arXiv:2610.22789v1 Announce Type: new Abstract: In settings such as online recommendation platforms, medical decision-making with interim summaries, and stochastic control with static plants, the underlying system is often static so that the next state depends only on the most recent action. Moreover, the true system state is high-dimensional and cannot be observed directly, so actions must be selected based on information received through a rate-limited communication link, which constrains the control performance. This leads to a fundamental rate-cost tradeoff$\unicode{x2014}$the minimum communication rate required to achieve a prescribed average control cost. We study this tradeoff for a class of static systems we term static time-invariant control (STIC) systems, namely, control systems in which the next state depends on the history only through the most recent control action via a time-invariant kernel. For general control systems$\unicode{x2014}$not necessarily static or time-invariant$\unicode{x2014}$our prior work characterized this tradeoff through the limit of a sequence of directed-information minimization problems. However, the dimension of these problems grows with the time horizon, making the limiting formulation computationally intractable. In the present paper, we show for STIC systems that this growing-size formulation admits a single-letter characterization. This identifies STIC systems as the control-side counterpart of Noisy Output is the STate (NOST) channels$\unicode{x2014}$one of the few channel models whose feedback capacity admits a single-letter characterization. This yields, to our knowledge, the first constant-size convex characterization of the rate$\unicode{x2013}$cost tradeoff beyond linear quadratic Gaussian (LQG) control.