Energy Efficiency Optimization Based On Base Station Sleeping For Cellular Networks

The application of Mobile Internet and the development of intelligent terminals promoted the demand for wireless broadband.However, the exponential growth of requirements for mobile data services and high-speed wireless access accompanies the rapid expansion of cellular network infrastructure, which also increases energy consumption and operating costs of cellular networks. For cellular networks, improving the energy efficiency of air interfaces, and reducing the energy consumption of base stations become one of the key research areas of green wireless networks.The characteristics of mobile internet applications determine the dynamics of mobile services. The mobility and regular activities of mobile users bring the obvious space-time variation characteristics of traffic load. In practice, the networks are usually deployed based on peak service requirements without the consideration of energy consumption optimization. Base stations are the main energy consumption components in cellular networks, base stations with low traffic load can be adjusted to sleeping (closed) state to reduce the energy consumption. Therefore dynamic network management based on base staion sleeping is a promising energy efficiency optimization technology.With the evolution of mobile communication technologies, relay and Coordinated Multi-Point (CoMP) techniques were introduced in the LTE/LTE-A systems, heterogeneous cellular network with small cells becomes current main trend network. The application of base staion sleeping technology in new network architecture, for instance, relay network and heterogeneous cellular network, need to take into account user association and node selection, to achieve best energy efficiency.The topic of this thesis comes from the research project"TD-LTE-Advanced relay trial devices development" under the National Science and Technology Major Project "New Generation Broadband Wireless Mobile Communications Networks",and Beijing Natural Science Foundation Project "Energy efficiency network technologies research for heterogeneous cellular networks with coordinated small cells". This dissertation conducts studies on energy efficiency optimization techniques for cellular networks, including: base station sleeping energy efficiency transmission mode selection, relay cellular networks user association and base station sleeping optimization, energy efficiency user association algorithm of heterogeneous cellular network.The detailed research and contributions are issued as follows:1. This thesis provides an overview of the current research of cellular network energy saving and energy efficiency optimization. First,it analyses the status of cellular network energy consumption, to emphasize the importance of cellular network energy saving and energy efficiency optimization. Then it summarizes the energy saving technologies and analyses the evaluation methods of current network energy consumption. Finally, it summarizes the research of energy efficiency optimization based on cellular network base staion sleeping techniques, including: feasibility of base staion sleeping techniques,current research status of base staion sleeping techniques for different scenarios, summary of base staion sleeping techniques and energy efficiency optimization, as the research basis of this thesis.2. Cell zooming, semi smart antenna and CoMP technologies are used to patching the coverage hole created by base staion sleeping in cellular networks in general, which brings the optimized transmission mode selection issue. The combined mode of multiple transmission technologies could further improve the energy efficiency optimization gain of base staion sleeping. For the networks with multiple transmission technologies, this thesis provides an efficient transmission mode selection algorithm, taken the energy efficiency maximization as the optimization goal. One transmission mode from single cell transmission mode with cell zooming, CoMP transmission mode, single cell transmission mode with semi smart antenna, and CoMP transmission mode with semi smart antenna, was selected for data transmission. Simulation results show that the algorithm can improve the network energy efficiency by transmission mode selection and keep the coverage of the network.3. In relay cellular networks, base station (relay station) sleeping could reduce network energy consumption, but the guarantee of Quality of Service (QoS) for users also need to be taken into account. The thesis provides a base staion sleeping algorithm combined with user selection,to obtain the compromise of QoS guarantee and network energy saving.First it establishes a mathematical model of base station sleeping combined with user association optimization, and then provides the suboptimal solution algorithm with low complexity. Finally an energy efficiency optimization strategy based on access point (AP) sleeping(base station and relay station) is introduced. The simulation results show that, energy consumption could be reduced significantly by closing low traffic load base stations and relay stations, especially for the case of low traffic load situation, which could provide high energy efficiency and low energy consumption, realize the compromise of QoS guarantee and network energy saving.4. Furthermore, this thesis studies user association issue under base station sleeping for general heterogeneous cellular networks and renewable energy power networks. For heterogeneous cellular network scenario, an energy efficient user association algorithm is proposed, and it uses a quantum behaved particle swarm algorithm to solve the mathematic model for optimization problem. The simulation results show that the proposed algorithm can effectively improve the network energy efficiency, especially in low traffic load condition. For the renewable energy power networks scenario, taking into account the characteristics of available energy distribution between base stations, this thesis presents an implementation of energy balance and load balance user association algorithm. First it defines the topology potential to characterize stations to the user's appeal; then, it takes the sum of base station topology potential as the base station utility values, and propose an user association optimization problem for fairness among base stations; this thesis proposes an iterative method for optimization problem, through the information interaction between user and base station to complete the AP selection of users. The simulation results show that the proposed algorithm could balance load between base stations with high efficiency of renewable energy and achieve the goal of the energy balance.