.png){kind=icon}
.png){kind=icon}
Return
Blind Interference Suppression for IRS-Aided Robust Wireless Communications
.png){kind=icon}
PRE
AI
DOI：10.1109/JIOT.2026.3675735.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
The application of intelligent reflecting surfaces (IRSs) to suppress interference in wireless communication systems has recently attracted significant research attention. Most existing approaches rely on complete or partial channel state information (CSI) to configure the IRS. However, acquiring accurate CSI in IRS-assisted systems involves considerable pilot overhead and introduces nonnegligible delays. This issue is further exacerbated under strong interference conditions, where interfering sources are typically noncooperative, making CSI acquisition even more challenging. As a result, existing CSI-dependent interference suppression methods become difficult to deploy in practice. To address these limitations, we propose a novel blind interference suppression strategy that combines a proportional phase-inversion (PPI) algorithm with the conditional sample mean (CSM) method. The proposed approach determines the IRS configuration using only the received signal power, without requiring any prior CSI. We conduct a comprehensive performance evaluation by deriving the theoretical performance of the proposed scheme, which is subsequently verified through numerical simulations. Furthermore, simulation results across various parameter settings demonstrate that the proposed blind interference suppression scheme reduces the interference power to the level of noise, thereby achieving a marked signal-to-interference-plus-noise ratio (SINR) improvement and outperforms existing benchmark schemes.
Keywords:
Blind beamforming
conditional sample mean (CSM)
intelligent reflecting surface (IRS)
interference suppression
Journal
IF:
8.9
Papers:
1.4W
Citations:
7.8W