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COST CA20120 INTERACT Framework of Artificial Intelligence-Based Channel Modeling
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DOI：10.1109/MWC.010.2400253.png)
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Abstract
En 中文
Accurate channel models are the prerequisite for communication-theoretic investigations as well as system design. Channel modeling generally relies on statistical and deterministic approaches. However, there are still significant limits for the traditional modeling methods in terms of accuracy, generalization ability, and computational complexity. The fundamental reason is that establishing a quantified and accurate mapping between the physical environment and channel characteristics becomes increasingly challenging for modern communication systems. Here, in the context of COST CA20120 Action, we evaluate and discuss the feasibility and implementation of using artificial intelligence (AI) for channel modeling, and explore where the future of this field lies. Firstly, we present a framework of AI-based channel modeling to characterize complex wireless channels. Then, we highlight in detail some major challenges and present the possible solutions: estimating the uncertainty of AI-based channel predictions; integrating prior knowledge of propagation to improve generalization capabilities; and interpretable AI for channel modeling. We present and discuss numerical results to showcase the capabilities of AI-based channel modeling.
Keywords:
Predictive models
Artificial intelligence
Data models
Computational modeling
Accuracy
Uncertainty
Costs
Channel models
Atmospheric modeling
Numerical models
Journal
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