Energy efficient resource allocation for power transmission line monitoring sensor networks

Abstract With the large-scale deployment of integrated sensing devices for power transmission line monitoring sensor networks (PTLMSN), the shortage of wireless spectrum resources is a growing problem in advanced communication and networking technology for smart grid. Device to-Device (D2D)-based green cognitive radio networks are considered as a key technology to alleviate wireless spectrum scarcity, but it faces the challenge of channel uncertainty. How to ensure energy efficiency and meet delay requirements in the presence of channel information uncertainty is a key issue to be addressed for PTLMSN. To address this issue, we consider the impact of channel uncertainty on PTLMSN using Device-to-Device (D2D) techniques and propose an energy-efficient resource allocation scheme for delay-constrained PTLMSN. We develop a queue-based delay model and propose an Energy Efficiency(EE)stochastic optimization model with delay constraints. The model is difficult to solve due to channel uncertainty. We simplify the stochastic constraints and propose a resource allocation algorithm that balances energy efficiency and delay guarantee performance of PTLMSN under uncertain channel information. In addition, we analyze the performance of the resource allocation algorithm, including complexity and feasibility. Simulation results show that the proposed algorithm has good Interference Efficiency (IE) and EE.