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南京邮电大学电子与光学工程学院、柔性电子(未来技术)学院,江苏 南京 210023
[ "宋云超(1988‒ ),男,博士,南京邮电大学电子与光学工程学院、柔性电子(未来技术)学院副教授,主要研究方向为大规模MIMO、智能反射面、强化学习。" ]
[ "李浩(1999‒ ),男,南京邮电大学电子与光学工程学院、柔性电子(未来技术)学院硕士生,主要研究方向为MIMO、多臂赌博机等。" ]
[ "梁汇彬(1998‒ ),男,南京邮电大学电子与光学工程学院、柔性电子(未来技术)学院博士生,主要研究方向为大规模MIMO通信、多臂赌博机、卫星通信等。" ]
[ "汪革(1994‒ ),女,南京邮电大学电子与光学工程学院、柔性电子(未来技术)学院博士生,主要研究方向为无人机通信、多臂赌博机等。" ]
收稿日期:2023-08-25,
修回日期:2024-01-23,
纸质出版日期:2025-03-30
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宋云超,李浩,梁汇彬等.多臂赌博机赋能的IRS辅助MISO系统传输方案设计[J].物联网学报,2025,09(01):128-137.
SONG Yunchao,LI Hao,LIANG Huibin,et al.A multi-armed bandits empowered transmission scheme for IRS-assisted MISO system[J].Chinese Journal on Internet of Things,2025,09(01):128-137.
宋云超,李浩,梁汇彬等.多臂赌博机赋能的IRS辅助MISO系统传输方案设计[J].物联网学报,2025,09(01):128-137. DOI: 10.11959/j.issn.2096-3750.2025.00386.
SONG Yunchao,LI Hao,LIANG Huibin,et al.A multi-armed bandits empowered transmission scheme for IRS-assisted MISO system[J].Chinese Journal on Internet of Things,2025,09(01):128-137. DOI: 10.11959/j.issn.2096-3750.2025.00386.
智能反射面(IRS
intelligent reflecting surface)是一种能够提升毫米波通信性能并应对传输挑战的技术。然而,传统方法在联合优化预编码和IRS相移时需要准确的信道状态信息,导频消耗随着基站天线数和IRS元件数的增加而增大。为降低导频,提出了一种基于多臂赌博机(MAB
multi-armed bandit)的传输设计方案。具体而言,在IRS辅助单天线用户下行通信系统中,通过双时间尺度的方法,将IRS相移和预编码波束成形问题解耦。利用强化学习中的上下文MAB算法,在每个相干时间块内根据上下文信息和奖励反馈来设计IRS相移矩阵。接着,采用迫零方法设计预编码,并引入贪婪法来选择每一时刻的动作,以避免陷入局部最优。仿真结果表明,与现有的算法相比,所提算法能够实现更高的有效频谱效率。
Intelligent reflecting surface (IRS) is an effective technology that can enhance millimeter-wave communication performance and address transmission challenges. However
conventional methods require accurate channel state information when jointly optimizing precoding and IRS phase shifting
and pilot consumption increases with the number of base station antennas and IRS components. To reduce pilot overhead
a transmission design scheme based on multi-armed bandit (MAB) was proposed. Specifically
in IRS-assisted single antenna user downlink communication systems
the problem of IRS phase shift design and precoding beamforming was decoupled through a dual time scale approach. Using the contextual MAB algorithm in reinforcement learning
the IRS phase shift matrix was designed within each coherent time block based on contextual information and reward feedback. Next
the zero forcing method was used to design precoding
and the greedy method was introduced to select actions at each moment to avoid getting stuck in local optima. The simulation results show that the proposed algorithm can achieve higher effective spectral efficiency than the existing algorithms.
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