Clustering and Power Optimization for NOMA Multi-Objective Problems

Zijian Wang (1) , Mylene Pischella (2) , Luc Vandendorpe (3)

1 UCL - Université Catholique de Louvain = Catholic University of Louvain
2 CEDRIC - LAETITIA - CEDRIC. Traitement du signal et architectures électroniques
3 TELE - Laboratoire de Télécommunications et Télédétection [Louvain]

This paper considers uplink multiple access (MA) transmissions, where the MA technique is adaptively selected between Non Orthogonal Multiple Access (NOMA) and Orthogonal Multiple Access (OMA). Two types of users, namely Internet of Things (IoT) and enhanced mobile broadband (eMBB) coexist with different metrics to be optimized, energy efficiency (EE) for IoT and spectral efficiency (SE) for eMBB. The corresponding multi-objective power allocation problems aiming at maximizing a weighted sum of EE and SE are solved for both NOMA and OMA. Based on the identification of the best MA strategy, a clustering algorithm is then proposed to maximize the multi-objective metric per cluster as well as NOMA use. The proposed clustering, power allocation and MA selection algorithm is shown to outperform other clustering solutions and non-adaptive MA techniques.

Domaines: Traitement du signal et de l'image [eess.SP]

Zijian Wang, Mylene Pischella, Luc Vandendorpe. Clustering and Power Optimization for NOMA Multi-Objective Problems. PMRC 2020, Aug 2020, Londres, United Kingdom. ⟨hal-02880569⟩