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Journal Articles IEEE Transactions on Communications Year : 2020

Resource Allocation in NOMA Systems for Centralized and Distributed Antennas with Mixed Traffic using Matching Theory

Abstract

In this paper, we study the traffic-aware resource allocation problem for a system with mixed traffic types. The considered framework encompasses real-time (RT) users having strict QoS requirements (in terms of amount of data and latency), and best-effort (BE) users for which the system tries to strike a balance between throughput and fairness. The resource allocation problem is studied in different contexts: orthogonal and non-orthogonal multiple access (OMA and NOMA respectively) in either centralized or distributed antenna systems (CAS and DAS respectively). Following the formulation of the resource optimization problem, we propose a low complexity suboptimal solution based on matching theory for each system context. We also propose an iterative approach to determine the number of subbands per antenna for the DAS contexts. The proposed techniques aim at guaranteeing the requirements of RT users while maximizing the utility function of BE users. Simulation results show that the proposed allocation method based on matching theory greatly outperforms a previously proposed greedy approach, especially in terms of RT users satisfaction.
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Dates and versions

hal-02307448 , version 1 (07-10-2019)

Identifiers

Cite

Marie-Josépha Youssef, Joumana Farah, Charbel Abdel Nour, Catherine Douillard. Resource Allocation in NOMA Systems for Centralized and Distributed Antennas with Mixed Traffic using Matching Theory. IEEE Transactions on Communications, 2020, 68 (1), pp.414 - 428. ⟨10.1109/TCOMM.2019.2947429⟩. ⟨hal-02307448⟩
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