Weighted Sum-Rate Maximization for Autonomous Transmissive RIS-Assisted mmWave High-Speed Railway Communication Using Genetic Algorithm

This paper presents a novel autonomous transmissive reconfigurable intelligent surface (ATRIS) framework for weighted sum-rate maximization in millimeter wave (mmWave) high-speed railway (HSR) communications. The proposed system employs ATRIS units mounted on high-speed train (HST) windows to enable efficient signal refraction from trackside base stations (BS) to in-cabin users, creating supplementary virtual line-of-sight (LoS) paths. To address the inherent challenges of HSR communications—including severe Doppler effects, multipath degradation, reduced coherence time, and fast fading—while reducing the computational complexity of conventional optimization approaches, we develop a decentralized feedback-based optimization framework. The system autonomously optimizes ATRIS phase shifts by maximizing the fraction of power transmitted through its' surface from BS, utilizing an on-board RF-Power Detector and genetic algorithm (GA). The optimized phase shift configurations are then transmitted to the BS via backhaul link, where weighted minimum mean square error (WMMSE) algorithms optimize the beamforming vectors to maximize users weighted sum-rates. For performance benchmarking, we implement a comparative centralized optimization approach using conventional passive transmissive reconfigurable intelligent surface (PTRIS) with direct BS control signal. Extensive simulation results demonstrate that our ATRIS-based system achieves competitive weighted sum-rates within 25% of the centralized PTRIS approach while significantly reducing computational complexity from <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$O\left(P G N K M_{B S}\right)$</tex> to O(PGN), where <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$P$</tex> is population size, <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$G$</tex> is number of generations, <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$N$</tex> is number of ATRIS elements, <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$K$</tex> is number of users, and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$M_{B S}$</tex> is number of BS antennas. These results validate the proposed framework's viability for practical HSR communication implementations operating at speeds of up to 600 km/h.

Authors

Institutions

Publication Details

Published
2025-06-17
DOI
https://doi.org/10.1109/vtc2025-spring65109.2025.11174519
Primary Topic
Millimeter-Wave Propagation and Modeling
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Weighted Sum-Rate Maximization for Autonomous Transmissive RIS-Assisted mmWave High-Speed Railway Communication Using Genetic Algorithm

Zheng Ma, Yannick Abel Talla Nana, Gang Liu
Millimeter-Wave Propagation and Modeling
article

Weighted Sum-Rate Maximization for Autonomous Transmissive RIS-Assisted mmWave High-Speed Railway Communication Using Genetic Algorithm

Zheng Ma, Yannick Abel Talla Nana, Gang Liu
article en

Abstract

This paper presents a novel autonomous transmissive reconfigurable intelligent surface (ATRIS) framework for weighted sum-rate maximization in millimeter wave (mmWave) high-speed railway (HSR) communications. The proposed system employs ATRIS units mounted on high-speed train (HST) windows to enable efficient signal refraction from trackside base stations (BS) to in-cabin users, creating supplementary virtual line-of-sight (LoS) paths. To address the inherent challenges of HSR communications—including severe Doppler effects, multipath degradation, reduced coherence time, and fast fading—while reducing the computational complexity of conventional optimization approaches, we develop a decentralized feedback-based optimization framework. The system autonomously optimizes ATRIS phase shifts by maximizing the fraction of power transmitted through its' surface from BS, utilizing an on-board RF-Power Detector and genetic algorithm (GA). The optimized phase shift configurations are then transmitted to the BS via backhaul link, where weighted minimum mean square error (WMMSE) algorithms optimize the beamforming vectors to maximize users weighted sum-rates. For performance benchmarking, we implement a comparative centralized optimization approach using conventional passive transmissive reconfigurable intelligent surface (PTRIS) with direct BS control signal. Extensive simulation results demonstrate that our ATRIS-based system achieves competitive weighted sum-rates within 25% of the centralized PTRIS approach while significantly reducing computational complexity from <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$O\left(P G N K M_{B S}\right)$</tex> to O(PGN), where <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$P$</tex> is population size, <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$G$</tex> is number of generations, <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$N$</tex> is number of ATRIS elements, <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$K$</tex> is number of users, and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$M_{B S}$</tex> is number of BS antennas. These results validate the proposed framework's viability for practical HSR communication implementations operating at speeds of up to 600 km/h.

Southwest Jiaotong University (CN)
Openalex Percentile: Top 73%
Millimeter-Wave Propagation and Modeling
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.