Research On Interference Alignment Algorithm Based On Energy Efficiency Optimization In Heterogeneous Networks

Heterogeneous network(Het Nets),as one of the key technologies of 5G,can improve network capacity and spectrum efficiency.What's more,it also can solve the problem of coverage of blind areas in traditional cellular network.However,Het Nets also brings more and more complicated interference,which leads to a decrease in system's spectral efficiency.However,if the system only focuses on how to reduce the interfernce and ignores the energy efficiency,the performance of system will not be optimal.The thesis focuses on how to reduce the interference in Het Nets,and applies IA technology to suppress the interference,with energy efficiency considered.Firstly,the thesis introduces the basic principles of IA in Het Nets and classic algorithms.With perfect CSI,three classic distributed iterative IA algorithms,including Min IL,Max SINR and MMSE-Based IA,are introduced.IA can achieve a better Do F,which means the sum rate of system will increase with the number of users increasing;At a low SNR,the sum rate of Max SINR is higher than the sum rate of Min IL;When SNR is high,the sum rate of the two algorithms tends to be the same;However,the sum rate of MMSE-Based IA has always been the lowest of all.Secondly,when CSI is imperfect,which means the system exists channel estimation error,the performance of system will decline.Therefore,an improved robust IA algorithm is proposed.It is a non-convex problem.And the thesis uses an iterative solution method to divide this problem into two sub-problems.Then each sub-problem is solved by using the Rayleigh-Reliz method.The effect of channel estimation error on the proposed algorithm is less than the effect on Min IL,Max SINR,and MMSE-Based IA algorithms.The proposed algorithm reduces the influence of channel estimation errors on system and rate performance,makes the system more stable,and more resistant to changes in channel estimation errors,and is more suitable for practical applications.Finally,on the basis of the established power consumption model,the thesis analyzes the energy efficiency of the previous algorithm with the average power allocation.Then the water filling algorithm is applyed to allocate the transmission power.The energy efficiency of each algorithm is simulated again and simulation shows that the water filling algorithm can improve the energy efficiency.Furthermore,the IA algorithm proposed in Chapter 3 can achieve good energy efficiency.And on the basis of that,a maximizing energy efficiency IA is proposed.This model is also a non-convex problem and solved by a zero-gradient-based local optimal solution algorithm.The simulation proves that the Max EEIA algorithm can further improve the energy efficiency of the communication system.