Research On Energy Conservation In LTE/LTE-Advanced Cellular Network

In recent years,environmental problems such as global warming and exhaust emissions have become more and more severe,which causes serious economic losses and various social responsibility issues.Mobile communication industry has became an important source of environmental problems with the great increase of data requirement in cellular network.The number of types of data demand has also increased along with the data amount,and we know that different types of users have different satisfaction of the amount of resource they obtain.However,traditional Energy Efficiency(EE)problems often assume that there only exists one type of user in the network.Therefore,how to solve the EE problems with various types of users in system has become one of the important topics of today's wireless communications industry.This thesis focuses on the resource allocation problem in Orthogonal Frequency Division Multiple Ac-cess(OFDMA)Heterogeneous Networks(HetNets)with various types of users,and aims at improving the utility-based Energy Efficiency(UEE)by allocating resource blocks(RBs)and power dynamically.Firstly,we formulate a joint optimization problem to maximize the UEE for OFDMA heterogeneous networks.Since macro BSs and low power BSs share the same frequency band,inter-cell interference is present,which makes the mathematical model of the problem very complicated.Based on the analysis of the formulation,the original problem is decomposed into two sub-problems,i.e.,the RB assignment problem and the power allocation problem.Based on the users' characteristics,a heuristic algorithm is proposed for the former problem,while the latter one can be solved by a conventional convex optimization method with the help of a lower bound approximation strategy and proper variable conversion.After solving the two subproblem respectively,an iterative algorithm which dynamically decides the RB assignment and the power on each RB is proposed.Finally,we conduct some simulations,and the result represents our proposed algorithm can achieve better UEE and user fairness compared with existing schemes.The above work only consider the UEE of the system,however,the system utility is also an important metric.Therefore,as an improvement,the thesis further studies the tradeoff between the UEE and system utility.We consider a small cell enhancement(SCE)scenario,where the problem is first formulated as a multi-objective optimization problem(MOP),and then it is transformed into a single-objective optimization problem(SOP)with different weights,where the corresponding objective function is defined as utility re-source efficiency(URE).Since the problem is also NP-hard,a similar decomposition method as the above problem is adopted,where a different lower bound approximation strategy and different variable conversion are introduced in the power allocation process.Meanwhile,a particle swarm optimization(PSO)algorithm is used to solve the power allocation problem.Finally,an iterative resource allocation algorithm for maximizing the system URE is proposed.Simulation results shows that the proposed algorithm outperforms some existing schemes on URE and user fairness.