AI & RoboticsNews

MIT CSAIL’s RFocus boosts wireless signal strength by a factor of nearly 10

Improving a device’s signal might be as simple as increasing the number of antennas within the said device, according to new research. A team at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) claim they’ve managed to bolster connectivity with what they call RFocus, a software-controlled external  “smart surface” that uses an array of more than 3,000 wireless antennas. Preliminary tests show that it’s able to boost average signal strength by a factor of nearly ten and channel capacity by a factor of two.

“The core goal here was to explore whether we can use elements in the environment and arrange them to direct the signal in a way that we can actually control,” said senior study author Hari Balakrishnan, who’s scheduled to present the results next month at the USENIX Symposium on Networked Systems Design and Implementation (NSDI) in Santa Clara, California. “If you want to have wireless devices that transmit at the lowest possible power, but give you a good signal, this seems to be one extremely promising way to do it.”

In many wireless systems, transmitters direct their signals to ensure more of it reaches the intended receiver, improving communication throughput and range and reducing interference with other transmissions. A radio’s ability to make its signal depends on its size; a radio that’s physically larger can better direct its energy than a smaller radio. But large radio antenna configurations are hard to deploy, even in infrastructure base stations or access points.

RFocus

Above: A schematic of MIT CSAIL’s RFocus system.

Image Credit: RFocus

RFocus attempts to solve this with a two-dimensional surface comprising antennas that let a signal through or reflect it. The state of the elements is set by a software controller with the goal of maximizing the signal strength at a receiver.  This enables RFocus not only to maintain a high level of performance but to remain cost-effective at scale because the antennas cost only a few cents, and because the surface can be manufactured as an inexpensive thin wallpaper requiring no wiring.

Study coauthor Venkat Arun, a Ph.D. student, envisions it being used in a warehouse to connect hundreds of sensors for monitoring machines and inventory. He notes that a similar technique was described in a recent paper published by a Princeton University team, but that RFocus is even more low-cost and suitable for a wider range of scenarios.

“The biggest challenge was determining how to configure the antennas to maximize signal strength without using any additional sensors, since the signals we measure are very weak,” says PhD student Venkat Arun, lead author of the new paper alongside Balakrishnan. “We ended up with a technique that is surprisingly robust.”


Author: Kyle Wiggers.
Source: Venturebeat

Related posts
AI & RoboticsNews

Nvidia and DataStax just made generative AI smarter and leaner — here’s how

AI & RoboticsNews

OpenAI opens up its most powerful model, o1, to third-party developers

AI & RoboticsNews

UAE’s Falcon 3 challenges open-source leaders amid surging demand for small AI models

DefenseNews

Army, Navy conduct key hypersonic missile test

Sign up for our Newsletter and
stay informed!