Distributed Joint Optimization of Beamforming and PowerAllocation for Maximizing the Energy Efficiency of...

Area of Science:

• Wireless Communication
• Network Engineering
• Signal Processing

Background:

• Cognitive heterogeneous networks (CHNs) face challenges in managing interference and optimizing energy efficiency.
• Existing methods for resource allocation in CHNs can be computationally intensive.
• Interference channels in multiple-input-single-output (MISO) systems require efficient management strategies.

Purpose of the Study:

• To develop an energy-efficient beamforming and power allocation strategy for cognitive heterogeneous networks.
• To maximize the sum energy efficiency of secondary users (SUs).
• To ensure interference to primary networks remains below a predefined threshold.

Main Methods:

• A distributed resource allocation algorithm based on dual methods was proposed.
• Each SU iteratively updates its beamforming vector and transmit power.
• The algorithm operates without information sharing among SUs until convergence.

Main Results:

• The proposed scheme achieves performance comparable to the optimal scheme.
• The algorithm significantly reduces computation time compared to optimal methods.
• Simulation results validate the effectiveness of the distributed approach.

Conclusions:

• The proposed distributed resource allocation strategy offers an effective solution for energy efficiency in cognitive heterogeneous networks.
• The method provides a practical approach for SU resource management with reduced computational complexity.
• This research contributes to the advancement of efficient wireless communication systems.