Throughput fairness trade-offs for downlink non-orthogonal multiple access systems in 5G networks

Area of Science:

• Telecommunications Engineering
• Wireless Communication Systems
• Network Optimization

Background:

• Non-orthogonal multiple access (NOMA) is a key technology for 5G networks, aiming to improve spectral efficiency and support massive connectivity.
• Achieving both high throughput and system fairness in NOMA remains a significant challenge due to complex resource allocation.
• Existing methods often struggle to balance these competing objectives effectively.

Purpose of the Study:

• To propose a hybrid user pairing and power allocation scheme for downlink NOMA systems in 5G networks.
• To maximize system throughput while ensuring fairness among users.
• To reduce the complexity of resource allocation in NOMA systems.

Main Methods:

• User pairing is performed using Integer Linear Programming.
• Power allocation is optimized via Particle Swarm Optimization.
• A scalarization technique converts multi-objective functions into a single objective, with a penalty function enforcing constraints.

Main Results:

• The proposed hybrid scheme demonstrates superior performance over conventional numerical approaches.
• Achieved at least a 9% improvement in throughput maximization.
• Maintained an acceptable level of system fairness.

Conclusions:

• The developed hybrid scheme effectively enhances throughput and fairness in 5G NOMA systems.
• Separating user pairing and power allocation simplifies resource management.
• The optimization strategy successfully balances throughput and fairness objectives within system constraints.