Optimal resource allocation method for energy harvesting based underlay Cognitive Radio networks

Area of Science:

• Wireless Communication
• Network Optimization
• Energy Harvesting

Background:

• Underlay Cognitive Radio (CR) networks enable spectrum sharing but face energy constraints.
• Energy Harvesting (EH) from Radio Frequency (RF) signals offers a sustainable power solution for CR networks.
• Maximizing Energy Efficiency (EE) is crucial for the practical deployment of EH-enabled CR systems.

Purpose of the Study:

• To propose an optimal resource allocation method for maximizing EE in EH-enabled underlay CR networks.
• To investigate the joint optimization of time allocation for energy harvesting and power allocation for data transmission.
• To develop an efficient algorithm for solving the EE maximization problem.

Main Methods:

• Modeling the EE maximization problem as a joint time and power optimization problem.
• Calculating the optimal energy harvesting time allocation factor.
• Deriving the optimal power allocation strategy using fractional programming and the Lagrange multiplier method.
• Developing an iterative algorithm for resource allocation.

Main Results:

• The proposed iterative method demonstrates superior performance compared to exhaustive and genetic algorithm methods.
• Simulation results confirm significant improvements in Energy Efficiency (EE) with the proposed method.
• The EE of the system model is substantially enhanced by incorporating energy harvesting capabilities.

Conclusions:

• The proposed optimal resource allocation method effectively maximizes EE in EH-enabled underlay CR networks.
• The joint time and power optimization strategy is key to achieving high energy efficiency.
• The developed iterative approach provides a computationally efficient solution for practical implementation.