Multichannel-Sensing Scheduling and Transmission-Energy Optimizing in Cognitive Radio Networks with Energy Harvesting

Area of Science:

• Wireless Communication
• Network Engineering
• Energy Harvesting

Background:

• Cognitive radio networks (CRNs) enable efficient spectrum utilization.
• Cognitive users (CUs) face hardware constraints, limiting sensing/transmission to one channel at a time.
• Energy harvesting introduces finite energy availability for CUs.

Purpose of the Study:

• To develop an optimization scheme for CRNs with energy harvesting CUs.
• To maximize the expected throughput of CRNs over multiple time slots.
• To address hardware limitations and finite energy resources.

Main Methods:

• Optimizing the channel-sensing schedule (action and order).
• Optimizing the transmission energy allocation for each channel.
• Considering factors like frequency-switching delay, energy costs, spectrum occupancy correlation, and sensing errors.

Main Results:

• The proposed scheme significantly improves CRN throughput compared to existing methods.
• Simulation results validate the effectiveness of the optimization scheme.
• The collision ratio on primary channels was investigated.

Conclusions:

• The developed scheme effectively enhances CRN performance under energy harvesting constraints.
• Intelligent resource management is crucial for optimizing throughput in CRNs.
• The approach provides a valuable framework for future CRN research.