An unacknowledged “borrowing”
Few things in technology are completely original, “from the ground up” innovations. Of course, that’s no knock on those who creatively move technology forward, whether they’re making a new idea practical, applying existing technology in a new area, or fixing the multitude of problems that always crop up.
All of us know how much hard work it is to drive something from the bright idea stage to the point where it can be manufactured and deployed to satisfy a need and make a profit. Therefore, it’s no surprise that many important technologies have recognizable—if not always acknowledged—precursors.
Today’s example is a technology precursor that is both remarkably close and remarkably unknown: the use of multiple-input/multiple-output (MIMO) concepts in modal analysis of structures and its claim for priority over MIMO in RF communications. The parallels in terms of the fundamental concept—the matrix math and the very physical principles involved—are so close that I doubt you’ll object to the rather pejorative term used in the title of this post. If it’s an exaggeration, I’d argue it’s forgivable.
First, let’s a look at a recent example of the technology that came first: understanding the dynamic response of a structure by stimulating it and analyzing it at multiple locations simultaneously. This is called MIMO modal analysis, referring to the various “modes of vibration” that occur in the structure.
MIMO structural (modal) analysis of a wind turbine rotor. Three electromechanical shakers convert stimulus signals (e.g., noise or sinusoids) into mechanical inputs to the turbine. The response of the turbine blades is measured in multiple locations simultaneously by small accelerometers. (Image from Wikimedia Commons)
Practical MIMO analysis of structures dates back to the 1970s, perhaps 20 years before it was clearly conceptualized for communications. The technique was first used for modal testing of aircraft and satellites for several reasons. First, the inherent parallelism of the approach dramatically improved test time, reducing or eliminating the need to reposition shakers and accelerometers and repeat tests, to reveal all structural modes. The time value of prototype test articles meant that MIMO saved enough money to pay for the additional test equipment.
In addition, structural vibration frequencies were low enough to be within the range of early generation ADCs, DACs, and—most importantly—DSP resources. MIMO analysis is very computationally intensive, requiring vector or complex calculations on all signals. The results were (and still are) used to animate an image of the structure at specific resonant frequencies and the associated modes or deformation shapes (e.g., bending, torsion, etc.).
I wasn’t deeply familiar with the details of MIMO structural analysis when I first heard of MIMO for RF communications, but remember thinking, “This looks like it’s essentially the same thing.” Both kinds of MIMO involve a full vector understanding of the propagation of energy from multiple origins to multiple destinations. This understanding is used to make the propagation paths separable, via matrix math (e.g., eigenvectors), despite the fact that the propagation is happening simultaneously over a single frequency range.
The separated paths can be used to understand structural deformation at multiple locations, due to multiple inputs simultaneously. They can also be used to create multiple signal paths from a single RF channel, dramatically increasing capacity. Just what modern wireless so desperately needs! It simply took nearly three decades for the necessary wideband real-time processing to become practical.
In the years since I first heard about wireless MIMO, I’ve encountered remarkably few RF engineers who are aware of the technique’s history and the very direct parallels. In retrospect, I guess I shouldn’t be surprised. I imagine the intersection of structural and RF engineers who both know MIMO is vanishingly small. Also, the developers of RF MIMO do not seem to call out the similarities in any of their explanations.
Nonetheless, the commonality in everything from name to mathematics to the fundamental physics is one of the most impressive examples of technology reuse I’ve ever encountered. We may never know whether it’s an example of fully independent innovation or some truly inspired and creative borrowing.