Effects of Some Lattice Reductions on the Success Probability of the Zero-Forcing Decoder

07/10/2018
by   Jinming Wen, et al.
0

Zero-forcing (ZF) decoder is a commonly used approximation solution of the integer least squares problem which arises in communications and many other applications. Numerically simulations have shown that the LLL reduction can usually improve the success probability P_ZF of the ZF decoder. In this paper, we first rigorously show that both SQRD and V-BLAST, two commonly used lattice reductions, have no effect on P_ZF. Then, we show that LLL reduction can improve P_ZF when n=2, we also analyze how the parameter δ in the LLL reduction affects the enhancement of P_ZF. Finally, an example is given which shows that the LLL reduction decrease P_ZF when n≥3.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
07/02/2018

Neural Lattice Decoders

Lattice decoders constructed with neural networks are presented. Firstly...
research
01/12/2021

Lattice reduction by cubification

Lattice reduction is a NP-hard problem well known in computer science an...
research
04/14/2021

Dimension-Preserving Reductions Between SVP and CVP in Different p-Norms

We show a number of reductions between the Shortest Vector Problem and t...
research
04/28/2021

Polytime reductions of AF-algebraic problems

We assess the computational complexity of several decision problems conc...
research
03/06/2017

A lattice formulation of the F4 completion procedure

We write a procedure for constructing noncommutative Groebner bases. Red...
research
01/15/2023

The Voronoi Region of the Barnes-Wall Lattice Λ_16

We give a detailed description of the Voronoi region of the Barnes-Wall ...
research
08/09/2022

Direct and diffuse shading factors modelling for the most representative agrivoltaic system layouts

Agrivoltaic systems are becoming more popular as a critical technology f...

Please sign up or login with your details

Forgot password? Click here to reset