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Home > News & Events > MITRE Publications > Envision >
Analog Integrated Circuits: Batteries Not Needed

ANALOG INTEGRATED CIRCUITS:
BATTERIES NOT NEEDED

By Robert M. Taylor, Jr.

SUMMARY: Many fields of technology are emerging that must function on very low power. Analog integrated chip technology is proving capable of providing all the computing functions necessary for running advanced technology while requiring mere microwatts of power.

Low Power Revolution

The artificial silicon retina microchip, implanted in the eye, stimulates damaged retinal cells so they can once again process visual signals. Invented by Dr. Alan Chow and his brother Vincent Chow, the chip is thinner than a human hair and powered solely by incidental light.

From bioelectronics to infinite-life sensor systems to computers that mimic the human brain, technologies that run on ultra-low-power integrated chips such as the retina microchip will transform our world. One of the challenges of these technologies is avoiding or minimizing the use of batteries. In the same way a patient does not want to have surgery to change a dead battery on a retinal implant, a reconnaissance team would invariably prefer not having to enter a hostile region to recharge a surveillance system.

Analog Integrated Circuits: Batteries Not Needed

Old School Circuitry

Power consumption is a key factor when choosing the type of microcircuitry to use in ultra-low-power applications. Digital integrated circuits are the ones we are most familiar with. Digital circuits employ their transistors as on-off switches, playing traffic cops in a binary world of computing. Because they are well understood, sturdy, and easily programmed, digital circuits lie at the heart of almost all of our computer and communication systems.

But before digital integrated circuits, there were analog integrated circuits. Analog circuits do not dedicate their transistors to merely signaling "on" and "off." Analog circuits can use the full computational capabilities of transistors to perform mathematical operations such as logarithms and square roots, operations that would take hundreds of transistors operating as switches to compute. At the same time, circuit designers are slowly overcoming many of the problems that have traditionally plagued analog circuits, such as precision, accuracy, thermal sensitivity, and programmability.

Power and Speed

Because one properly used transistor can perform the functions it would require many switches to perform, analog computing systems require less power. Furthermore, each transistor operating as a low-voltage analog device consumes much less power than the transistor operating as a digital switching device—potentially magnitudes less power.

While digital chips have managed to adhere to Gene's Law (a prediction made by Texas Instruments' Gene Frantz that the energy efficiency of integrated circuits will double every 18 months), analog chips are not subject to even that generous limitation. Commercial companies currently produce analog chips that require 10 times less power than equivalent digital chips; university researchers have observed 100 times less power for certain functions like forward error correction in communication systems. Analog chips are nearing the power consumption efficiency (requiring less than a microwatt to operate) necessary to completely do away with batteries and simply harvest energy from the environment.

Analog Integrated Circuits: Batteries Not Needed

Analog systems may also be faster. Digital integrated circuits are synchronous; they are governed by a clock signal that dictates the operation speed of the transistors. A digital circuit is only as fast as the clock signal. Most analog integrated circuits are asynchronous; there is no clock signal to limit their speed. Analog circuits therefore have the ability to be orders of magnitude faster than digital computation.

Sharing Insights

MITRE has gained expertise on ultra-lowpower applications from our work designing sensor and communication networks for defense and intelligence applications, where the need to minimize size, weight, and power while maximizing computational power is paramount.

MITRE has invested this expertise into several projects that apply analog chip technology, such as a study of neuromorphic computing, where our researchers design computers to "think" like a brain using new kinds of algorithms and microprocessors that replicate the features of neurons. We are also employing analog circuitry in our research into compressive sensing, currently one of the most active research areas in signal processing owing to its potential to acquire signals at a much lower sampling rate with limited loss of information. Analog circuitry also plays a role in MITRE's pursuit of ultra-low-power, real-time compressive decoding/imaging.

Mobile electronic devices never stop getting smaller even while they gain more functions and computational power. The batteries that power these devices have also been forced to shrink even as they are asked to provide more juice. Eventually, batteries will reach their limits in powering devices running on digital integrated chips. Eventually, we'll desire devices that require no batteries at all. When it comes time to rethink how we design mobile electronics, ongoing research will provide the initial guidance for applying analog integrated chips to these applications.

Robert M. Taylor, Jr.

INSIDE VIEW

When it comes to computation, Robert Taylor does not bow to tradition. "Everyone tends to do what the generation before them did. But sometimes you have to stop and ask, is there something better?" Taylor is intrigued with the inherent computation certain materials naturally exhibit and their connection to solving sophisticated mathematical problems. "We are familiar with semi-conductor chips, but almost any material can be used for computation. You can do arithmetic by flowing water through reservoirs and valves and pipes. Researchers have built computers that use DNA, quantum effects, and even toys, as evidenced by the MIT Tinker Toy computer. The question is: What is the best match of your materials to your math to meet your objectives?"

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For more information, please contact Robert M. Taylor, Jr. using the employee directory.


Page last updated: February 22, 2011   |   Top of page

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