Selective Encoding Policies for Maximizing Information Freshness

An information source generates independent and identically distributed status update messages from an observed random phenomenon which takes n distinct values based on a given probability mass function (PMF). These update packets are encoded at the transmitter node to be sent to a receiver node which wants to track the observed random variable with as little age as possible. The transmitter node implements a selective k encoding policy such that rather than encoding all possible n realizations, the transmitter node encodes the most probable k realizations. We consider three different policies regarding the remaining n-k less probable realizations: highest k selective encoding which disregards whenever a realization from the remaining n-k values occurs; randomized selective encoding which encodes and sends the remaining n-k realizations with a certain probability to further inform the receiver node at the expense of longer codewords for the selected k realizations; and highest k selective encoding with an empty symbol which sends a designated empty symbol when one of the remaining n-k realizations occurs. For all of these three encoding schemes, we find the average age and determine the age-optimal real codeword lengths, including the codeword length for the empty symbol in the case of the latter scheme, such that the average age at the receiver node is minimized. Through numerical evaluations for arbitrary PMFs, we show that these selective encoding policies result in a lower average age than encoding every realization, and find the corresponding age-optimal k values. Since we focus on real-valued codeword lengths in this paper, the resulting age value obtained in each case studied here serves as a lower bound to what can be attained by integer-valued codeword lengths in that case.