ISIT 2024, IEEE International Symposium on Information Theory, 7-12 July 2024, Athens, Greece
We devise achievable encoding schemes for distributed source compression for computing inner products, symmetric matrix products, and more generally, square matrix products, which are a class of nonlinear transformations. To that end, our approach relies on devising nonlinear mappings of distributed sources, which are then followed by the structured linear encoding scheme, introduced by Körner and Marton. For different computation scenarios, we contrast our findings on the achievable sum rate with the state of the art to demonstrate the possible savings in compression rate. When the sources have special correlation structures, it is possible to achieve unbounded gains, as demonstrated by the analysis and numerical simulations.
Type:
Conference
City:
Athens
Date:
2024-07-07
Department:
Communication systems
Eurecom Ref:
7671
Copyright:
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