Signal Processing - January 2017 - 12

Mit

Figure 3. MegaMIMO 2.0 research team members doctoral student Ezzeldin Hamed, visiting researcher Hariharan Rahul and Prof. Dina Katab with a prototype of their technology, which promises
to transfer wireless data over three times faster than existing systems.

including various properties of orthogonal frequency-division multiplexing signals, Fourier transforms and translation
between time and frequency domains, as
well as the efficient application of linear
time-invariant filters to signals.
As they developed the technology, the
researchers faced a challenge in coordinating
time and phase synchronization.
 

"The Wi-Fi transmitters have to be synchronized in time very tightly," Katabi
says. Such synchronization must occur
on a nanosecond scale. Also, since Wi-Fi
signals are waves, two waves can combine
to cancel each other out or, on the other
hand, enforce each other. "If you are not
careful about phase synchronization, the
wave can combine to create the opposite

of the intended effect," Katabi explains.
MegaMIMO uses signal processing to
enable access points to process signals in
a synchronized manner, providing a lightweight, distributed approach that requires
only minimal changes to the existing
Wi-Fi wireless processing pipeline.
In real-world applications, MegaMIMO
promises to dramatically improve throughput in the dense wireless networks-both
Wi-Fi and cellular-commonly deployed
in large, public places, such as sports stadiums, convention centers, hotels, airports,
and shopping malls.
The researchers are now focused
on scaling up the prototype system into
larger deployments consisting of scores of
Wi-Fi access points. "We have had interest from a variety of players in the wireless space, as well as end users that are
currently facing challenges with dense
wireless scenarios," Katabi says.

Author
Joh n Edwar ds ( je dwa r d s@joh n
edwardsmedia.com) is a technology writer based in the Phoenix, Arizona, area.

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Digital Object Identifier 10.1109/MSP.2016.2647178

12

IEEE Signal Processing Magazine

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January 2017

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Table of Contents for the Digital Edition of Signal Processing - January 2017
