Arimoto channel coding converse and Rényi divergence

Arimoto proved a non-asymptotic upper bound on the probability of successful decoding achievable by any code on a given discrete memoryless channel. In this paper we present a simple derivation of the Arimoto converse based on the data-processing inequality for Rényi divergence. The method has two benefits. First, it generalizes to codes with feedback and gives the simplest proof of the strong converse for the DMC with feedback. Second, it demonstrates that the sphere-packing bound is strictly tighter than Arimoto converse for all channels, blocklengths and rates, since in fact we derive the latter from the former. Finally, we prove similar results for other (non-Rényi) divergence measures.