Fairness-Aware Resource Allocation in Multi-Hop Wireless Powered Communication Networks with User Cooperation

Area of Science:

• Wireless communication networks
• Resource allocation algorithms
• Network performance optimization

Background:

• Wireless powered communication networks (WPCNs) face throughput unfairness due to variable harvested energy among user nodes (UNs).
• Limited harvested energy necessitates strategic allocation for forwarding others' information versus transmitting own data, exacerbating unfairness.
• Existing methods struggle to address the inherent throughput disparities in WPCNs.

Purpose of the Study:

• To improve throughput fairness in wireless powered communication networks (WPCNs).
• To address the NP-hard problem of max-min throughput with resource allocation in WPCNs.
• To develop an efficient algorithm for fair energy and resource management.

Main Methods:

• Leveraging user cooperation in multi-hop transmissions within WPCNs.
• Formulating the fairness problem as a max-min throughput optimization with resource allocation.
• Designing and implementing an approximate algorithm to solve the NP-hard fairness problem.

Main Results:

• The proposed approximate algorithm provides tight upper and lower bounds for the optimal solution.
• Theoretical proofs confirm the algorithm's effectiveness.
• Simulation results demonstrate significant enhancement in throughput fairness compared to benchmark methods.

Conclusions:

• User cooperation in multi-hop transmissions is an effective strategy for improving WPCN fairness.
• The developed approximate algorithm efficiently addresses the complex resource allocation problem.
• The proposed method offers a practical solution for achieving enhanced throughput fairness in energy-constrained wireless networks.