﻿This simulation code package is mainly used to reproduce the results of the following paper [1]:

[1] X. Wei, D. Shen, and L. Dai, "Channel Estimation for RIS Assisted Wireless Communications—Part II: An Improved Solution Based on Double-Structured Sparsity," IEEE Commun. Lett., vol. 25, no. 5, pp. 1403-1407, May 2021.

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If you use this simulation code package in any way, please cite the original paper [1] above. 
 
The author in charge of this simulation code pacakge is: Xiuhong Wei (email: weixh19@mails.tsinghua.edu.cn).

Reference: We highly respect reproducible research, so we try to provide the simulation codes for our published papers (more information can be found at: 
http://oa.ee.tsinghua.edu.cn/dailinglong/publications/publications.html). 

Please note that the MATLAB R2020a is used for this simulation code package,  and there may be some imcompatibility problems among different MATLAB versions. 

Copyright reserved by the Broadband Communications and Signal Processing Laboratory (led by Dr. Linglong Dai), Beijing National Research Center for Information Science and Technology (BNRist), Department of Electronic Engineering, Tsinghua University, Beijing 100084, China. 
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Abstract of the paper: 

Reconfigurable intelligent surface (RIS) can manipulate the wireless communication environment by controlling the coefficients of RIS elements. However, due to the large number of passive RIS elements without signal processing capability, channel estimation in RIS assisted wireless communication system requires high pilot overhead. In the second part of this invited paper, we propose to exploit the double-structured sparsity of the angular cascaded channels among users to reduce the pilot overhead. Specifically, we first reveal the double-structured sparsity, i.e., different angular cascaded channels for different users enjoy the completely common non-zero rows and the partially common non-zero columns. By exploiting this double-structured sparsity, we further propose the double-structured orthogonal matching pursuit (DS-OMP) algorithm, where the completely common non-zero rows and the partially common non-zero columns are jointly estimated for all users. Simulation results show that the pilot overhead required by the proposed scheme is lower than existing schemes.
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How to use this simulation code package?

The simulation result (Fig. 2 in the paper) can be obtained by running the Main.m in the folder. The proposed DS-OMP algorithm is presented in DS_OMP.m.

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Enjoy the reproducible research!