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Variable-Length Feedback Coding With Universal Decoding and Bandit Channel Selection

Yavas, Recep Can
arXiv (All) · Papers
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94a15information-theorymachine-learning
We study variable-length feedback (VLF) coding over $K$ additive white Gaussian noise (AWGN) channels whose noise variances are unknown to both terminals but lie in a known interval. The receiver selects one channel at each time, conveys the selection over noiseless feedback, and must learn the chan
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