  This correspondence presents a novel sensing-assisted sparse channel recovery
approach for massive antenna wireless communication systems. We focus on a
fundamental configuration with one massive-antenna base station (BS) and one
single-antenna communication user (CU). The wireless channel exhibits sparsity
and consists of multiple paths associated with scatterers detectable via radar
sensing. Under this setup, the BS first sends downlink pilots to the CU and
concurrently receives the echo pilot signals for sensing the surrounding
scatterers. Subsequently, the CU sends feedback information on its received
pilot signal to the BS. Accordingly, the BS determines the sparse basis based
on the sensed scatterers and proceeds to recover the wireless channel,
exploiting the feedback information based on advanced compressive sensing (CS)
algorithms. Numerical results show that the proposed sensing-assisted approach
significantly increases the overall achievable rate than the conventional
design relying on a discrete Fourier transform (DFT)-based sparse basis without
sensing, thanks to the reduced training overhead and enhanced recovery accuracy
with limited feedback.
