Power Allocation Algorithm For Multi-layer Cellular Networks Based On Energy Harvesting

With the rapid development of new communication service like Internet of Things,machine to machine communication,electronic medical and big data,smart mobile devices begin to be widely applied,and the data rate requirement of wireless communication system becomes higher and higher.The traditional macrocell architecture has been unable to meet the coverage demand of the variable scenario,which has forced the implementation of hierarchical cellular network(HCN).At the same time,the emergence of massive wireless terminal further increases the energy consumption of the base station.Therefore,it's important for mobile communication development to reduce the energy consumption of HCN.Energy Harvesting(EH)using renewable energy as the energy source is a promising technology that can be applied to solve the energy demand issue of heterogeneous cellular network.Hence,research on heterogeneous cellular networks(EH-HCN)based on energy harvesting has become one of the hotspots in the field of green communication.This thesis analyzes the power allocation technologies of energy harvesting based cellular network,focusing on the principle and implementation mechanism of different kinds of power allocation algorithm and energy arrival modeling,and proposes an off-line power allocation algorithm aiming to maximize system efficiency.Firstly,the energy arrival is modeled,and the problem is modeled as the maximum energy efficiency of the system.Then a two-layer iterative algorithm is proposed to allocate the transmit power for each channel to maximize the system energy efficiency.Simulation results show that the proposed algorithm can achieve fast convergence while maximizing the system energy efficiency,which is of great theoretical guidance in guiding the research of power allocation algorithms in heterogeneous networks.However,the analysis shows that,due to the causality of energy arrival.The offline algorithm is not practical enough.Based on this problem,this thesis proposes an online power allocation algorithm.First of all,this algorithm selects the small cell base stations that satisfy the activating condition at the beginning of each time slot via an energy discrimination algorithm.Then allocate the transmit power for those selected small cell base stations to maximize the system efficiency of each time slot by using the two-layer iterative algorithm.Finally,the algorithm is simulated in MATLAB.Simulation results demonstrate the effectiveness of energy harvesting based online power allocation algorithm under different energy arrival rate.When the energy arrival rate satisfies the small cell activating conditions,the proposed algorithm achieves higher energy efficiency compared with the existing algorithm.When other conditions are the same,the proposed algorithm can activate more small cell base stations in a macro cell while maximizing the energy efficiency.