Deep Residual Learning-Assisted Channel Estimation in Ambient Backscatter Communications

Channel estimation is a challenging problem for realizing efficient ambient backscatter communication (AmBC) systems. In this letter, channel estimation in AmBC is modeled as a denoising problem and a convolutional neural network-based deep residual learning denoiser (CRLD) is developed to directly recover the channel coefficients from the received noisy pilot signals. To simultaneously exploit the spatial and temporal features of the pilot signals, a novel three-dimension (3D) denoising block is specifically designed to facilitate denoising in CRLD. In addition, we provide theoretical analysis to characterize the properties of the proposed CRLD. Simulation results demonstrate that the performance of the proposed method approaches the performance of the optimal minimum mean square error (MMSE) estimator with perfect statistical channel correlation matrix.Comment: 5 pages, 5 figures, Submitted to IEEE Wireless Communications Letter

Enhancing Ambient Backscatter Communication Utilizing Coherent and Non-Coherent Space-Time Codes

Ambient backscatter communication (AmBC) leverages the existing ambient radio frequency (RF) environment to implement communication with battery-free devices. The key challenge in the development of AmBC is the very weak RF signals backscattered by the AmBC Tag. To overcome this challenge, we propose the use of space-time codes by incorporating multiple antennas at the Tag. Our approach considers both coherent and non-coherent space-time codes so that systems with and without Channel State Information can be considered. To allow the application of space-time codes, we propose an approximate linearized and normalized multiple-input multiple-output (MIMO) channel model for the AmBC system. Such MIMO channel model is shown to be accurate for a wide range of useful operating conditions. Two coherent detectors and a non-coherent detector are also provided based on the proposed channel. Simulation results show that enhanced bit error rate performance can be achieved, demonstrating the benefit of using multiple Tag or Reader antennas to leverage the diversity gain. The results are restricted to two antennas at the Tag, to maintain compact size by using polarization diversity and maintain a multiplexing gain of unity, but the results can easily be extended to more than two antennas.Comment: 27 pages, 8 figure