Rick, what the paper describes is otherwise known as MIMO. Each AP transmits a signal on the same frequency channel. As long as the receivers can decorrelate the propagation paths from the different APs, they can reconstruct the desired signal.
In traditional MIMO, each transmitter sends multiple beams in different directions, and each receiver would combine the bit streams from all of the propagation paths. In this DIDO, it looks like each receiver is only interested in one of the propagation paths, rather than aggregating the signals from all of the paths. The net effect is the same, though.
These are clever techniques that APPEAR to violate Shannon's limit, but in fact they don't. They depend on decorrelated propagation paths, much as you would have if you used multiple separate cables in parallel. If the signals paths become more correlated, you will lose that spectral efficiency. For example, bring the APs physically very close together compared with the distance to the receivers. That sort of thing makes it difficult to decorrelate the different propagation paths.
What are the engineering and design challenges in creating successful IoT devices? These devices are usually small, resource-constrained electronics designed to sense, collect, send, and/or interpret data. Some of the devices need to be smart enough to act upon data in real time, 24/7. Are the design challenges the same as with embedded systems, but with a little developer- and IT-skills added in? What do engineers need to know? Rick Merritt talks with two experts about the tools and best options for designing IoT devices in 2016. Specifically the guests will discuss sensors, security, and lessons from IoT deployments.