Energy-Efficient Optimal Power Allocation in Integrated Wireless Sensor and Cognitive Satellite Terrestrial Networks

Area of Science:

• Wireless Communication
• Satellite Networks
• Cognitive Radio

Background:

• Cognitive satellite terrestrial networks offer seamless access and address spectrum scarcity for broadband applications.
• Increasing demand for spectral resources and concerns over energy efficiency in communication systems necessitate optimized resource allocation.

Purpose of the Study:

• To propose novel energy-efficient optimal power allocation schemes for cognitive satellite terrestrial networks.
• To maximize the energy efficiency (EE) of cognitive satellite users while ensuring acceptable interference levels for primary terrestrial users.

Main Methods:

• Developed energy-efficient power allocation schemes for non-real-time and real-time applications.
• Employed average interference power (AIP) constraints to protect primary users.
• Utilized average transmit power (ATP) or peak transmit power (PTP) constraints for satellite user power regulation.
• Solved the nonlinear concave fractional programming problem using Dinkelbach's method combined with Lagrange duality.

Main Results:

• The proposed schemes effectively maximize EE for cognitive satellite users.
• Interference to primary terrestrial users is maintained below acceptable levels.
• Simulation results show that fading severity in the terrestrial interference link benefits the satellite user.

Conclusions:

• The proposed energy-efficient power allocation schemes are effective for cognitive satellite terrestrial networks.
• Satellite users can achieve greater EE gains under ATP constraints compared to PTP constraints, especially with favorable fading conditions.