Remote sensing and communications fundamentally tend to conflict with one another. Remote sensing typically transmits known information into the environment (or channel) and measures a reflected response, which is then used to extract unknown information about the environment. For example, in the case of a radar system, the known information is the transmitted signal and the unknown information is the target channel that is desired to be estimated. On the other hand, a communications system basically sends unknown information into a known environment. Although a communications system does not know what the environment (also called a propagation channel) is beforehand, every system operates under the assumption that it is either previously estimated or its underlying probability distribution is known. Due to both systems’ conflicting nature, it is clear that when it comes to designing systems that can jointly sense and communicate, the solution is non-trivial. Due to difficulties in jointly sensing and communicating, both systems are often designed to be isolated in time, space, and/or frequency. Often, the only time legacy systems consider the other user in their mode of operation is through regulations, which are defined by agencies such as the FCC (United States), that constrain the other user's functionality. As spectral congestion continues to force both remote sensing and communications system to share spectral resources, achieving RF convergence is the solution to optimally function in an increasingly crowded wireless spectrum.