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2010

Lattice-reduction aided HNN for vector precoding

9 years 5 months ago
Lattice-reduction aided HNN for vector precoding
In this paper we propose a modication of the Hopeld neural networks for vector precoding, based on Lenstra, Lenstra, and Lov`asz lattice basis reduction. This precoding algorithm controls the energy penalty for system loads = K/N close to 1, with N and K denoting the number of transmit and receive antennas, respectively. Simulation results for the average transmit energy as a function of show that our algorithm improves performance within the range 0.9 1, between 0.4 dB and 2.6 dB in comparison to standard HNN precoding. The proposed algorithm performs close to the sphere encoder (SE) while requiring much lower complexity, and thus, can be applied as an efcient suboptimal precoding method.
Vesna Gardasevic, Ralf R. Müller, Daniel J. R
Added 13 Feb 2011
Updated 13 Feb 2011
Type Journal
Year 2010
Where ISITA
Authors Vesna Gardasevic, Ralf R. Müller, Daniel J. Ryan, Lars Lundheim, Geir E. Øien
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