Analysis of Channel Knowledge Map Updating from Information Perspective

With the widespread adoption of 5G and the standardization of 6G, environment-aware communication techniques such as Channel Knowledge Map (CKM) have attracted increasing interest. CKM is a location-specific dataset containing channel state information, providing accurate wireless propagation characteristics. However, in time-varying environments, CKM requires periodic updates due to information aging, involving substantial data collection and training, which incurs non-negligible costs. Thus, a key challenge in CKM research is balancing update costs with information utility. This paper defines an information value function for CKM in time-varying environments and investigates when to update the CKM to maximize its average information value. It is proved that, under certain conditions regarding environmental dynamics, there exists a unique optimal update time, which can be derived from a closed-form expression. Numerical results validate the proposed theory, and case studies are conducted under typical time-varying channel models.