论文标题
Wi-Fi 7及以后
Intelligent Feedback Overhead Reduction (iFOR) in Wi-Fi 7 and Beyond
论文作者
论文摘要
IEEE 802.11基于标准的无线局域网（WLAN）或Wi-Fi网络对于在当今世界提供互联网访问至关重要。 Wi-Fi网络中对高数据速率的需求不断增长，导致了802.11标准的几个进步。支持在更宽的带宽上运行的传输天线的支持MIMO传输是达到更高吞吐量的关键功能之一。但是，由于越来越多的发射天线导致的反馈开销的增加可能会显着遏制吞吐量的增益。在本文中，我们开发了一种基于学习的方法，以减少Wi-Fi Mimo链接中的发声持续时间。仿真结果表明，我们的方法仅使用现有反馈机制所需的位数的大约8％，并且可以将系统吞吐量提高高达52％。
The IEEE 802.11 standard based wireless local area networks (WLANs) or Wi-Fi networks are critical to provide internet access in today's world. The increasing demand for high data rate in Wi-Fi networks has led to several advancements in the 802.11 standard. Supporting MIMO transmissions with higher number of transmit antennas operating on wider bandwidths is one of the key capabilities for reaching higher throughput. However, the increase in sounding feedback overhead due to higher number of transmit antennas may significantly curb the throughput gain. In this paper, we develop an unsupervised learning-based method to reduce the sounding duration in a Wi-Fi MIMO link. Simulation results show that our method uses approximately only 8% of the number of bits required by the existing feedback mechanism and it can boost the system throughput by up to 52%.
