DOA estimation in MIMO systems with Compressive Sensing for future handsets

Abstract

Future handsets are characterized by their small size which limits the number of antennas and the spacing between them. This paper mainly focuses on Direction-of-Arrival (DOA) estimation in Multiple-Input-Multiple-Output (MIMO) systems based on Compressive Sensing (CS) with practical limitations. The main objective is to strike an optimal balance between complexity and accuracy. A comparison between important DOA estimation algorithms is presented including: Beamforming, Capon, MUSIC, and l1-Singular Value Decomposition (l1-SVD). When considering two antennas with practical antenna spacing limitations, simulation shows that the Root Mean Squared Error (RMSE) of the estimated DOAs is approximately the same for all algorithms in the presence of a single source. The smallest RMSEs are achieved when the spacing between the antennas relative to the wavelength = 1/3. The l1-SVD algorithm is recommended due to the narrow beamwidth and high resolution.