Parameter Estimation For 60GHz Millimeter-wave System Based On Particle Swarm Optimization Algorithm

As the resources of frequency spectrum are becoming more and more scarce,the 60GHz millimeter wave wireless communication system is one of the hot topics in both academic and industrial fields due to its good international universality and the use of free license application,as well as the unique advantages of Gbps high speed transmission rate and excellent anti jamming performance and security.In the 60GHz communication system,as a result of the high attenuation propagation characteristics of the 60GHz signal,the power amplifier needs to amplify the modulated RF signal to meet the requirements of the level,so as to ensure that the signal to noise ratio(SNR)of the receiver side can meet the requirements.However,the operating point of the amplifier is usually in the nonlinear region near the saturation point,which brings serious nonlinear distortion,leading to the system performance degradation.Therefore,in order to compensate the nonlinear distortion of the power amplifier,it is very important to estimate the nonlinear parameters of the power amplifier.The innovation point of this paper is that it is the first time to apply the classical particle swarm optimization algorithm(PSO)and its modified algorithm(MPSO)to solve the problem of the nonlinear parameter estimation in the 60GHz millimeter wave wireless communication system.Based on the analysis of single diameter of 60GHz system after Gaussian channel model and nonlinear model of the power amplifier on the system model,the problem is abstracted as a fitness function,then a series of nonlinear estimation researches based on PSO algorithm are operated.A new method of solving the problem of the nonlinear parameter estimation in 60GHz mm-wave wireless communication systems with power amplifiers is provided.Based on the standard PSO algorithm,the process of the nonlinear parameter estimation in 60GHz channel is designed and simulated.In this paper,the influence of PSO parameters on the estimation performance is discussed,including the influence of value strategy of inertia weight,the several situations of learning factor,the maximum speed limit and population size on the estimation performance and estimation accuracy.The simulation results show that it is useful to apply the standard particle swarm algorithm to the linear parameter estimation of 60 GHZ system,which can quickly converge to the optimal value to meet the requirements.The thoughtless of the specific issues is becoming the obvious problems of the standard PSO algorithm due to the strong compatibility.On the basis of this,the modified particle swarm optimization(MPSO)algorithm and standard PSO algorithm are compared.The MPSO algorithm is modified with the initialization of the particles,the addition of mutation factor and parameter settings,which is to find a more suitable particle swarm optimization algorithm for our 60GHz channel model.The results show that the MPSO algorithm is more suitable for the 60GHz nonlinear estimation.