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On the best lattice quantizers

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Allen,  Bruce
Observational Relativity and Cosmology, AEI-Hannover, MPI for Gravitational Physics, Max Planck Society;

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2202.09605.pdf
(Preprint), 435KB

On_the_Best_Lattice_Quantizers.pdf
(Publisher version), 459KB

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Citation

Agrell, E., & Allen, B. (2023). On the best lattice quantizers. IEEE Transactions on Information Theory. doi:10.1109/TIT.2023.3291313.


Cite as: https://hdl.handle.net/21.11116/0000-000A-BBA9-5
Abstract
A lattice quantizer approximates an arbitrary real-valued source vector with
a vector taken from a specific discrete lattice. The quantization error is the
difference between the source vector and the lattice vector. In a classic 1996
paper, Zamir and Feder show that the globally optimal lattice quantizer (which
minimizes the mean square error) has white quantization noise: for a uniformly
distributed source, the covariance of the error is the identity matrix,
multiplied by a positive real factor. We generalize the theorem, showing that
the same property holds (i) for any locally optimal lattice quantizer and (ii)
for an optimal product lattice, if the component lattices are themselves
locally optimal. We derive an upper bound on the normalized second moment (NSM)
of the optimal lattice in any dimension, by proving that any lower- or
upper-triangular modification to the generator matrix of a product lattice
reduces the NSM. Using these tools and employing the best currently known
lattice quantizers to build product lattices, we construct improved lattice
quantizers in dimensions 13 to 15, 17 to 23, and 25 to 48. In some dimensions,
these are the first reported lattices with normalized second moments below the
Zador upper bound.