Recently, wireless local area networks (WLAN) with dense access points (APs) and multi-AP coordination (MAPC) have emerged as promising solutions for enabling coordinated transmission and reducing interference. Several coordination schemes have been proposed for MAPC. Among them, coordinated spatial reuse (C-SR) and coordinated beamforming (C-BF) enable simultaneous transmissions within overlapping basic service sets. However, these schemes involve trade-offs: C-SR offers lower overhead but provides limited signal-to-interference-plus-noise ratio (SINR) gain, whereas C-BF offers significant SINR improvement at the cost of increased overhead. Consequently, the optimal scheme depends on network conditions, such as AP density and user distribution. However, conventional MAPC employs only a single coordination scheme regardless of the situation. Therefore, we propose an adaptive coordination scheme selection method that estimates the expected performance of each scheme by evaluating trade-offs based on environmental information, without relying on channel state information. Simulation results confirm that our scheme selection method outperforms conventional approaches and improves system throughput. The adaptive coordination scheme selection overcomes the performance limitations of conventional MAPC, thereby accelerating the advancement of future WLANs.
Kouki Iizuka, Hiroaki Hashida, Y. Kawamoto et al.· IEEE Transactions on Cogniti...· 0 citations
To enable global connectivity through 6G, the efficient operation of hierarchical satellite networks that integrate geostationary (GEO) and low-earth orbit (LEO) satellites is paramount. A significant challenge in achieving this operational efficiency lies in the dynamic association between the extensive array of LEO satellites and ground stations (GSs). In LEO satellite constellations, accurately estimating the queuing delay experienced by data along end-to-end (E2E) paths is challenging because of the complex interleaving of routing paths from countless sources and destinations. In particular, the satellite-to-ground links, which possess lower transmission capacity than inter-satellite links, often become critical bottlenecks for delay. Therefore, this study focuses on GS traffic loads and mathematically demonstrates, through convexity verification of queuing delays, that minimizing the maximum load effectively reduces the E2E delay. Building on these findings, we propose a novel GS-LEO association method designed to reduce delay while suppressing the maximum GS load with low computational complexity. Simulation results utilizing real-world parameters, including IXP locations and traffic demand distributions, demonstrate that the proposed method achieves lower E2E delay than existing routing approaches while maintaining a significantly lower computational load compared with strict optimization methods.
Kazuma Mashiko, Hiroaki Hashida, Y. Kawamoto et al.· IEEE Transactions on Cogniti...· 0 citations
