Abstract
In this work, intelligent reflecting surfaces (IRSs) are optimized to manipulate signal polarization and improve the uplink performance of a dual-polarized multiple-input multiple-output (MIMO) non-orthogonal multiple access (NOMA) network. By multiplexing subsets of users in the polarization domain, we propose a strategy for reducing the interference load observed in the successive interference cancelation (SIC) process. To this end, dual-polarized IRSs are programmed to mitigate interference impinging at the base station (BS) in unsigned polarizations, in which the optimal set of reflecting coefficients are obtained via conditional gradient method. We also develop an adaptive power allocation strategy to guarantee rate fairness within each subset, in which the optimal power coefficients are obtained via a low-complexity alternate approach. Our results show that all users can reach high data rates with the proposed scheme, substantially outperforming conventional systems.
Highlights
D UAL-POLARIZED antenna arrays are effective for overcoming physical space limitations in multiple-input multiple-output (MIMO) systems [1]
Power-domain non-orthogonal multiple access (NOMA) is another promising technique envisioned for enabling massive access in future wireless systems
Consider that multiple users are communicating in uplink mode with a single base station (BS) in a MIMO-NOMA network
Summary
D UAL-POLARIZED antenna arrays are effective for overcoming physical space limitations in multiple-input multiple-output (MIMO) systems [1]. Dual-polarized MIMO systems can deliver improved user multiplexing and higher spectral efficiency than that achieved in singlepolarized counterparts [2]. Date of publication July 26, 2021; date of current version October 7, 2021. Besides limiting the sum-rate, this behavior leads to unbalanced individual rates, which is not suitable for applications where multiple devices require a uniform performance. One can alleviate this issue by balancing the users’ rates through adaptive power allocation [4]. We exploit dual-polarized IRSs to propose a novel approach for reducing the interference levels of the SIC process in the uplink. The operator vec(·) transforms a M × N matrix into a column vector of length MN, vecd(·) converts the diagonal elements of an M × M square matrix into a column vector of length M, and diag(·) transforms a vector of length M into an M × M diagonal matrix
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
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 call
