Transmission Power Control In Wireless Sensor Networks

Wireless sensor networks (WSN) can be rapidly deployed with the properties of self-organization, strong invulnerability, self-healing. It has a wide application prospect in military, civil and industrial control and environmental monitoring. However, the hash deployment environment, high node density and very limited energy make the nodes suffer severe environmental interference and interference between nodes. Therefore, how to design effective transmission power control mechanism to improve the effectiveness of using energy and mitigation the interference among nodes become an important issue in WSN since it can prolong the networks survival time and improve the performance of the networks.This dissertation contains four folds. First, the concept and application of wireless sensor networks, then introduce the transmission power control issue and its research status. Secondly, propose a transmission control mechanism based on Supermodular game. To limiting the selfish behavior of the nodes, an external price mechanism is introduced. The myopic best response based power updating algorithm can converge to the unique Nash equilibrium of the Supermodular game based power control game. Then the simulation results verify the correctness of the proposed mechanism. Again, we use Gibbs sampling to analyze the transmission power control in wireless sensor networks. We bound the global interference to local interference of neighbors. The Gibbs sampling based power control algorithm can dynamically generate the power updating set, and the nodes can distribute implement the Gibbs power sampling which can converge to the optimal solution. Finally, we propose a power control mechanism which considers the residual energy of the nodes under non-cooperative game. The residual considered power game has unique Nash equilibrium. And the numerical simulation results demonstrate the effectiveness of the mechanism.