Dynamic Energy Allocation Strategies For Energy Harvesting Wireless Communication Systems

The Internet of things technology is an important realizing method of “Internet of everything” under the era of big data. Its key component is wireless sensor node. Traditional wireless sensor node is usually powered by battery, which significantly reduces the reliability and continuity of the node. Along with the development of Green Communications, applying renewable energy on sensor nodes is drawing more and more attention. Therefore, this thesis studies the energy dynamic allocation strategies of energy harvesting sensor nodes, based on the energy harvesting rate and data arrival rate. The main research contents include:1. The energy dynamic allocation strategies of single node energy harvesting system were studied. The stability condition of the node was derived. And the performances of the strategies for different utility objects, different energy-data rate mapping functions and different fading channels were measured. Furthermore, reinforcement learning algorithm was introduced to get optimal energy allocation strategies. We also accelerated the convergence rate of the algorithm by changing the parameters of it.2. We studied the energy dynamic allocation strategies of two-hop relay energy harvesting system. The stability conditions of multi-hop relay system were derived. Moreover, we studied the delay optimal strategy for relay node and compared the sum delay performances of different strategy combinations. The sum delay optimal strategies were derived based on the principle of optimality.3. We studied the energy dynamic allocation routing protocols of wireless Mesh network. The vibration energy harvesting model was studied, too. We compared the differences between planar routing protocols and cluster routing protocols. We also combined energy harvesting technology with LEACH protocol and DEEC protocol and verified its influence on the life circle and throughput of the wireless Mesh network by simulation.