An Introduction to Spectral Convergence: Challenges and Paths to Solutions

摘要

With rapid advances in flexible, software-defined computational architectures and radio front-end technologies, we have an opportunity to improve the efficiency of spectral use, reinforce system reliability, and enable new system capabilities. We deprecate the traditional “stove-piped” approach towards spectral management in favor of networks of RF, mmWave, and terahertz systems that jointly execute multiple radio functions, including communications; radar; positioning, navigation, and timing (PNT); spectral situational awareness; and opportunistic spectrum access. Such multi-function systems are enabled by a class of waveform, processing, and co-design techniques which we label spectral convergence. In this paper, we review the set of challenges obstructing the integration of such devices into the same spectral region. We briefly survey the current status of the field, outline a taxonomy of solution classes, and recommend paths towards fruitful research. We discuss existing and novel approaches towards enabling multifunction systems in the context of contemporary applications such as automotive networks and satellite meshes. We address the challenges associated with distributed resource optimization in networks of multi-function systems. We apply these concepts to a simple automotive network example and demonstrate the potential of spectral convergence solutions in a basic simulation environment