Enhancing Performance of Downlink NOMA-Based C-RAN Topology Through Optimal User Pairing and Dynamic Power Allocation Scheme

This research introduces cutting-edge advancements in non-orthogonal multiple access (NOMA) technology. It begins by presenting a state-of-the-art user localization algorithm based on trilateration, which accurately determines user positions in NOMA systems. Additionally, two innovative algorithms,...

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Bibliographic Details
Published inIEEE access Vol. 11; pp. 111324 - 111334
Main Authors Elbakry, Mohamed S., Amer, Amira A., Ismail, Tawfik
Format Journal Article
LanguageEnglish
Published Piscataway IEEE 2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Algorithms
capacity maximization
Data transmission
dynamic power allocation
Dynamic scheduling
Heuristic algorithms
Interference
Localization
NOMA
Nonorthogonal multiple access
optimal fairness
Optimization
Performance enhancement
Radio access networks
Resource management
Signal to noise ratio
Topology
Transmission efficiency
Trilateration
user pairing
User requirements
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Summary:This research introduces cutting-edge advancements in non-orthogonal multiple access (NOMA) technology. It begins by presenting a state-of-the-art user localization algorithm based on trilateration, which accurately determines user positions in NOMA systems. Additionally, two innovative algorithms, MP (maximize number of paired users) and ME (maximize pairing efficiency), are introduced to optimize system performance by addressing challenges in localization, user pairing, and dynamic power allocation. These algorithms enhance system capacity, reduce interference, and improve quality of service (QoS) for all users. To further optimize system performance, a dynamic power allocation scheme is developed to seamlessly integrate with NOMA pairing optimization. This scheme ensures optimal power allocation based on user-specific factors, leading to enhanced data transmission efficiency and overall system performance. The research also pioneers a mathematical formulation for the NOMA pairing problem, taking into consideration the variability of user demands. This unique contribution improves system performance for users with diverse data rate requirements, addressing a critical aspect of NOMA research. Furthermore, the NOMA pairing optimization problem is formulated as a graph maximum weighted sum problem. This formulation enables the use of efficient low-complexity algorithms, contributing to the advancement of algorithmic approaches in NOMA systems.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2023.3322231