Open AccessTransceiver Design for IRS-Aided Massive MIMO Networks with Rate-Splitting
Author(s) -
Hanxiao Ge,
Navneet Garg,
Anastasios Papazafeiropoulos,
Tharmalingam Ratnarajah
Publication year - 2023
Publication title -
ieee access
Language(s) - English
Resource type - Journals
ISSN - 2169-3536
DOI - 10.1109/access.2023.3343612
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
Intelligent reflecting surface (IRS), equipped with multiple reflective elements, is an important technology for improving the achievable rate and energy efficiency of communications. Meanwhile, rate-splitting (RS) is an approach that reduces the detrimental effect of multi-user interference in the system by splitting users’ messages into private and common parts. In this work, we use the RS method in an IRS-aided massive multiple-input multiple-output (mMIMO) system. We assume each user is equipped with multiple antennas and then design the transceiver, which include the precoder and the combiner. We analyze the performance of the achievable sum-rate when the base station (BS) and users know perfect channel state information (CSI) or only statistical CSI. We use a projected gradient descent method (PGDM) to optimize the IRS phase shifts by minimizing the mean-squared error (MSE) for data estimates when the system has mixed CSI. The performance of combiner and precoder quantization, as well as the limited feedback has also been investigated in simulations in terms of the achievable sum-rate by using the iterative chordal distance (ICD) method.