Low-complexity robust beamforming based on conjugate gradient techniques

Abstract

We propose low-complexity robust beamforming algorithms based on the conjugate gradient method and the worst-case optimization based criterion. Unlike the existing robust beamformers based on the worst-case optimization based criterion that use a second-order cone program, the proposed algorithms employ a joint optimization strategy based on low-complexity conjugate gradient algorithms. The proposed algorithms are termed the Robust Constrained Minimum Variance Modified Conjugate Gradient (Robust-CMV-MCG) and the Robust Constrained Constant Modulus Modified Conjugate Gradient (Robust-CCM-MCG), which has an advantage for the special case of constant modulus signals. Simulations show that the performances of the proposed algorithms are equivalent or better than that of existing robust algorithms, whereas the complexity is more than an order of magnitude lower.