This thesis explores the theoretical underpinnings and practical implications of Integrated Sensing and Communication (ISAC) within future wireless networks. As a transformative technology, ISAC merges sensing and communication functionalities to optimize the utilization of spectrum and hardware resources, a necessity driven by the increasing demands of modern applications such as autonomous vehicles and immersive technologies. The research addresses the critical need to understand the fundamental trade-offs between sensing and communication within ISAC systems. It investigates the Bayesian Cramér-Rao Bound (BCRB) as a metric for evaluating the performance limits of ISAC systems under various conditions. This bound is particularly relevant given the non-realistic nature of assuming known state information in dynamic channel environments, necessitating continuous estimation.