Target Sensing With Intelligent Reflecting Surface: Architecture and Performance

Intelligent reflecting surface (IRS) has emerged as a promising technology to reconfigure the radio propagation environment by dynamically controlling wireless signal’s amplitude and/or phase via large number of elements. In contrast vast literature on studying IRS’s performance gains in communications, we study this paper new application IRS for sensing/localizing targets networks. Specifically, propose self-sensing IRS architecture where controller is capable transmitting probing signals that are not only directly reflected target (referred direct echo link), but also consecutively and then IRS-reflected link). Moreover, dedicated sensors installed at receiving both from target, such can sense direction its nearby applying customized multiple signal classification (MUSIC) algorithm. However, since angle estimation mean square error (MSE) MUSIC algorithm intractable, optimize passive reflection maximizing average signals’ total power derive resultant Cramer-Rao bound (CRB) MSE. Last, numerical results presented show effectiveness proposed sensing algorithm, compared other benchmark systems/algorithms.