Application of compressive sensing in sparse spatial channel recovery for beamforming in mmWave outdoor systems

Abstract

In this paper the use of compressive sensing (CS) to accurately estimate the sparse Power Angle Profile (PAP) of a mmWave propagation channel has been investigated. This scheme is especially attractive for outdoor mmWave applications where large antenna arrays are more likely to be deployed to compensate for high pathloss. Current analogue beamforming techniques such as the codebook based 802.11ad beamforming manifest large beamforming overhead for large antenna arrays of typically 16×16 elements. Measurements in an anechoic chamber were performed to demonstrate the applicability of CS to mmWave PAP estimation. The impact of noise on the estimation of Directions-of-Departure (DoD) using CS theory is analysed and finally the benefit of exploiting the reconstructed PAP in beamforming is assessed and compared to the beam searching algorithm adopted in the IEEE 802.11ad standard.