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华东交通大学电气与自动化工程学院,江西 南昌 330013
[ "丁青锋(1980- ),男,博士,华东交通大学电气与自动化工程学院教授、博士生导师,主要研究方向为大规模MIMO技术、智能电网通信和轨道无线通信等。" ]
[ "邹志祥(1998- ),男,华东交通大学电气与自动化工程学院硕士生,主要研究方向为波束成形和智能超表面等。" ]
收稿日期:2023-12-13,
修回日期:2024-03-06,
纸质出版日期:2024-05-20
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丁青锋,邹志祥.高铁场景下有源智能超表面辅助的能效优化研究[J].电信科学,2024,40(05):38-48.
DING Qingfeng,ZOU Zhixiang.Research on energy efficiency optimization assisted by active reconfigurable intelligent surface in high-speed railway scenarios[J].Telecommunications Science,2024,40(05):38-48.
丁青锋,邹志祥.高铁场景下有源智能超表面辅助的能效优化研究[J].电信科学,2024,40(05):38-48. DOI: 10.11959/j.issn.1000-0801.2024150.
DING Qingfeng,ZOU Zhixiang.Research on energy efficiency optimization assisted by active reconfigurable intelligent surface in high-speed railway scenarios[J].Telecommunications Science,2024,40(05):38-48. DOI: 10.11959/j.issn.1000-0801.2024150.
针对高铁场景中无源智能超表面(reconfigurable intelligent surface,RIS)引入的“乘性衰落”效应问题,一种有效解决办法是部署有源RIS。然而,传统的有源RIS全连接架构中大量有源元件会导致过高的硬件成本和功耗,因此提出一种有源RIS子连接架构,旨在满足车地通信中传输速率要求的同时兼顾系统的能量效率。首先,基于高铁场景的特殊性建立有源RIS辅助多用户的系统模型;其次,考虑基站最大发射功率约束、有源RIS发射功率约束和有源RIS相移矩阵约束,提出系统能量效率最大化问题,并通过使用分式规划理论中的拉格朗日对偶变换和二次变换,将上述非凸问题转化为凸优化问题;最后,提出一种联合发射波束成形和有源RIS相移矩阵的交替优化算法。仿真结果表明,相比传统无源RIS和有源RIS全连接架构方案,所提方案能有效解决“乘性衰落”问题,并且在满足用户传输速率的同时实现更高的能量效率。
In addressing the challenge of the multiplicative fading introduced by passive reconfigurable intelligent surface (RIS) in high-speed railway scenarios
an effective solution is the deployment of an active RIS. However
the conventional fully-connected architecture of active RIS
characterized by a multitude of active elements
results in excessive hardware costs and power consumption. Consequently
a sub-connected architecture of active RIS was proposed
with the aim of simultaneously considering the system's energy efficiency and the transmission rate in train-ground communication. Initially
a system model for active RIS-assisted multi-user scenarios was established
taking into account the distinctive features of the high-speed railway environment. Subsequently
the problem of maximizing system energy efficiency was formulated by considering constraints on the maximum transmission power of the base station
the transmission power of the active RIS
and the phase-shift matrix of the active RIS. Through the utilization of Lagrange dual transformation and quadratic transformation from fractional programming theory
the non-convex problem was transformed into a convex optimization problem. Finally
an alternating optimization algorithm was proposed for the joint optimization of beamforming and the phase-shift matrix of the active RIS. Simulation results indicate that
compared to traditional passive RIS and fully-connected of active RIS architectures
the proposed solution effectively addresses the multiplicative fading issue. Additionally
the proposed solution achieves higher energy efficiency while meeting user transmission rate requirements.
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