In this paper, we provide a lower and an upper bound for the strong converse exponent of the soft covering problem in the classical setting. This exponent characterizes the slowest achievable convergence speed of the total variation to one when a code with a rate below mutual information is applied to a discrete memoryless channel for synthesizing a product output distribution. We employ a type-based approach and additionally propose an equivalent form of our upper bound using the R\'enyi mutual information. Future works include tightening these two bounds to determine the exact bound of the strong converse exponent.

翻译：本文针对经典软覆盖问题，给出了强逆指数的下界与上界。该指数刻画了在离散无记忆信道上，当采用低于互信息速率的编码合成乘积输出分布时，总变差收敛至一的最慢可达收敛速度。我们采用基于类型的方法进行研究，并进一步利用Rényi互信息给出了上界的等价形式。未来的工作包括收紧这两个界以确定强逆指数的精确界。