Integrated Super-Resolution Sensing and Communication with Sparse MIMO for Symbiotic Radio

Integrated super-resolution sensing and communication (IS<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup>AC) in symbiotic radio (SR) systems enables highly efficient simultaneous localization and information transmission for both primary and secondary user devices. However, accurate estimation of the two-dimensional (2-D) directions of the backscatter devices (BDs) poses a great challenge when they are densely located. To address this issue, in this paper, we propose a sparse multiple-input multiple-output (MIMO)-based IS<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup>AC SR system with L-shaped nested array (NA) deployed at the base station (BS) to achieve both super-resolution 2-D sensing for multiple secondary BDs and efficient communication for all users. To achieve efficient channel estimation, the elevation and azimuth angles of the primary and secondary users in SR systems are firstly estimated and paired. After that, by matching the paired angles to obtain beamforming gain, the channel gains of both direct and backscatter links are estimated. To evaluate the performance of channel estimation with L-shaped NA, the sum mean square error (MSE) of all channels are analyzed. Simulation results are provided to demonstrate that sparse MIMO can provide significant performance gain than conventional compact MIMO.