Ring-Based Planning Approach for Intelligent Reflecting Surface in 6G Networks

Intelligent reflecting surface (IRS) is regarded as a promising technique of establishing virtual line-of-sight paths for mmWave signals. Existing literature on the IRS deployment focuses on the placing location of an IRS between a macrocell and a user or some users. The orientation of the deployed IRS and the deployment of multiple IRSs and macrocells are missed but challenging and vital to an ultra-dense network for 6G. In this paper, the deployment problem of an ultra-dense network with multiple macrocells and multiple IRSs is considered and solved. On the basis of the ring-based algorithm proposed in our previous paper, a novel deployment algorithm is proposed to adjust IRS’s orientation for the better achievable rate of all served users, i.e. the Ring-based Sector algorithm. The ring-based algorithm yielded notable achievable rate but failed to serve more users with IRS’s reflection signals. By changing IRS’s orientation, the elements on IRS receive macrocell’s signal perpendicularly along with higher received signal power. On the other hand, a user-side IRS deployment method is further proposed to improve users’ achievable rate, i.e. the Ring-weight Dominating algorithm. Simulations are conducted in one square kilometer of planned network topology with 200 candidate position and 500 user equipment as an ultra-dense network scenario, where macrocell’s carrier frequency of mmWave and its bandwidth is 30 GHz and 100 MHz respectively. Compared to benchmark algorithms, our approach achieves a significant 20.5% increase in average achievable rate and a 20.2% improvement in network capacity performance.

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Publication Details

Journal
IEEE Access
Published
2025-01-01
DOI
https://doi.org/10.1109/access.2025.3556877
Citations
2
Primary Topic
Advanced Wireless Communication Technologies
Type
article
Field-Weighted Citation Impact
1.46

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article

Ring-Based Planning Approach for Intelligent Reflecting Surface in 6G Networks

Fan‐Hsun Tseng, Hao-Kai Hong, Hsin‐Hung Cho, Chi‐Yuan Chen
2 citations
IEEE Access
Advanced Wireless Communication Technologies
1.46
article

Ring-Based Planning Approach for Intelligent Reflecting Surface in 6G Networks

Fan‐Hsun Tseng, Hao-Kai Hong, Hsin‐Hung Cho, Chi‐Yuan Chen
article en
2 citations

Abstract

Intelligent reflecting surface (IRS) is regarded as a promising technique of establishing virtual line-of-sight paths for mmWave signals. Existing literature on the IRS deployment focuses on the placing location of an IRS between a macrocell and a user or some users. The orientation of the deployed IRS and the deployment of multiple IRSs and macrocells are missed but challenging and vital to an ultra-dense network for 6G. In this paper, the deployment problem of an ultra-dense network with multiple macrocells and multiple IRSs is considered and solved. On the basis of the ring-based algorithm proposed in our previous paper, a novel deployment algorithm is proposed to adjust IRS’s orientation for the better achievable rate of all served users, i.e. the Ring-based Sector algorithm. The ring-based algorithm yielded notable achievable rate but failed to serve more users with IRS’s reflection signals. By changing IRS’s orientation, the elements on IRS receive macrocell’s signal perpendicularly along with higher received signal power. On the other hand, a user-side IRS deployment method is further proposed to improve users’ achievable rate, i.e. the Ring-weight Dominating algorithm. Simulations are conducted in one square kilometer of planned network topology with 200 candidate position and 500 user equipment as an ultra-dense network scenario, where macrocell’s carrier frequency of mmWave and its bandwidth is 30 GHz and 100 MHz respectively. Compared to benchmark algorithms, our approach achieves a significant 20.5% increase in average achievable rate and a 20.2% improvement in network capacity performance.

IEEE AccessVol. 13
National Ilan University (TW), Fo Guang University (TW), National Cheng Kung University (TW)
National Science and Technology Council
Sustainable cities and communities
Openalex Percentile: Top 18%
Advanced Wireless Communication Technologies
1.46
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