Integer-forcing for channels, sources and ADCs

Or Ordentlich
Graduate Student, Tel Aviv University
Given on: Sept. 27th, 2013


Integer-Forcing (IF) is a new framework, based on compute-and-forward, for decoding multiple integer linear combinations from the output of a Gaussian multiple-input multiple-output (MIMO) or multiple-access (MAC) channel. Integer-forcing is applicable when all transmitters use nested linear/lattice codes.

Building on the IF framework, we derive new theoretical results and develop new low-complexity coding schemes for several problems.

We begin by studying the capacity region of the Gaussian MAC under the constraint that all users transmit from a chain of nested lattice codes. Interestingly, the obtained rate-region depends on number-theoretic properties of the channel gains. Then, we apply these results in conjunction with lattice interference alignment to approximate the sum capacity of the symmetric K-user Gaussian interference channel.

We next apply the IF approach to arrive at a new low-complexity scheme, IF source coding, for distributed lossy compression of correlated Gaussian sources under an MSE distortion measure. The performance of the proposed scheme closely follows Berger-Tung's inner bound. Moreover, a one-shot version of IF source coding is described and analyzed. We argue that this scheme is simple enough to potentially lead to a new design principle for analog-to-digital converters (ADCs) that can exploit spatial correlations between the sampled signals.


Or Ordentlich received the B.Sc. degree (cum laude) and the M.Sc. degree (summa cum laude) in 2010 and 2011, respectively, in electrical engineering from Tel Aviv University, Israel. He is currently working toward the Ph.D. degree at Tel Aviv University.

Or is the recipient the Adams Fellowship awarded by the Israel Academy of Sciences and Humanities, the Advanced Communication Center (ACC) Feder Family award for outstanding research work in the field of communication technologies (2011), and the Weinstein Prize for research in signal processing (2011,2013).