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Jamming Suppression in Massive MIMO Systems
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AI
DOI：10.1109/TCSII.2019.2902074.png)
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摘要
En 中文
In this brief, we propose a framework for protecting the uplink transmission of a massive multiple-input multiple-output (mMIMO) system from a jamming attack. Our framework includes a novel minimum mean-squared error-based jamming suppression (MMSE-JS) estimator for channel training and a linear zero-forcing jamming suppression (ZFJS) detector for uplink combining. The MMSE-JS exploits some intentionally unused pilots to reduce the pilot contamination caused by the jammer. The ZFJS suppresses the jamming interference during the detection of the legitimate users' data symbols. The proposed framework is implementable, since the complexities of computing the MMSE-JS and the ZFJS are linear (not exponential) with respect to the number of antennas at the base station and can be fabricated using 28-nm fully depleted silicon on insulator technology and for the mMIMO systems. Our analysis shows that the jammer cannot dramatically affect the performance of an mMIMO system equipped with the combination of MMSE-JS and ZFJS. Numerical results confirm our analysis.
Keyword:
Jamming
Channel estimation
Uplink
Detectors
Contamination
Coherence
Estimation error
Massive MIMO
Physical layer security
jamming pilot contamination
jamming suppression
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