A Training-Based Mutual Information Lower Bound for Large-Scale Systems

Xiangbo Meng; Kang Gao; Bertrand M. Hochwald

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arXiv · 2108.00034

A Training-Based Mutual Information Lower Bound for Large-Scale Systems

Xiangbo Meng·Kang Gao·Bertrand M. Hochwald

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Abstract

We provide a mutual information lower bound that can be used to analyze the effect of training in models with unknown parameters. For large-scale systems, we show that this bound can be calculated using the difference between two derivatives of a conditional entropy function. The bound does not require explicit estimation of the unknown parameters. We provide a step-by-step process for computing the bound, and provide an example application. A comparison with known classical mutual information bounds is provided.

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Xiangbo Meng, Kang Gao, Bertrand M. Hochwald. 2021-07-30. A Training-Based Mutual Information Lower Bound for Large-Scale Systems. https://arxiv.org/abs/2108.00034

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