Key Technologies In Green Wireless Networks With Diversified And Unsustainable Energy

With dramatic development of wireless network, users’ demand for high data rate mobile digital service becomes increasingly large. The popularity of smart terminals, such as smart phones and tablet PC, has further accelerated the demand for digital service in wireless network. Meanwhile, wireless network has become the most energy consuming part in information communication industry, which exerts pressure of energy saving on wireless network. It’s imperative to construct green wireless telecommunication systems, which aims at energy saving and emission reduction. Many countries have been studying key technologies of green wireless telecommunication network, most of which concentrate on improving the energy efficiency for wireless telecommunication networks to satisfy the broader service needs without increasing power supply. This method can only reduce the relative amount of energy consumption and noxious gas emission, which is only a short-term solution to the power shortage and environment issues. This dissertation focuses on powering wireless telecommunication systems with renewable energy, which can reduce the absolute amount of power consumption and toxic gas emission. With utilization of renewable energy, we can radically resolve the power shortage and environment issues.However, powering wireless telecommunication network with renewable energy faces two major problems:state uncertainty and energy diversification. On one hand, the process of harvesting renewable energy is affected by natural environment and climate condition, so the power supply is discontinuous and unstable. The start of service and the amount of data transfer are also random, so the consumption of energy is also discontinuous and unstable. The power demand in green wireless network must be met all the time, and the uncertainty of energy state will affect the normal operation of green wireless. Lagging in energy storage technology, the batteries can only reduce but not eliminate the uncertainty of energy state. On the other hand, to make sure that the power demand in green wireless network be fully satisfied, we can only use various kinds of renewable energy or integrate with power grid to supply power for green wireless telecommunication network, which leads to the diversification of energy supply. The increasing of energy state uncertainty increases the difficulty of energy distribution. So it’s a chief priority to study the key technologies of diversification of energy and uncertainty of state in green wireless telecommunication network.Firstly, as basis of this research, this dissertation studies the energy states modeling problem under the condition of diversified energy and uncertain state in green wireless telecommunication network. Under the circumstances of single energy supply, we establish a G/G/1energy queue model, and we make use of diffusion approximation to analyze the factors that influence energy state. Under the condition of diversified energy supply, diverse energy queue model is proposed and factors that influence the performance of electrical power system in green wireless network are analyzed. The model provides theoretic support for resource management, network deployment, transmission rate allocation and energy allocation problems in green wireless networks. The analytical results and the accuracy of the proposed models are verified by the simulation.Secondly, the dissertation studies the resource management problem in green wireless network with unsustainable energy. The resource management problem is modeled as an optimization problem aiming to maximize the network energy residue ratio (ERR), considering both energy depleting rate (EDR) performance and the fairness in the network range. This optimization problem can be decomposed into two sub-problems which are energy efficiency maximization problem at the physical (PHY) layer and network ERR maximization problem at media access control (MAC) layer. The optimization is thus done in a cross-layer manner by an Iterative Hungarian Algorithm based scheme. The scheme performs excellently in improving both the network lifetime and the number of users served by renewable energy.Thirdly, the dissertation studies the network deployment problem in green wireless network with unsustainable energy. Energy dynamics metrics are analyzed base on G/G/1energy queue model by adopting diffusion approximation. Based on the results obtained in the analysis, cell zooming schemes are proposed under dynamic transmit-power control and dynamic transmit-rate control. Considering the energy depletion probability and energy waste probability together, the former scheme performs excellently in improving both the lifetime and green energy utilization of green base stations. Considering the efficiency and stability of green base station operation, the later scheme balances the tradeoff between coverage area and service unsustainability.Then, the dissertation studies the transmission rate allocation problem in green wireless network with unsustainable energy. The G/G/1energy queue model is reformed for renewable energy powered base station with sleep mode. Based on this model, the closed-form expressions of queue dynamic metrics characterizing both sleep phase and active phase are provided. Therefore, the transmission rate allocation problem is formulated as an effective rate maximization problem and then solved by the transmission rate adaption algorithm. The transmission rate adaption algorithm is validated by extensive simulations.Last but not least, this dissertation investigates energy allocation problem in green wireless network with diversified and unsustainable energy. Using diversified energy queue model, it analyzes performance index of power system of green wireless network, and obtains closed-form expression of power price, energy utilization, energy residue time as functions of energy allocation strategy. Based on theoretical results, aiming at optimizing performance parameters of power system jointly, an energy diversification and state uncertainty oriented strategy for allocate energy is proposed. The strategy not only satisfies performance requirements, but also leads to lower electricity bill.