Satoshi Suyama

This paper presents a pilotless transmission scheme that combines a learned constellation with a neural receiver, and validates the approach through over-the-air indoor experiments. Motivated by the need for evidence beyond simulation when applying artificial intelligence/machine learning at the air interface, we first use a channel emulator to establish basic characteristics and to evaluate a wide range of parameters including channel-model family, delay spread, signal-to-noise ratio, and velocity. The channel emulator-based experiments show that the proposed pilotless scheme achieves a block error rate (BLER) generally comparable to a 5G New Radio baseline. As the BLERs converge, eliminating pilots (demodulation-reference signals (DMRSs)) overhead provides the expected throughput gain. Moreover, under strong time- and frequency-selective conditions, the conventional pipeline typically requires DMRS pattern optimization, whereas the proposed neural receiver maintains its performance level without such tuning. We then validate the approach in real indoor channels. Over-the-air measurements in an obstructed room, an open lobby, and a corridor enclosed by walls, floor, and ceiling with partial non-line-of-sight yield throughput gains of 6.5% to 18.2%.

Sub-terahertz (sub-THz) frequencies (100–300 GHz) are expected to play a key role in beyond-5G and 6G mobile networks. However, their quasi-optical propagation characteristics require new channel models beyond sub-100 GHz extrapolations. This paper presents an extensive double-directional (D-D) channel measurement campaign conducted in an outdoor street-canyon environment at 154 GHz and 300 GHz under both line-of-sight (LoS) and non-line-of-sight (NLoS) conditions using an in-house-developed multi-tone frequency-domain channel sounder. Based on these measurements, clustering with merged datasets across the two frequencies enables comparative analyses that identify both common and distinct multipath clusters, as well as the frequency dependence of cluster-level characteristics. A quasi-deterministic (Q-D) channel model is then proposed, combining deterministic components, such as LoS and single-bounce reflections from side walls, with random components. Large-scale parameters (path loss, delay spread, angular spread, and Rician K-factor) are also evaluated. These results provide valuable insights into sub-THz propagation in urban street canyons and contribute toward the development of accurate, channel models for future 6G systems.

Metasurface reflectors and reconfigurable intelligent surfaces (RISs), which are key technologies for robust, high-speed, and high-capacity communications in millimeter-wave bands, can eliminate shadowed areas caused by buildings and moving objects by artificially shaping the propagation environment. Metasurface reflectors are passive devices that can generate reflected waves in desired directions and are expected to be installed on buildings and windows as low-cost, power-free solutions. However, since their reflection angles cannot be adjusted after installation, the improvement in coverage area may be limited. To address this limitation, we propose the concept of building a multipath environment by deploying a massive number of metasurface reflectors on windows and building surfaces. When scaling up such deployments, each metasurface reflector must be individually designed due to variations in the distance and angle relative to the base station and the user equipment, leading to increased design and manufacturing costs. To mitigate this issue, we also propose a method for simplifying the design of the incident and reflection angles for metasurface reflectors. We fabricated prototype metasurface reflectors, each measuring one square meter, and designed them to exhibit specific incident and reflection angle characteristics. These metasurface reflectors were deployed continuously to form a ten-meter-long array, and we experimentally evaluated their angle-of-arrival characteristics in a large-scale setting. We confirmed that the reflected waves arrived from the designed reflection angle at each point within the measurement area.

This study analyzes the actual transmitted power from 5G beamforming radio base stations (BF-RBSs) to clarify the effectiveness and issues of an actual maximum approach specified in the International Electrotechnical Commission 62232:2025. The actual maximum approach is a new compliance assessment method for electromagnetic field exposure levels from BF-RBSs based on time-averaged transmitted power. In this study, the actual maximum transmitted power every 5 or 30 min from more than 400 BF-RBSs using millimeter waves in urban areas in Japan was collected using a network management system over a period of one month. For each BF-RBS, normalized actual transmitted power was derived as the ratio of actual to configured maximum transmitted power. As a result of this measurement, the maximum value of normalized actual transmitted power was approximately −3 dB when the number of sets of user equipment (UEs) in the BF-RBS was less than two with high data traffic. Moreover, statistical analysis results of the measurement data shows that the actual maximum approach may underestimate the electromagnetic field exposure levels from a BF-RBS with three or fewer UEs when the actual transmitted power of the BF-RBSs is not monitored and controlled to maintain a level below the threshold.

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.