Macro/Femtocell Heterogeneous Network Resource Allocation Based On Energy Efficiency

With the development of communication technology,multi-network co-existence become the trend of network.Network convergence can not only exert the advantages of various networks,integrate network resources,but provide users with more faster,more diverse and anytime,anywhere network connection services.However,network convergence must face the problem that the network resources allocate reasonably.Therefore,it is of great significance to study the allocation strategy of wireless resources.Now,the communication system has become the world's fifth-largest energy consuming industry.In order to practice the concept of green communication,network energy efficiency is becoming a new indicator to measure network performance,improve the EE is a research hotspot in communications industry.This paper starts from OFDMA-based Macro/Femtocell Het network system to maximize EE.Research on spectrum and power allocation strategies for heterogeneous networks.The content includes the following aspects:Firstly,Designning and Planning of Macro/Femtocell Heterogeneous Network model architecture for OFDMA.For the downlink systems,analyzing the impact of specific cross-layer interference on system performance,building an optimization model with EE as theoretical foundation for allocation of carrier and power resources.Secondly,Research on spectrum allocation algorithm for Macro/Femtocell Heterogeneous Networks.In order to solve the shortcomings of poor late local convergence,an exponential inertia weight factor introduced into the bat algorithm's speed update formula to improve the performance.Using the BA-EDIW algorithm that based on exponentially decreasing inertia weights to allocate spectrum resources.Comparison of Energy Performance Performance by Simulation Experiment.Simulation results show that increasing the number of carriers and the number of users will reduce the system energy efficiency.Standard bats can achieve higher energy efficiencythan genetic algorithms.The BA-EDIW algorithm will further improve the system rate,and the energy efficiency is about 11% higher than the genetic algorithm.Thirdly,On the basis of spectrum allocation,further study of power resource allocation strategies.Firstly,the upper bounds of the lower bounds and cross-layer interference tolerances of the system transmission rate are simplified for the optimization model.Establish optimization goals with guidelines for maximizing energy efficiency and lower bounds.According to the nature of the score plan,the optimization goal is converted into the subtraction form.Building System Lagrangian Functions.Using Lagrange KKT Iterative Algorithm to Distribute Power of Heterogeneous Networks.The simulation results confirm that the increase of transmission power of large/small base stations and the decrease of user-to-base station distance can increase the cross-layer interference of the system.The impact of the transmission power of large/small base stations on the system energy efficiency and transmission rate is analyzed.Finally,The Lagrange algorithm and BA-EDIW algorithm are applied to the power resource configuration separately.The system energy efficiency and rate performance are simulated.The simulation results show that the Lagrange algorithm can find the optimal energy efficiency faster,but because the optimization model is simplified,the result obtained is the lower bound of the energy efficiency value.The BA-EDIW algorithm requires a longer search time than the Lagrangian algorithm,but the energy efficiency value is about3% higher.