Harnessing Interference via Algebraic Structure

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Event Speaker: 

Bobak Nazer (Boston University)

Event Location: 

32-155

Event Date/Time: 

Tuesday, May 14, 2013 - 4:00pm

Reception to follow.
 
Abstract
In a wireless network, interference between transmitters is usually viewed as highly undesirable and clever algorithms and protocols have been devised to avoid it. Collectively, these strategies transform the physical layer into a set of reliable bit pipes which can then be used seamlessly by higher layers in the protocol stack. Unfortunately, interference avoidance results in sharply decreasing rates as the number of users increases.

This talk proposes a new strategy, compute-and-forward, that exploits the interference property of the wireless channel to achieve higher end-to-end rates in a network. The key idea is that users should decode linear combinations of the transmitted messages according to their observed channel coefficients. This is a departure from classical information-theoretic frameworks which tend to either to decode interfering messages in their entirety or treat them as noise. Structured codes (such linear or lattice codes) ensure that these linear combinations can be decoded reliably, often at far higher rates than the messages individually. Historically, codes with linear/lattice structure have been studied as a stepping stone to practical constructions. Our recent work has employed compute-and-forward as a building block for coding theorems which lead to new achievability results in network information theory. In particular, we have developed a linear receiver architecture for MIMO channels that approaches the performance of joint decoding, determined the approximate sum capacity of a class of symmetric interference channels, and proposed a novel framework for interference alignment that permits decoding (rather than nulling) of aligned data streams.

Biography
Bobak Nazer is an Assistant Professor in the Department of Electrical and Computer Engineering at Boston University. He received his Ph.D in 2009 and M.S. in 2005 from the University of California, Berkeley in electrical engineering and computer sciences and his B.S. in 2003 from Rice University in electrical and computer engineering. He is the recipient of the NSF CAREER award in 2013 and the Eli Jury award in 2009 from the Berkeley EECS Department.