Tomoaki Ogawa’s research while affiliated with Nippon Telegraph and Telephone and other places

This paper presents the frequency dependence of the path loss exponent (PLE) based on measurement results of multiple frequency bands in indoor environments and explains the propagation mechanisms that cause frequency dependence. Path loss measurements from 0.8 GHz to 66.5 GHz in two indoor open office environments were used to derive the parameters of a close-in free space reference distance model (CI model) and an alpha-beta-gamma model (ABG model). We revealed that the PLE of the single-frequency CI model tended to decrease with increasing frequency, while the frequency coefficient of the ABG model was smaller than that of the free space loss (FSPL), indicating a different frequency dependence than FSPL in these environments. Furthermore, the propagation mechanisms of the waveguide effect and the first Fresnel zone shielding cause this frequency dependence. Ray-tracing simulations revealed that the PLE becomes large and small in the low- and high-frequency bands, respectively, when the ceiling height is low, consistent with the measurements. The PLE becomes small regardless of the frequency band when the ceiling height is high, indicating frequency dependence along the propagation mechanism in both the ray-tracing simulation and measurement results.

The next generation 6G wireless systems are envisioned to have higher reliability and capacity than the existing cellular systems. The reconfigurable intelligent surfaces (RISs)-assisted wireless networks are one of the promising solutions to control the wireless channel by altering the electromagnetic properties of the signal. The dual connectivity (DC) increases the per-user throughput by utilizing radio resources from two different base stations. In this work, we propose the RIS-assisted DC system to improve the per-user throughput of the users by utilizing resources from two base stations (BSs) in proximity via different RISs. Given an α-fair utility function, the joint resource allocation and the user scheduling of a RIS-assisted DC system is formulated as an optimization problem and the optimal user scheduling time fraction is derived. A heuristic is proposed to solve the formulated optimization problem with the derived optimal user scheduling time fractions. Exhaustive simulation results for coverage and throughput of the RIS-assisted DC system are presented with varying user, BS, blockage, and RIS densities for different fairness values. Further, we show that the proposed RIS-assisted DC system provides significant throughput gain of 52% and 48% in certain scenarios when compared to the existing benchmark and DC systems.

The 6G wireless systems are expected to have higher capacity, reliability, and energy efficiency than the existing cellular systems. Millimeter-wave (mmWave) frequencies offer high capacity at the cost of high attenuation and blockage losses. Reconfigurable intelligent surface (RIS) assisted mmWave networks consist of smaller antenna elements that control the propagation channel between the base station (BS) and the user by appropriately tuning the phase and the reflection of the incident electromagnetic signal. The deployment of RIS is considered to be an energy efficient solution to improve the coverage of regions with high blocking probability. However, if every BS is associated with one or more dedicated RIS, then the density of RIS increases proportionally with the density of BSs. Hence in this work, we propose RIS sharing mechanisms where multiple BSs share one RIS. We formulate resource allocation of RIS sharing in terms of time and the RIS elements as an optimization problem, and we propose heuristics to solve both. Further, we present detailed simulation results to compare time and the element based RIS sharing methods for various scenarios with the benchmark and the RIS system without sharing. The proposed time and element based RIS sharing methods improve throughput upto 53% and 25%, respectively, compared to the RIS system without sharing in specific scenarios.