To enhance the throughput performance and reliability of Wi-Fi backscatter communication, we develop a nonsequential link adaptation scheme using repetition codes and voting to obtain the final decoded bit from repeated bits. To address the estimation of channel conditions from limited transmission results, we convert the packet success rate of one coding scheme into that of another via virtual independent and identically distributed bit errors. The packet success rates that would result in equal expected throughputs of different repetition codes are similarly derived and used as code selection thresholds. We prototype the proposed scheme and, via testbed experiments incorporating commercial Wi-Fi receivers, demonstrate the effectiveness of link adaptation using repetition codes and the throughput gain of the proposed scheme over benchmark schemes.

In WiFi backscatter communication, the frequency shift technique allows a backscattered signal to appear not in the frequency channel of the carrier signal but in adjacent ones, thus avoiding noisy OFDM-based carrier signals and increasing the communication range. Through testbed experiments, we observe that frequency shift is effective in mitigating the impact of the inherent fluctuation of WiFi signals, particularly in bistate backscatter communication; however, due to the weak strength of the backscattered signal, other signals from incumbent transmitters may appear in the shifted frequency channels, significantly interfering with the backscattered signal. To combat this challenge in a way that is nondisruptive to incumbent transmitters, we propose a receiver-side spectro-temporal combining scheme in which spectrum combining is performed to suppress interference appearing in one of the shifted channels, while temporal combining is performed with transmission repetitions to suppress bit errors resulting from residual interference. The scheme’s on-the-fly spectrum combining and bit-sequence temporal combining require minimal buffer memory. Through system prototyping and testbed experiments, we demonstrate that the proposed scheme outperforms the conventional and temporal-combining-only cases in terms of the bit error rate and throughput under various conditions.

WiFi backscatter communication has emerged as a promising enabler of ultralow-power connectivity for Internet of things, wireless sensor network and smart energy. In this paper, we propose a multi-filter design for effective decoding of WiFi backscattered signals. Backscattered signals are relatively weak compared to carrier WiFi signals and therefore require algorithms that filter out original WiFi signals without affecting the backscattered signals. Two multi-filter designs for WiFi backscatter decoding are presented: the summation and delimiter approaches. Both implementations employ the use of additional filters with different window sizes to efficiently cut off undesired noise/interference, thus enhancing frame detection and decoding performance, and can be coupled with a wide range of decoding algorithms. The designs are particularly productive in the frequency-shift WiFi backscatter communication. We demonstrate via prototyping and testbed experiments that the proposed design enhances the performance of various decoding algorithms in real environments.

In the Wi-Fi backscatter communication system using temporal combining to enhance communication reliability, we identify an uneven bit reliability problem within a tag packet due to airtime-varying Wi-Fi carrier signals. To address this problem, we propose a position-wise repetition coding framework that assigns different repetition codes to bits based on their positions within a tag packet. We develop three adaptation algorithms to determine the appropriate repetition code for bit blocks according to current channel conditions. Prototyping the framework and algorithms, our testbed experiments with commodity Wi-Fi receivers demonstrate the framework’s effectiveness and the throughput gains achieved by the algorithms.