Expanding the compute-and-forward framework: Unequal powers, signal levels, and multiple linear combinations

Bobak Nazer, Viveck R. Cadambe, Vasilis Ntranos, Giuseppe Caire

Research output: Contribution to journalArticlepeer-review

39 Scopus citations

Abstract

The compute-and-forward framework permits each receiver in a Gaussian network to directly decode a linear combination of the transmitted messages. The resulting linear combinations can then be employed as an end-to-end communication strategy for relaying, interference alignment, and other applications. Recent efforts have demonstrated the advantages of employing unequal powers at the transmitters and decoding more than one linear combination at each receiver. However, neither of these techniques fit naturally within the original formulation of compute-and-forward. This paper proposes an expanded compute-and-forward framework that incorporates both of these possibilities and permits an intuitive interpretation in terms of signal levels. Within this framework, recent achievability and optimality results are unified and generalized.

Original languageEnglish (US)
Article number7517355
Pages (from-to)4879-4909
Number of pages31
JournalIEEE Transactions on Information Theory
Volume62
Issue number9
DOIs
StatePublished - Sep 2016

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Computer Science Applications
  • Library and Information Sciences

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