Open AccessAnalog Combining in Intelligent Reflecting Surface Assisted System with Low-Resolution ADCs
Author(s) -
ZhiKang Xu,
Rui Wang,
Chi Harold Liu
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1684/1/012012
Subject(s) - reflection (computer programming) , computer science , quantization (signal processing) , matrix (chemical analysis) , electronic engineering , channel (broadcasting) , converters , expression (computer science) , power (physics) , algorithm , engineering , telecommunications , physics , materials science , quantum mechanics , composite material , programming language
Intelligent Reflection Surface (IRS) and low-resolution analog-to-digital converters (ADCs) are proven to be efficient ways to release the burden of power consumption for future wireless systems. In this paper, the effect of IRS and quantization on the performance of multiple-input multiple-output (MDVIO) channels is investigated in terms of channel capacity. The reflection matrix of the IRS and analog combiner matrix are optimized jointly. To this end, the expression of capacity with low SNR is derived, and the optimization problem of the reflection matrix is converted to semidefinite programming (SDP). A gradient-based approach is proposed to optimize the analog combiner matrix and the reflection matrix in a general case. Simulation results are provided to assess the performance of proposed designs, it is shown that the IRS can improve the performance of the system where there is no line-of-sight channel to some extent, and a larger capacity could be obtained in low SNR expression than general expression under same conditions.