Measurement of Coded Backscatter Communication Utilizing Commercial LTE Ambient Signal

The 3rd Generation Partnership Project (3GPP) has recently undertaken a study on the Ambient Internet of Things (AIo <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$T$</tex>), with a focus on evaluating backscatter communication as a key technique. Several studies on Ambient Backscatter Communications (AmBC) with Long-Term Evolution (LTE) in downlink have shown the feasibility of using the User Equipment (UE) channel estimator as backscatter receiver. In practical deployment scenarios, the backscattered link often suffers from low Signal-to-Noise Ratio (SNR), resulting in a poor Bit Error Rate (BER) performance for un-coded transmissions. This paper proposes to utilize convolutional coding for backscatter links, mirroring the approach used for LTE downlink control signals. It enables to reuse the existing 3GPP specified coding blocks for LTE data channels, at UE for channel estimation and decoding of backscattered signal. To evaluate the performance of proposed scheme, over the air measurements were conducted while using a commercial LTE downlink signals as an ambient source. The performance metrics considered for the analysis are the average Reference Signal Received Power (RSRP) of the LTE carrier, the SNR of the backscattered signal at the UE, and the outage probability. The results presented in this paper indicate that the convolutional channel coding provides a significant gain of approximately 6.3 dB in SNR and reduces the outage probability by at least 11% for a target BER of 0.001, compared to un-coded FSK.