Electromagnetic radio frequency (RF) convergence is a signal-processing paradigm that is utilized when several RF systems have to share a finite amount of resources among each other. RF convergence indicates the ideal operating point for the entire network of RF systems sharing resources such that the systems can efficiently share resources in a manner that's mutually beneficial. With communications spectral congestion recently becoming an increasingly important issue for the telecommunications sector, researchers have begun studying methods of achieving RF convergence for cooperative spectrum sharing between remote sensing systems (such as radar) and communications systems. Consequentially, RF convergence is commonly referred to as the operating point of a remote sensing and communications network at which spectral resources are jointly shared by all nodes (or systems) of the network in a mutually beneficial manner. Remote sensing and communications have conflicting requirements and functionality. Furthermore, spectrum sharing approaches between remote sensing and communications have traditionally been to separate or isolate both systems (temporally, spectrally or spatially). This results in stove pipe designs that lack back compatibility. Future of hybrid RF systems demand co-existence and cooperation between sensibilities with flexible system design and implementation. Hence, achieving RF convergence can be an incredibly complex and difficult problem to solve. Even for a simple network consisting of one remote sensing and communications system each, there are several independent factors in the time, space, and frequency domains that have to be taken into consideration in order to determine the optimal method to share spectral resources. For a given spectrum-space-time resource manifold, a practical network will incorporate numerous remote sensing modalities and communications systems, making the problem of achieving RF convergence intangible.