Closed-Form Error Probability of Network-Coded Cooperative Wireless Networks with Channel-Aware Detectors - CentraleSupélec Accéder directement au contenu
Communication Dans Un Congrès Année : 2011

Closed-Form Error Probability of Network-Coded Cooperative Wireless Networks with Channel-Aware Detectors

Résumé

In this paper, we propose a simple analytical methodology to study the performance of multi-source multi-relay cooperative wireless networks with network coding at the relay nodes and Maximum-Likelihood (ML-) optimum channel-aware detectors at the destination. Channel-aware detectors are a broad class of receivers that account for possible decoding errors at the relays, and, thus, are inherently designed to mitigate the effect of erroneous forwarded and network-coded data. In spite of the analytical complexity of the problem at hand, the proposed framework turns out to be simple enough yet accurate and insightful to understand the behavior of the system, and, in particular, to capture advantages and disadvantages of various network codes and the impact of error propagation on their performance. It is shown that, with the help of cooperation, some network codes are inherently more robust to decoding errors at the relays, while others better exploit the inherent spatial diversity and redundancy provided by cooperative networking. Finally, theory and simulation highlight that the relative advantage of a network code with respect to the others might be different with and without decoding errors at the relays.
Fichier principal
Vignette du fichier
GLOBECOM-2011a.pdf (223.73 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-00661321 , version 1 (19-01-2012)

Identifiants

  • HAL Id : hal-00661321 , version 1

Citer

Michela Iezzi, Marco Di Renzo, Fabio Graziosi. Closed-Form Error Probability of Network-Coded Cooperative Wireless Networks with Channel-Aware Detectors. GLOBECOM 2011, Dec 2011, Houston, United States. pp.1-6. ⟨hal-00661321⟩
145 Consultations
317 Téléchargements

Partager

Gmail Facebook X LinkedIn More