| In the era of booming wireless communication and internet of things,massive communication equipment have brought a surge of energy consumption to the entire wireless network,which result in increasingly serious economic and environmental problems.The traditional cellular network cannot meet the demand of modern communication traffic only by wireless channel technology and limited bandwidth expansion.How to efficiently manage wireless communication networks has become the key factor for achieving green communication.Note that energy capture technology is an effective way to save energy for base stations in wireless heterogeneous networks.Due to the randomness and volatility of green energy,hybrid energy of electric energy and green energy are used to drive the base station so that they can ensure the quality of communication.However,the energy-saving of heterogeneous network driven by hybrid energy still has some shortcomings,which is mainly reflected in the imbalance of base station load and low utilization rate of green energy caused by energy heterogeneity.Therefore,effective user association strategy and resource management strategy are of great significance for energy saving of hybrid energy driven wireless heterogeneous networks.The main contributions of this dissertation can be summarized as follows:First,the basic theory of hybrid energy heterogeneous network is summarized,including hybrid energy wireless heterogeneous network,energy-saving management technology and its evaluation standards,as well as related optimization theory.Second,we focus on the load balancing and spectrum resource waste caused by the network architecture and energy heterogeneity in a homogeneously distributed hybrid energy heterogeneous network scenario.Here,an approach of user association mechanism and resource allocation strategy is proposed for a given communication rate.In order to minimize the total energy of system,the bias factor of the SBS’ favorite is used to describe the extent of user association,and an estimation algorithm of energy hungry probability is presented for uncertainty reduction in energy by utilizing the large deviation theory.Moreover,the resource allocation strategy is proposed to allocate band resource reasonably through the Lagrange dual algorithm.Numerical simulation results show that the energy consumption of the proposed algorithm can reduce 82.47%.Also,the utilization rate of green energy of the proposed algorithm will increase 48% than that of the maximum channel gain algorithm.Third,in a heterogeneous network with heterogeneously distributed hybrid energy,high-power macro base stations have a certain degree of rejection.If the deployed micro base stations are too close to MBS,the communication quality will decrease.In addition,the arrival of energy in micro base stations with energy capture has random fluctuations,and the leakage of energy storage batteries may reduce the availability of the network.We firstly model the network as a Poisson Hole Process(PHP),and derive the network interruption probability under the PHP model.Next,a power-aware user association and renewable energy configuration schemes are proposed with the goal of optimizing network energy consumption.In the case,power-aware user association rules can dynamically obtain the available set of associated base stations by predicting the power required by other users in each time slot.Meanwhile,the Lyapunov optimization method is used in a single time slot to control the power consumed by each user,and heuristic algorithms are designed to balance green energy in different time slots.Numerical simulation results verify the feasibility of the proposed scheme.Furthermore,the proposed scheme is superior to other schemes in optimizing power grid energy consumption. |
