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 lowresolution 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 symbollevel precoder and combiner by decomposing the original largescale optimization problem into several sub-problems. Simulation results validate the effectiveness of our proposed algorithms. Index Terms-Intelligent reflecting surface (IRS), symbol-level precoding, constant envelope precoding, low-resolution phases, multiple-input multiple-output (MIMO).
In REF , the problem of precoding design in an RIS-based multi-user MISO wireless system is addressed, assuming that only discrete phase shifts values at the RIS are possible.
Symbol-Level Precoding Design for Intelligent Reflecting Surface Assisted Multi-User MIMO Systems
2019 11th International Conference on Wireless Communications and Signal Processing (WCSP)
2019 11th International Conference on Wireless Communications and Signal Processing (WCSP)
Computer Science Engineering