Uplink Channel Estimation and Signal Extraction Against Malicious IRS in Massive MIMO System
- Resource Type
- Conference
- Authors
- Zheng, Xiaofeng; Cao, Ruohan; Ma, Lidong
- Source
- 2021 IEEE International Conference on Communications Workshops (ICC Workshops) Communications Workshops (ICC Workshops), 2021 IEEE International Conference on. :1-6 Jun, 2021
- Subject
- Communication, Networking and Broadcast Technologies
Computing and Processing
Engineering Profession
Base stations
Correlation
Conferences
Simulation
Channel estimation
Mean square error methods
Massive MIMO
Malicious attack
uplink channel estimation
massive MIMO
intelligent reflecting surface
- Language
- ISSN
- 2694-2941
This paper investigates effect of malicious intelligence reflecting surface (IRS). The malicious IRS is utilized for performing attack by randomly reflecting data sequences of legitimate users (LUs) to a base station (BS). We find that the data sequences of LUs are correlative to the signals reflected by malicious IRS. The correlation undermines the performance of traditional eigenvalue decomposition (EVD)-based channel estimation (CE) methods. To address this challenge, we propose an empirical-distribution-based channel estimation approach in the presence of malicious IRS. The proposed method works by capturing desired convex hulls from signals disturbed by malicious IRS, on the basis of its empirical distribution. Simulation results show that our proposed approach outperforms traditional EVD-based methods as much as nearly 5 dB in normalized mean square error (NMSE).