학술논문

Hybrid Multiple-Access: Mode Selection, User Pairing and Resource Allocation
Document Type
Periodical
Source
IEEE Access Access, IEEE. 11:107251-107264 2023
Subject
Aerospace
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Engineering Profession
Fields, Waves and Electromagnetics
General Topics for Engineers
Geoscience
Nuclear Engineering
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Resource management
NOMA
Quality of service
Visible light communication
Hybrid power systems
Cellular networks
Uplink
Hybrid
interference management
mode selection
non-orthogonal multiple-access
resource allocation
Language
ISSN
2169-3536
Abstract
This paper proposes hybridization of non-orthogonal multiple-access (NOMA) and orthogonal multiple access (OMA) schemes for next-generation cellular networks. Specifically, two schemes that operate NOMA/OMA mode selection as well as channel and power allocation are proposed to improve the resource utilization and bandwidth-efficiency for network capacity maximization. The two proposed hybrid schemes are: (1) single-cell hybrid multiple-access (SC-HMA) and (2) multi-cell hybrid multiple-access (MC-HMA) schemes. The SC-HMA scheme determines the optimal NOMA/OMA mode and user pairs in each resource block by utilizing a matrix representing the capacity outcomes of pairing all possible combinations of users. On the other hand, in the MC-HMA, the NOMA/OMA modes are categorized into intra-cell and inter-cell based on an interference map, where the principal objective is to determine the best mode of operation between the user pairs to improve the overall sum-rate and quality-of-service (QoS). The results show that the proposed HMA schemes provide superior overall network capacity compared to benchmark schemes. In addition, the SC-HMA scheme outperforms the MC-HMA in terms of network capacity at the expense of higher computational complexity.