A Discretization Approach to Compute-Forward
We present a novel unified framework of compute- forward achievable rate regions for simultaneous decoding of multiple linear codeword combinations. This framework covers a wide class of discrete and continuous-input channels, and computation over finite fields, integers, and reals. The resulting rate regions recover several well-known achievability results, and in some cases extend them. The framework is built upon a recently established achievable rate region based on linear codes and joint typicality decoding. The latter is extended from finite fields to computation over the integers and, via a discretization approach, to computation over the reals with integer coefficients and continuous inputs. Evaluating the latter with Gaussian distributions, we obtain a closed-form rate region which generalizes the classic compute-forward rates originally derived by means of lattice codes by Nazer and Gastpar.
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Pastore, A., Lim, S. H., Feng, C., Nazer, B., & Gastpar, M. (2021). A Discretization Approach to Compute-Forward. 2021 Ieee International Symposium on Information Theory (Isit), IEEE International Symposium on Information Theory, 2208–2213. https://doi.org/10.1109/ISIT45174.2021.9518259
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WOS:000701502202051
2021-01-01
New York
978-1-5386-8209-8
IEEE International Symposium on Information Theory
2208
2213
REVIEWED
EPFL
| Event name | Event place | Event date |
ELECTR NETWORK | Jul 12-20, 2021 | |