| With the popularity of smart devices and emerging smart applications,mobile data traffic has exploded.To meet the demand of higher data rates and large-scale wireless connections,heterogeneous cloud radio access network(HCRAN)has been introduced,but a large number of low-power nodes and interference between nodes lead to a sharp increase in energy consumption.Therefore,energy efficiency optimization has become a key issue to achieve sustainable network development.Based on the above background,this thesis considers the scheme of mixed use of renewable energy and grid power in HCRAN,and the renewable energy collected by energy harvesting technology is used as a supplement to grid energy.Based on the above scheme,taking user association,sub-channel allocation,power control and renewable energy cooperation between base stations into account,the research proposes effective resource management methods to improve the system energy efficiency.The main contents of this thesis are arranged as follows:(1)To solve the problem of how to effectively utilize renewable energy in two-layer HCRAN and maximize energy efficiency,a scheme of joint power allocation and energy cooperation for small cell users which considers the randomness of renewable energy arrival is proposed under the constraints of user’s quality of service requirements.First,this scheme adopts Dinkelbach’s method to reduce the complexity of proposed optimization algorithm and improve the convergence speed.Then a meta-heuristic algorithm is used to obtain the sub-optimal allocation scheme of renewable energy cooperation between base stations.Finally,power allocation is performed for small cell users by using Lagrangian dual decomposition.The simulation results show that,compared with the scheme without the mechanism of renewable energy cooperation,the proposed scheme reduces grid energy consumption by about 10%,and the total EE of the system increases by about 12%.(2)Increased network utility in NOMA-HCRAN comes at the expense of more energy consumption,resulting in low energy efficiency.To solve the problem of how to balance network utility and grid energy consumption and maximize system revenue,a joint sub-channel and power allocation scheme is proposed.First,the difference between network utility and grid energy cost is defined as system revenue.Then,an optimization problem is established with the goal of maximizing system revenue where the constraints of maximum transmission power,battery capacity of energy harvesting,user’s minimum data rate requirement,and cross-layer interference threshold are considered.Next,the greedy algorithm(GA)is used to pair users and assign sub-channels.This algorithm can fairly assign sub-channels to users,effectively reduce the impact of the cross-layer or same-layer interference,and obtain a low-complexity sub-optimal solution.Finally,the power allocation of small cell users is optimized by using the Lagrangian maximization method based on the alternating direction method of multipliers(ADMM).The simulation results show that,compared with the scheme without considering EH units,the system revenue has increased by about 18.8%;compared with the scheme in OFDMA system equipped with EH units,the system revenue has increased by about 11.8%.Grid energy consumption has reduced by approximately 50%. |
