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

被引:0
作者
Elbakry, Mohamed S. [1 ]
Amer, Amira A. [2 ]
Ismail, Tawfik [3 ,4 ]
机构
[1] Inst Aviat Engn & Technol, Giza 12612, Egypt
[2] Cairo Univ, Fac Engn, Dept Commun & Comp Engn, Giza 12613, Egypt
[3] Cairo Univ, Natl Inst Laser Enhanced Sci, Giza 12613, Egypt
[4] Taibah Univ, Coll Engn, Madinah 42353, Saudi Arabia
关键词
NOMA; localization; user pairing; dynamic power allocation; optimal fairness; capacity maximization; EFFICIENT RESOURCE-ALLOCATION; NONORTHOGONAL MULTIPLE-ACCESS;
D O I
10.1109/ACCESS.2023.3322231
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:111324 / 111334
页数:11
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