The direction of arrival (DOA) estimation in array signal processing is an important research area. The effectiveness of the direction of arrival greatly determines the performance of multi-input multi-output (MIMO) antenna systems. The multiple signal classification (MUSIC) algorithm, which is the most canonical and widely used subspace-based method, has a moderate estimation performance of DOA. However, in hybrid massive MIMO systems, the received signals at the antennas are not sent to the receiver directly, and spatial covariance matrix, which is essential in MUSIC algorithm, is thus unavailable. Therefore, the spatial covariance matrix reconstruction is required for the application of MUSIC in hybrid massive MIMO systems. In this article, we present a quantum algorithm for MUSIC-based DOA estimation in hybrid massive MIMO systems. Compared with the best-known classical algorithm, our quantum algorithm can achieve an exponential speedup on some parameters and a polynomial speedup on others under some mild conditions. In our scheme, we first present the quantum subroutine for the beam sweeping based spatial covariance matrix reconstruction, where we implement a quantum singular vector transition process to avoid extending the steering vectors matrix into the Hermitian form. Second, a variational quantum density matrix eigensolver (VQDME) is proposed for obtaining signal and noise subspaces, where we design a novel objective function in the form of the trace of density matrices product. Finally, a quantum labeling operation is proposed for the direction of arrival estimation of the signal.
翻译:在阵列信号处理中,抵达估计方向是一个重要的研究领域。抵达方向的效力决定了多投入多输出(MIMO)天线系统的性能。多信号分类(MUSIC)算法,这是最直接和广泛使用的亚空基方法,具有DA的适度估计性能。然而,在混合大型的MIMO系统中,天线接收到的信号没有直接发送给接收者,因此,在MUSICI算法中至关重要的空间变异矩阵,因此无法提供。因此,在混合大型MIMO系统中应用多投入多输出多输出(MUSIC)天线系统的性能。在本文章中,我们为基于MUSICE的多信号分类(MIS)算算算法在混合大型MIMIMO系统中,提出了基于MUSICE的D值估计值算法。与最著名的经典算法相比,我们的量算法可以在某些参数上实现指数加速,而在一些温和的条件下,对其它的测算法,我们首先为基于空间变异性矩阵的量基体运行空间变缩缩缩缩缩缩缩缩缩缩缩缩缩缩缩缩缩缩缩缩缩缩缩缩缩缩缩缩缩缩缩缩缩缩缩缩缩图。我们把缩缩缩缩缩缩缩缩缩缩缩缩缩缩缩缩缩缩缩缩缩缩缩缩缩图。