  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%.
