Research On Technologies Of Green Wireless Communications Based On Energy Harvesting And Heterogeneous Network

With the rapid growth of the number of global mobile users,and the increasing demand for highbandwidth and high-traffic services such as video-on-demand and online games,the research of next generation mobile communication technologies has been widely carried out and gained abundant achievements.At the same time,the energy consumption of mobile communication networks is also growing rapidly,which leads to numerous greenhouse gas emissions and serious economic and ecological problems.Therefore,the research of green wireless communications has attracted worldwide attention.Energy harvesting and heterogeneous networks are the two important technical routes to realize green wireless communications.This dissertation focuses on the research of these two aspects.The main contents are summarized below.First,the secrecy energy efficiency maximization(SEEM)problem is studied in a single cell multiple input multiple output(MISO)system.A single legitimate user and multiple eavesdroppers who are involved in the system exploit power splitting scheme for radio frequency energy harvesting.In order to prevent eavesdroppers,artificial noise is added into the confidential signals for the legitimate user at the base station.Considering that the base station has imperfect channel state information,a joint optimization problem with the power of confidential signals,the power of artificial noise and the power splitting ratio of the legitimate user to be the variables is established and formulated,and the constraints are the minimum secrecy rate,the minimum harvested energy,the power splitting ratio and the maximum transmission power of the base station.By introducing an auxiliary relaxation variable,the original non-convex fractional optimization problem is transferred into an equivalent two-layer iterative optimization problem.The outer optimization problem is solved through a one-dimensional search algorithm,while the optimal solution of the inner one is obtained by Dinkelbach method.The closed-form expressions of the power of confidential signal and artificial noise are also derived.Simulation results show that the proposed robust SEEM algorithm can achieve a good performance on system secrecy energy efficiency,and has a good convergence and a low computational complexity.Then,the energy efficiency problem in a single cell distributed antenna system(DAS)is studied.The user with single antenna in the cell has the ability of radio frequency energy harvesting.By considering the constraints of minimum harvested energy,the power splitting ratio and the maximum transmission power of each remote antenna unit(RAU),a fractional optimization problem is formulated,with the system energy efficiency maximization as the objective function.Through the analysis of the Karush-Kuhn-Tucker(KKT)conditions of the problem,some specific properties of the optimal solution are revealed,and the closed-form expressions of the optimal transmission power of each RAU are also deduced.A two-level iterative optimization algorithm is then proposed to maximize the system energy efficiency.Simulation results show that the performance of the proposed algorithm is much better than that of the sub-optimal Dinkelbach algorithm and that of the spectrum efficiency(SE)maximization algorithm.Next,the problem of minimizing energy consumption of macro base station(MBS)in two-tier heterogeneous wireless caching networks is studied,where the non-ignorable circuit power consumption is taken into account.Considering the proactive knowledge of the demand rates of users,an infinite-dimensional joint optimization problem with the transmission rate of MBS and the cache rate of the small base station(SBS)as the optimization variables is established.Through the insightful characteristics of the optimal transmission rate and the cache rate,and the variable substitution method,the original optimization problem is transformed into a finite-dimensional piece-wise convex optimization problem.Due to the high complexities of the traditional convex optimization methods,this paper investigates an optimal transmission scheme of MBS under given cache policy.Based on the analysis of KKT conditions,the properties of the optimal transmission strategy for minimizing the energy consumption of MBS are deduced,and an off-line energy efficiency optimal transmission scheme is furtherly proposed.Simulation results show that the proposed scheme can greatly reduce the energy consumption of MBS under different cache capacities and file request popularity,which verifies the effectiveness of the proposed algorithm.Finally,the capacity and the energy efficiency performance of a multi-user multiple input multiple output(MU-MIMO)heterogeneous cellular network which deploys device-to-device(D2D)communication are studied.The system sum rate maximization problem is firstly considered while assuming D2 D users cannot perform energy harvesting.A heuristic joint zero-forcing beamforming and interference alignment(JZFBFIA)algorithm is proposed to solve the NP-hard integer programming problem,which can make full use of the spatial freedom of multiple antennas at the base station,reduce the interference from the base station to the D2 D users greatly,and improve the performance of system capacity significantly.Subsequently,the system sum rate maximization problem is extended to the scenario that the D2 D users exploit time switching(TS)scheme for energy harvesting.The closed-form expression of the optimal time switching ratio is also derived.In the end,the expressions of system energy efficiency under the above two scenarios are given.Simulation results show that the proposed JZFBFIA algorithm has significant advantages in improving the system capacity,increasing the number of the admitted D2 D users,and improving the system energy efficiency.