All of your examples sound like variations on fundamental CS problems, and most CS undergrads should have been exposed to them and to their solutions.
Are you saying industry is leaps and bounds ahead in the fundamentals of CS theory? Or just that there is a lot of vendor specific detail in the hardware and infrastructure? Because the latter is not CS.
They're not just variations on fundamental CS problems because the complexity of the problem is dominated by physics + hardware + infrastructure. E.g., while most CS undergraduates are exposed to control theory, a power control loop isn't a simple application of a controller. It has to deal with the physics of signal propagation, knowledge of the kinds of environments users encounter, the characteristics of the underlying radio, and the nature of the network infrastructure. All that insight and experimental validation is ultimately packaged as an algorithm (although a very specific and detailed one).
To analogize to another domain: a power control loop in a cell phone base band is as much "just a variation on fundamental CS problems" as is register allocation for a hairy architecture like x86. Yes, graph coloring gives you a conceptual framework to start with, but that gets you 10% of the way to a usable solution.
You seem to be saying that it's "fundamental computer science" to be aware of a problem and the naive ways to solve it, but not fundamental CS to know what methods are actually usable in the real world. That definition may have its merits, but is certainly not appropriate to use in a patent law discussion.
Are you saying industry is leaps and bounds ahead in the fundamentals of CS theory? Or just that there is a lot of vendor specific detail in the hardware and infrastructure? Because the latter is not CS.