Throughput, capacity and latency analysis of P-NOMA RRM schemes in 5G URLLC

• Published in: Multimedia tools and applications 2022-04, Vol.81 (9), p.12251-12273
• Main Authors: Iradier, Eneko, Abuin, Aritz, Fanari, Lorenzo, Montalban, Jon, Angueira, Pablo
• Format: Article
• Language: English
• Subjects: 1172: 5G Multimedia communications for Vehicular; Algorithms; Computer Communication Networks; Computer Science; Cycle time; Data Structures and Information Theory; Frequency division multiplexing; Industry and Entertainment Applications; Multimedia; Multimedia Information Systems; Network latency; Nonorthogonal multiple access; Resource allocation; Resource management; Special Purpose and Application-Based Systems; Waveforms; Wireless communication systems
• ISSN: 1380-7501; 1573-7721
• DOI: 10.1007/s11042-021-11086-6

5G is expected to cover a wide range of potential use cases due to its flexible and configurable physical layer waveform. One of the use cases proposed is the application of 5G on Ultra-Reliable Low Latency Communication (URLLC), which are characterized by very challenging reliability/availability and latency requirements. In addition, multimedia applications are being consolidated as a relevant aspect of current industrial environments. In order to meet those strict requirements, Radio Resource Management (RRM) becomes a critical phase of any wireless communication system. This work proposes the use of power domain Non-Orthogonal Multiple Access (P-NOMA) techniques in 5G RRM for factory automation environments. The research presented in this paper includes the design and evaluation of different RRM algorithms based on P-NOMA and on traditional Orthogonal Multiple Access (OMA) techniques, such as Time/Frequency Division Multiplexing Access (T/FDMA). Those algorithms are comprehensively explained and oriented to optimize the resource allocation based on different metrics (i.e., capacity, number of users, or cycle time). Moreover, extensive results are presented, where the performance of NOMA and OMA techniques is compared in terms of different metrics under the influence of several parameters, such as payload, bandwidth, or the number of users. Results indicate that although both NOMA and OMA provide positive aspects, eventually NOMA-based RRM algorithms are the solutions that enhance considerably the spectral efficiency.