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

[1] R. Su, L. Dai, J. Tan, M. Hao, and R. MacKenzie, "Capacity Enhancement for Irregular Reconfigurable Intelligent Surface-Aided Wireless Communications," in Proc. IEEE Global Commun. Conf. (IEEE GLOBECOM'20), Dec. 2020, pp. 1-6.

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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: Ruochen Su (email: src18@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 R2016b and 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), Tsinghua National Laboratory
for Information Science and Technology (TNList), Department of Electronic Engineering, Tsinghua University, Beijing 100084, China. 

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Abstract of the paper: 

Reconfigurable intelligent surface (RIS) is an emerging
technology to improve the spectral efficiency of wireless
communication systems. However, the increase of RIS elements
results in the non-negligible overhead of channel estimation and
channel feedback, as well as the high complexity of beam design.
Therefore, how to improve the system capacity with a limited
number of RIS elements becomes a challenge. In this paper, we
propose a brand new irregular RIS structure to enhance the
capacity of RIS-aided wireless communications. The key idea is
to irregularly configure a given number of RIS elements on an
enlarged surface, which provides extra degrees of freedom and
spatial diversity compared with the classical regular RIS. For the
proposed irregular RIS-aided communication, we then formulate
the joint topology and beamforming design problem to maximize
the system capacity. Accordingly, we propose a joint optimization
framework with low complexity to alternately optimize the RIS
topology and the corresponding beamforming design. Finally,
simulation results demonstrate that the proposed irregular RIS
with a limited number of RIS elements can significantly enhance
the system capacity compared with the traditional regular RIS.

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How to use this simulation code package?

Fig. 3 in the paper can be derived by running the corresponding RISpre_SNR.m file (Refer to the paper for parameter selection).
Fig. 4 can be derived by the output of the function in CEO_improve_RIS_sparse.m file.
Fig. 5 can be derived by running the corresponding RISpre_Sparsedegree_size.m file.

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Enjoy the reproducible research!
