DNN-DANM: A High-Accuracy Two-Dimensional DOA Estimation Method Using Practical RIS

Reconfigurable intelligent surface (RIS) or intelligent reflecting surface (IRS) has been an attractive technology for future wireless communication and sensing systems. However, in the practical RIS, the mutual coupling effect among RIS elements, the reflection phase shift, and amplitude errors will degrade the RIS performance significantly. This article investigates the two-dimensional direction-of-arrival (DOA) estimation problem in the scenario using a practical RIS. After formulating the system model with the mutual coupling effect and the reflection phase/amplitude errors of the RIS, a novel DNN-DANM method is proposed for the DOA estimation by combining the deep neural network (DNN) and the decoupling atomic norm minimization (DANM). The DNN step reconstructs the received signal from the one with RIS impairments, and the DANM step exploits the signal sparsity in the two-dimensional spatial domain. Additionally, a semi-definite programming (SDP) method with low computational complexity is proposed to solve the atomic minimization problem. Finally, both simulation and prototype are carried out to show estimation performance, and the proposed method outperforms the existing methods in the two-dimensional DOA estimation with low complexity in the scenario with practical RIS.

I. Introduction

Reconfigurable intelligent surface (RIS) or intelligent reflecting surface (IRS) has been an attractive technology to improve the efficiency of spectrum and energy with a low-cost feature, and can control reflected signals and provide a configurable wireless propagation environment [1], [2], [3]. Usually, the RIS is composed of multiple elements, and each element can control the amplitude or phase of the reflected signals. The RIS is a passive plane with a varactor diode and metamaterial structure without high-cost radio-frequency (RF) [4], [5]. Recently, an active RIS is also proposed by adding a power supply to provide additional reflection gain [6]. The RIS can be used to improve wireless communication and sensing performance: •

For wireless communication applications, an IRS-aided communication system is proposed in [7] to achieve transmitting diversity and passive beamforming. Two-sided cooperative IRSs are introduced in a low-earth orbit (LEO) satellite communication [8] to improve the achievable rate.

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For the applications of sensing targets, the RIS can provide an additional path from targets to a sensor [9], [10], especially in the non-line-of-sight (NLOS) scenario. With the improved coverage, the RIS-based radar system is developed in [11] to sense the targets. In [12], [13], a RIS-aided localization for near and far filed is formulated, where the localization performance is improved significantly by the RIS. Additionally, a Swendsen-Wang sampling-based method is proposed in [14] to optimize the RIS scanning channels for the target localization.