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arXiv AI By Abdul Karim Gizzini, Yahia Medjahdi

X-RACE: XAI-assisted Recurrent neural network Attribution for Channel Estimation

Read the original on arXiv AI →

The paper introduces X-RACE, a framework that combines explainable AI with recurrent neural networks to improve channel estimation in high‑mobility vehicular environments. X-RACE employs a low‑complexity, one‑shot dual‑optimization strategy to prune unnecessary input subcarriers and hidden units, while also defining new temporal XAI metrics—Saturation Time, Importance Drift, and Relevance Contrast—to analyze LSTM learning dynamics. Simulation results show that X-RACE cuts inference complexity by at least 44.1% and maintains or improves Bit Error Rate performance compared to traditional XAI methods.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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