Improving Cooperative Wi-Fi Broadcast with Fine-Grained Channel Estimation

Cooperative broadcast is an efficient approach to improve Wi-Fi broadcast performance in a crowded scenario with densely deployed access points (APs). However, the current concurrent transmission MAC protocols cannot synchronize multi-APs’ signals perfectly for all users. As a result, the superimposed signal from APs is time-varying at the users due to the multiple time-domain channels and carrier frequency offsets (CFOs) from multiple APs. The traditional channel estimation approach that estimates the superimposed channel as a whole is ill-suited for the superimposed signal. In this paper, we propose a fine-grained channel estimation approach to first estimate these channel parameters for each AP, and then reconstruct the superimposed channel. Specifically, we present a two-stage channel estimation algorithm that first estimates the CFOs by discretizing the CFO range and matching the most possible CFOs, and then computes the time-domain channels. Experiment and simulation results show the new channel estimation approach achieves much lower bit error rate (BER) and packet error rate (PER) than the traditional IEEE 802.11 approach. In addition, we propose a distributed mechanism to choose the master AP that initializes multi-APs’ simultaneous transmission, which the current concurrent transmission MAC protocols lack. Network-layer simulation results show that the proposed cooperative broadcast scheme improves the throughput by 64% to 82% compared with the traditional uncooperative broadcast scheme.