Resource Allocation in NOMA Systems for Centralized and Distributed Antennas With Mixed Traffic Using Matching Theory

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 str...

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Bibliographic Details
Published inIEEE transactions on communications Vol. 68; no. 1; pp. 414 - 428
Main Authors Youssef, Marie-Josepha, Farah, Joumana, Nour, Charbel Abdel, Douillard, Catherine
Format Journal Article
LanguageEnglish
Published New York IEEE 01.01.2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Institute of Electrical and Electronics Engineers
Subjects
Antenna arrays
Antennas
Computer Science
DAS
Information Theory
latency
Matching
matching theory
Mixed traffic types
Multiplexing
Networking and Internet Architecture
NOMA
Nonorthogonal multiple access
Optimization
Receivers
Resource allocation
Resource management
Signal and Image Processing
User requirements
User satisfaction
NOMA
Mixed traffic types
Matching theory
Resource allocation
DAS
Latency
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Summary: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.
ISSN:0090-6778
1558-0857
DOI:10.1109/TCOMM.2019.2947429