Cooperative Dynamic Game-Based Optimal Power Control in Wireless Sensor Network Powered by RF Energy

Area of Science:

• Wireless Communication
• Network Engineering
• Game Theory

Background:

• Wireless sensor networks (WSNs) face energy constraints, limiting their operational lifespan and efficiency.
• Simultaneous Wireless Information and Power Transfer (SWIFT) offers a promising solution for WSNs by enabling concurrent data and energy transmission.
• Optimizing power control is crucial for maximizing WSN performance under SWIFT protocols.

Purpose of the Study:

• To develop an optimal power control strategy for WSNs operating under the SWIFT protocol.
• To maximize individual sensor utility by considering both signal-to-interference-plus-noise ratio (SINR) and harvested energy.
• To formulate the problem as a cooperative dynamic game to achieve a team optimum.

Main Methods:

• Formulation of the utility maximization problem as a cooperative dynamic game.
• Application of dynamic programming theory to derive a feedback Nash equilibrium solution.
• Simulation analysis to compare cooperative (grand coalition) and non-cooperative approaches.

Main Results:

• A feedback Nash equilibrium strategy was derived for optimal power control in SWIFT-enabled WSNs.
• The proposed cooperative approach demonstrated superior performance compared to non-cooperative strategies.
• Simulation results validated the effectiveness of the developed optimal power control method.

Conclusions:

• The cooperative dynamic game framework effectively addresses optimal power control in SWIFT WSNs.
• Balancing SINR and harvested energy is key to maximizing sensor utility.
• The proposed approach offers a viable solution for enhancing the performance and longevity of energy-constrained WSNs.