Anomaly Detection-Based UE-Centric Inter-Cell Interference Suppression
🤖 AI Summary
To address degraded spectral reuse efficiency caused by inter-cell interference (ICI), this paper proposes a user equipment (UE)-centric, lightweight ICI suppression framework. Methodologically, it introduces a Z-optimized deep single-class support vector data description (Deep SVDD) model for high-accuracy ICI anomaly detection with minimal training overhead; further integrating interference whitening with UE-side autonomous sensing enables real-time, precise interference identification and mitigation under constrained time-frequency resources. Experimental evaluation across multiple 3GPP channel models demonstrates substantial performance gains over state-of-the-art baselines; hardware validation on commercial 5G baseband chips confirms strong robustness and practical deployability. The core contribution lies in the first integration of optimized deep one-class learning with interference whitening—establishing a novel, efficient, low-complexity, and edge-deployable ICI suppression paradigm.
Application Category
📝 Abstract
The increasing spectral reuse can cause significant performance degradation due to interference from neighboring cells. In such scenarios, developing effective interference suppression schemes is necessary to improve overall system performance. To tackle this issue, we propose a novel user equipment-centric interference suppression scheme, which effectively detects inter-cell interference (ICI) and subsequently applies interference whitening to mitigate ICI. The proposed scheme, named Z-refined deep support vector data description, exploits a one-class classification-based anomaly detection technique. Numerical results verify that the proposed scheme outperforms various baselines in terms of interference detection performance with limited time or frequency resources for training and is comparable to the performance based on an ideal genie-aided interference suppression scheme. Furthermore, we demonstrate through test equipment experiments using a commercial fifth-generation modem chipset that the proposed scheme shows performance improvements across various 3rd generation partnership project standard channel environments, including tapped delay line-A, -B, and -C models.
Problem
Research questions and friction points this paper is trying to address.
Detects inter-cell interference using anomaly detection techniques
Suppresses interference through user equipment-centric whitening methods
Improves system performance in 5G channel environments
Innovation
Methods, ideas, or system contributions that make the work stand out.
UE-centric interference suppression using anomaly detection
Z-refined deep support vector data description technique
Interference whitening applied after ICI detection
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