EliMO: Eliminating Channel Feedback from MIMO

Abstract

MIMO beamforming provides high throughput for WiFi networks, but it also leads to high computation and communication overhead due to Channel State Information (CSI) feedback. Explicit CSI feedback provides high beamforming gains, but it introduces extremely high overhead. Implicit CSI feedback has low overhead, but it provides very low beamforming gains. We propose EliMO to completely Eliminate CSI feedback from MIMO without sacrificing beamforming gains. EliMO uses two-way channel estimation to allow WiFi Access Points (AP) to accurately estimate downlink CSI without explicit CSI feedback. To measure downlink CSI at the WiFi AP, the WiFi station (STA) puts the received signal of downlink training symbols into Feedback Training Field (FTF) and sends it back to the AP. The AP estimates the two-way channel using the received signal of FTF. Analysis and experiment results show that EliMO is able to provide as high beamforming gains as explicit CSI feedback and as low overhead as implicit CSI feedback. EliMO significantly reduces computation and communication costs of measuring and sending CSI feedback for smart devices, like smartphones, smartwatches, and wireless drones. We evaluate the throughput and energy consumption of EliMO by experiment measurements in both static and mobile scenarios. Evaluation results show that EliMO provides 5× and 4× throughput as implicit and explicit CSI feedback, espectively. Energy consumption of EliMO is only 85%/30% of that of implicit/explicit CSI feedback.