Abstract
Reconfigurable intelligent surfaces (RISs) are an emerging technology for future wireless communication. The vast majority of recent research on RIS has focused on system level optimizations. However, developing straightforward and tractable electromagnetic models that are suitable for RIS aided communication modeling remains an open issue. In this paper, we address this issue and derive communication models by using rigorous scattering parameter network analysis. We also propose new RIS architectures based on group and fully connected reconfigurable impedance networks that can adjust not only the phases but also the magnitudes of the impinging waves, which are more general and more efficient than conventional single connected reconfigurable impedance network that only adjusts the phases of the impinging waves. In addition, the scaling law of the received signal power of an RIS aided system with reconfigurable impedance networks is also derived. Compared with the single connected reconfigurable impedance network, our group and fully connected reconfigurable impedance network can increase the received signal power by up to 62%, or maintain the same received signal power with a number of RIS elements reduced by up to 21%. We also investigate the proposed architecture in deployments with distance-dependent pathloss and Rician fading channel, and show that the proposed group and fully connected reconfigurable impedance networks outperform the single connected case by up to 34% and 48%, respectively.
Highlights
R ECONFIGURABLE intelligent surfaces (RISs), known as intelligent reflecting surfaces, have gained popularity as a revolutionary technology for achieving spectrum efficient, energy efficient, and cost effective wireless communication [1], [2], [3]
Given the same received signal power, it is shown that using fully connected and group connected reconfigurable impedance networks can reduce the number of RIS elements by up to 21%, which is beneficial for reducing the cost and area of RIS, especially when the number of RIS elements is large
Given the same average received signal power, the number of RIS elements required by the group connected or fully connected reconfigurable impedance network is less than that required by the single connected reconfigurable impedance network
Summary
R ECONFIGURABLE intelligent surfaces (RISs), known as intelligent reflecting surfaces, have gained popularity as a revolutionary technology for achieving spectrum efficient, energy efficient, and cost effective wireless communication [1], [2], [3]. We derive a straightforward and tractable yet EM based RIS aided communication model using a rigorous scattering parameter network analysis It has been inspired by previous results on MIMO antennas [37] and here it is extended to RIS. We propose efficient RIS architectures, namely fully connected and group connected reconfigurable impedance networks, to improve the received signal power. We investigate the RIS architecture and propose two new architectures based on fully connected and group connected reconfigurable impedance networks, that are respectively modeled using complex symmetric unitary and block diagonal matrices with each block being complex symmetric unitary. Given the same received signal power, it is shown that using fully connected and group connected reconfigurable impedance networks can reduce the number of RIS elements by up to 21%, which is beneficial for reducing the cost and area of RIS, especially when the number of RIS elements is large. Means that B − A is positive semi-definite. diag(a1, ..., aN ) refers to a diagonal matrix with diagonal elements being a1, ..., aN . diag(A1, ..., AN ) refers to a block diagonal matrix with blocks being A1, ..., AN
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
