Title :

Adaptive NOMA in time-varying wireless networks with no CSIT/CDIT relying on a 1-bit feedback

Author(s) :

El Hassani, Hajar [Auteur]
Equipes Traitement de l'Information et Systèmes [ETIS - UMR 8051]
Savard, Anne [Auteur]
Circuits Systèmes Applications des Micro-ondes - IEMN [CSAM - IEMN ]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
Ecole nationale supérieure Mines-Télécom Lille Douai [IMT Lille Douai]
Veronica Belmega, E [Auteur]
Equipes Traitement de l'Information et Systèmes [ETIS - UMR 8051]

Journal title :

IEEE Wireless Communications Letters

Pages :

750-754

Publisher :

IEEE comsoc

Publication date :

2021-04

ISSN :

2162-2337

HAL domain(s) :

Mathématiques [math]
Sciences de l'ingénieur [physics]

English abstract : [en]

In this letter, the outage performance of a two user downlink non-orthogonal multiple access (NOMA) time varying network without any knowledge on the channel state or distribution at the base station (BS) is investigated. ...
Show more >In this letter, the outage performance of a two user downlink non-orthogonal multiple access (NOMA) time varying network without any knowledge on the channel state or distribution at the base station (BS) is investigated. Building on reinforcement learning techniques and, more precisely, on multi-armed bandits (MAB), we propose a novel adaptive NOMA scheme that optimally tunes which user should perform successive interference cancellation (SIC) jointly with the power allocation at the BS. Remarkably, our proposed scheme requires only a single bit (ACK-type) of feedback from each user and is still able to outperform OMA, as demonstrated by the numerical results in many settings of interest including stochastic and even non-stationary (adversarial) ones.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

ANR Project :

Technologies Emergentes pour l'Internet des Objets

Collections :

• Institut d'Électronique, de Microélectronique et de Nanotechnologie (IEMN) - UMR 8520

Source :

Harvested from HAL