Symbol-Level Precoding Design for Intelligent Reflecting Surface Assisted Multi-User MIMO Systems

Intelligent reflecting surface (IRS)has emerged as a promising solution to enhance wireless information transmissions by adaptively controlling prorogation environment. Recently, the brand-new concept of utilizing IRS to implement a passive transmitter attracts researchers' attention since it p...

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Published in:International Conference on Wireless Communications and Signal Processing pp. 1 - 6
Main Authors: Liu, Rang, Li, Hongyu, Li, Ming, Liu, Qian
Format: Conference Proceeding
Language:English
Published: IEEE 01.10.2019
Subjects:
constant envelope precoding
Information processing
Intelligent reflecting surface (IRS)
low-resolution phases
MIMO communication
multiple-input multiple-output (MIMO)
Optimization
Precoding
Receivers
symbol-level precoding
Transmitters
Wireless communication
ISSN:2472-7628
Online Access:Get full text
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Abstract Intelligent reflecting surface (IRS)has emerged as a promising solution to enhance wireless information transmissions by adaptively controlling prorogation environment. Recently, the brand-new concept of utilizing IRS to implement a passive transmitter attracts researchers' attention since it potentially realizes low-complexity and hardware-efficient transmitters of multiple-input single/multiple-output (MISO/MIMO)systems. In this paper we investigate the problem of precoder design for a low-resolution IRS-based transmitter to implement multi-user MISO/MIMO wireless communications. Particularly, the IRS modulates information symbols by varying the phases of its reflecting elements and transmits them to K single-antenna or multi-antenna users. We first aim to design the symbol-level precoder for IRS to realize the modulation and minimize the maximum symbol-error-rate (SER)of single-antenna receivers. In order to tackle this NP-hard problem, we first relax the low-resolution phase-shift constraint and solve this problem by Riemannian conjugate gradient (RCG)algorithm. Then, the low-resolution symbol-level precoding vector is obtained by direct quantization. Considering the large quantization error for 1-bit resolution case, the branch-and-bound method is utilized to solve the 1-bit resolution symbol-level precoding vector. For multiantenna receivers, we propose to iteratively design the symbol-level precoder and combiner by decomposing the original large-scale optimization problem into several sub-problems. Simulation results validate the effectiveness of our proposed algorithms.
AbstractList Intelligent reflecting surface (IRS)has emerged as a promising solution to enhance wireless information transmissions by adaptively controlling prorogation environment. Recently, the brand-new concept of utilizing IRS to implement a passive transmitter attracts researchers' attention since it potentially realizes low-complexity and hardware-efficient transmitters of multiple-input single/multiple-output (MISO/MIMO)systems. In this paper we investigate the problem of precoder design for a low-resolution IRS-based transmitter to implement multi-user MISO/MIMO wireless communications. Particularly, the IRS modulates information symbols by varying the phases of its reflecting elements and transmits them to K single-antenna or multi-antenna users. We first aim to design the symbol-level precoder for IRS to realize the modulation and minimize the maximum symbol-error-rate (SER)of single-antenna receivers. In order to tackle this NP-hard problem, we first relax the low-resolution phase-shift constraint and solve this problem by Riemannian conjugate gradient (RCG)algorithm. Then, the low-resolution symbol-level precoding vector is obtained by direct quantization. Considering the large quantization error for 1-bit resolution case, the branch-and-bound method is utilized to solve the 1-bit resolution symbol-level precoding vector. For multiantenna receivers, we propose to iteratively design the symbol-level precoder and combiner by decomposing the original large-scale optimization problem into several sub-problems. Simulation results validate the effectiveness of our proposed algorithms.
Author Liu, Rang
Li, Ming
Li, Hongyu
Liu, Qian
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  givenname: Ming
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  givenname: Qian
  surname: Liu
  fullname: Liu, Qian
  organization: School of Computer Science and Technology, Dalian University of Technology,Dalian, Liaoning,China,116024
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Snippet Intelligent reflecting surface (IRS)has emerged as a promising solution to enhance wireless information transmissions by adaptively controlling prorogation...
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SubjectTerms constant envelope precoding
Information processing
Intelligent reflecting surface (IRS)
low-resolution phases
MIMO communication
multiple-input multiple-output (MIMO)
Optimization
Precoding
Receivers
symbol-level precoding
Transmitters
Wireless communication
Title Symbol-Level Precoding Design for Intelligent Reflecting Surface Assisted Multi-User MIMO Systems
URI https://ieeexplore.ieee.org/document/8928065
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