Decoding by Embedding: Correct Decoding Radius and DMT Optimality - CentraleSupélec Access content directly
Conference Papers Year : 2011

Decoding by Embedding: Correct Decoding Radius and DMT Optimality

Abstract

In lattice-coded multiple-input multiple-output (MIMO) systems, optimal decoding amounts to solving the closest vector problem (CVP). Embedding is a powerful technique for the approximate CVP, yet its remarkable performance is not well understood. In this paper, we analyze the embedding technique from a bounded distance decoding (BDD) viewpoint. 1=(2 )- BDD is referred to as a decoder that finds the closest vector when the noise norm is smaller than 1=(2 ), where 1 is the minimum distance of the lattice. We prove that the Lenstra, Lenstra and Lov'asz (LLL) algorithm can achieve 1=(2 )-BDD for O(2n=4). This substantially improves the existing result = O(2n) for embedding decoding. We also prove that BDD of the regularized lattice is optimal in terms of the diversitymultiplexing gain tradeoff (DMT).
Fichier principal
Vignette du fichier
C1116.pdf (115.49 Ko) Télécharger le fichier
Origin Files produced by the author(s)
Loading...

Dates and versions

hal-00648134 , version 1 (05-12-2011)

Identifiers

  • HAL Id : hal-00648134 , version 1

Cite

Cong Ling, Shuiyin Liu, Laura Luzzi, Damien Stehlé. Decoding by Embedding: Correct Decoding Radius and DMT Optimality. IEEE International Symposium on Information Theory (ISIT'11), Jul 2011, Saint-Petersburg, Russia. 5 p. ⟨hal-00648134⟩
69 View
115 Download

Share

Gmail Mastodon Facebook X LinkedIn More