimated by the proposed method without considering moving objects and trees.