Research On Energy Management Policy Of Wireless Energy Harvesting Sensor Networks

In wireless energy harvesting sensor networks,energy harvesting system harvests energy from nature for sensors,which addresses the problem of energy supply constraints of the conventional wireless sensor networks.However,the introduction of energy harvesting technology brings new challenges.The natural environment varies randomly or periodically so that energy harvesting system cannot continue to provide enough energy for the wireless sensor.The complex wireless communication environment can cause inefficient transmission.The rechargeable battery is not ideal features such as storage loss and irreversible degradation mechanisms,which will reduce the energy efficiency and life cycle.In order to effectively using the precious energy harvesting resources and improving the working efficiency of wireless sensor network,it is necessary to research on energy management strategies.Most works aim to maximize the throughput,which assume battery with constant capacity and storage loss and perpetual battery operation,neglect any battery degradation issues related to battery usage.The battery degradation effects power allocation and shorts the life cycle of sensor.In this context,we focus on storage loss and battery degradation depending on how the battery is used,and research on the energy management strategy of wireless energy harvesting sensor networks to maximize the throughput in the lifetime cycle.Firstly,the energy management strategy for static channel condition is studied.The problem of system optimization is transformed into convex optimization problem.We obtain the power control strategy related to the current harvesting energy level and the battery energy level by the convex optimization analysis,and propose a dual power threshold algorithm which is suitable for the battery storage loss and capacity decay to optimize the average throughput.For optimizing the lifetime,a charge and discharge management policy is provided to minimize the discharge space.Secondly,in order to adapt to the complex communication environment,the energy management strategy under the fading channel condition is studied.We propose the dual power threshold algorithm for adaptive fading channels by means of convex optimization analysis,and analyze the battery charge and discharge management strategy to minimize the discharge space under channel fading.Finally,simulation results and theoretical analysis show that regardless of the static channel condition or the fading channel condition,the corresponding dual power threshold algorithm improves the energy efficiency of information transmission and avoids the energy storage loss,which optimizes the average throughput in the life cycle.The battery charge and discharge management strategy to minimize the discharge space extend the node's life cycle.The double-threshold algorithm with the minimized discharge space effectively improves the total throughput in the life cycle.