Energy-efficient Resource Management For Heterogeneous Networks With Hybrid Energy

With the continuous growth of the demand for high data rate and high-capacity communication systems,the number of communication devices,the scale of heterogeneous networks and the energy consumption have been increasing substantially in today's society.In order to respond to the call for energy conservation and environmental protection,to achieve green communication,a hybrid form of green energy and grid energy to power the base station to reduce energy consumption in the grid.In this thesis,the two-layer heterogeneous network scenario where the green energy and the grid energy are mixed for the base station is studied.For improving the energy efficiency,the heterogeneous network resource management problem is studied from the perspective of the user side and the base station side.The main work and achievements are as follows:1.An access algorithm based on green energy perception comprehensive utility function is proposed.Under the two-layer heterogeneous network system where the hybrid energy source is used to power the base station,on the premise of ensuring the user service quality,the green energy status of the base station is taken as an access parameter meanwhile considering user cost,network security level,network delay,and SINR.These parameters can be computed by using the analytic hierarchy process.Then the utility function of the user access algorithm which serves as the basis for the user to access the base station is obtained by the access parameters.The simulation results show that the algorithm can reduce the total energy consumption cost,increase the number of green energy users,and facilitate heterogeneity network load balancing compared with the access algorithm based on user signal strength and the access algorithm based on the maximum signal-to-noise ratio.In addition,the access algorithm can balance the network load.Aiming at the high load system scenario,with huge consumption of grid energy and green energy,an access adjustment algorithm based on green energy perception utility function is proposed.First,the user intends to access the base station based on the green energy-aware integrated utility function access algorithm.Then according to the energy-powered style of base station,the connection matrix between the base stations and users is updated so that asmany base stations work as possible in the green energy supply state,thereby improving the system energy efficiency.Through simulation analysis,when the system load is high,compared with the green energy aware user association(NEAT)algorithm,the access algorithm based on the green energy perception comprehensive utility function can significantly improve the green energy utilization,reduce the system energy cost,improve system energy efficiency when the system load is high.2.The micro base sleep control algorithm with macro base station power adjustment is proposed.For a two-layer heterogeneous network scenario where the hybrid energy source is used to power the base station,when the base station is in a low load state,on the premise of ensuring the user service quality,the variation of base station energy consumption cost is used as a decision indicator for dormancy control of the micro base station.The micro base sleep control algorithm with macro base station power adjustment is proposed by combining dormancy control of the micro base station with power adjustment of the macro base station.Through simulation analysis,the proposed algorithm can improve the system energy efficiency without increasing the total system bandwidth compared with the utility function access algorithm where user only adopts the green energy-aware.3.A resource block allocation strategy based on energy efficiency and service type is proposed.To solve the resource block allocation problem,the resource block allocation strategy based on energy efficiency and service type is proposed from the perspective of energy efficiency and service type.Firstly,the users are classified according to the service type.Then the resource block allocation is completed in two stages of dividing the macroblock base station resource block and the user resource block partition.The resource block allocation model is established as an assignment problem in the user resource block partitioning stage.Finally,the Hungarian algorithm is used to solve the matching problem between resource blocks and users.The simulation results show that this strategy improves the system energy efficiency while ensuring the user's service quality.