Détecteur pour l'accès aléatoire massif entre machines avec connaissance statistique du canal en lien ascendant

Diane Duchemin 1 Lélio Chetot 1 Jean-Marie Gorce 1 Claire Goursaud 1
1 MARACAS - Modèle et algorithmes pour des systèmes de communication fiables
Inria Grenoble - Rhône-Alpes, CITI - CITI Centre of Innovation in Telecommunications and Integration of services
Abstract : This paper focuses on random uplink transmissions of a subset of nodes disseminated in a cell. Under the constraints of massive Machine Type Communication (mMTC) in cellular Low Power Wide Area Networks (LPWAN) and Ultra Reliable Low Latency Communications (URLLC), we assume a highly restricted coordination with the receiver and the usage of coded Non Orthogonal Multiple Access (NOMA). We then target direct data transmission and propose an optimal detector of the active users with channel state information at the receiver limited to statistical knowledge. This algorithm implements a Maximum Likelihood (ML) detector. We give the formulation of the optimal detector and we evaluate its performance, with different codelengths and for various number of base station antennas.
Complete list of metadatas

Cited literature [11 references]  Display  Hide  Download

https://hal.inria.fr/hal-02297508
Contributor : Diane Duchemin <>
Submitted on : Thursday, September 26, 2019 - 11:15:49 AM
Last modification on : Wednesday, November 20, 2019 - 8:20:29 AM

File

GRETSI_detecteur_acces_multipl...
Files produced by the author(s)

Identifiers

  • HAL Id : hal-02297508, version 1

Collections

Citation

Diane Duchemin, Lélio Chetot, Jean-Marie Gorce, Claire Goursaud. Détecteur pour l'accès aléatoire massif entre machines avec connaissance statistique du canal en lien ascendant. GRETSI 2019, Aug 2019, Lille, France. ⟨hal-02297508⟩

Share

Metrics

Record views

18

Files downloads

185