Geometric deep learning for lattice reduction
AssigneeQUALCOMM Incorporated
InventorsGiovanni Luca MARCHETTI, Gabriele CESA, Kumar PRATIK, Arash BEHBOODI
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Abstract
Certain aspects of the present disclosure provide techniques for wireless communications by an apparatus. Certain techniques include providing a first gram matrix to a neural lattice reduction model; generating, with the neural lattice reduction model, one or more partial changed bases; and generating a first reduced basis based on the one or more partial changed bases.
Claims20
An apparatus, comprising:
- one or more memories;
- and
- one or more processors, coupled to the one or more memories, configured to cause the apparatus to:
- provide a first gram matrix to a neural lattice reduction model;
- generate, with the neural lattice reduction model, one or more partial changed bases;
- and
- generate a first reduced basis based on the one or more partial changed bases.
A method for wireless communications by an apparatus comprising:
- providing a first gram matrix to a neural lattice reduction model;
- generating, with the neural lattice reduction model, one or more partial changed bases;
- and
- generating a first reduced basis based on the one or more partial changed bases.
A non-transitory computer-readable medium comprising processor-executable instructions that, when executed by one or more processors of an apparatus, causes the apparatus to perform a method comprising:
- providing a first gram matrix to a neural lattice reduction model;
- generating, with the neural lattice reduction model, one or more partial changed bases;
- and
- generating a first reduced basis based on the one or more partial changed bases.
Dependencies are inferred from the claim text.