Angle of Arrival Based Signal Classification in Intelligent Reflecting Surface-Aided Wireless Communications

Intelligent Reflecting Surface (IRS) has been recognized as a promising technology for future wireless communications. It can reconfigure the radio signal propagation environment and improve the performance of wireless networks. However, this attractive strength of the IRS is grounded on a commonly perceived assumption that the IRS is able to distinguish the incoming signals so that IRS can be controlled to either improve or reduce the total received signal strength at a receiver. The signal differentiation issue for IRS is overlooked in the literature. To tackle this challenge, this paper proposes a solution that integrates an Angle of Arrival (AoA) algorithm into IRS systems. First, we propose a new idea that IRS can work as smart antenna by a hybrid architecture, i.e., all elements are passive except for a few active sensing elements. The active elements can collaboratively serve as a smart antenna. Second, the MUSIC (MUltiple SIgnal Classification) AoA algorithm is applied to this hybrid IRS architecture to classify the incoming signal directions due to its advantages of simple implementation and high resolution. Last, extensive simulations are conducted to evaluate the classification performance of the proposed method under various scenarios. The simulation results demonstrate the effectiveness and accuracy of our approach.