Research On Beam Pattern Optimization And Correction Of The Antenna Arrays Based On Swarm Intelligence

Antenna arrays play a more and more important role in modern wireless communications,especially in mobile communications,satellite communications,and radar systems.But the number of communication users and their communication needs are rapidly increasing at an exponential rate,this makes the spectrum resources increasingly scarce.So,in order to fully utilize the limited spectrum resources,and improve the communication efficiency of communications,the innovation of the various technologies of antenna arrays has become a key topic for the related researchers.Antenna arrays can be used to enhance the communication range,the signal quality,the coverage area,the connectivity rate and the spectral efficiency of communication systems effectively,and the radiation beam patterns of antenna arrays have a decisive role in the performance of communication systems.The technology of propagating the electromagnetic wave in a specific direction is called beamforming which can be generated by antenna arrays,and the radiation beam pattern synthesis of antenna arrays is precisely the basic element for the realization of beamforming.The structure of an antenna array is made up of a number of single antennas arranged in a particular shape,and the parameters such as the number,position,excitation phase and excitation amplitude of array elements in the antenna array all can control the radiation characteristics of the whole antenna array.At present,the radiation beam pattern synthesis of antenna arrays refers to using intelligent means to adjust and determine the related parameters in the antenna array,and to make the final radiation beam pattern can reach or approach the desired result.There are many criteria for measuring the performance of antenna arrays,including beam width,sidelobe level(SLL),noise sensitivity,directivity,robustness and so on.This paper researches radiation beam patterns of antenna arrays based on swarm intelligence optimization algorithms,and to make them with minimized maximum SLLs.The main work of this paper is as follows:(1)Firstly,this paper makes an in-depth analysis of the biogeography-based optimization(BBO)algorithm,and discovers that the updating procedure of BBO can make the solution get into the local optimum easily.For this problem,this paper presents a biogeography-based optimization algorithm with a new local search strategy and a selection operator(BBOLS),and uses it to determine an optimal set of excitation current values for linear antenna arrays(LAAs)and an optimal set of excitation current as well as spacing values for circular antenna arrays(CAAs),and to make the radiation beam patterns with minimized maximum SLLs.Various simulations are performed to examine the effectiveness of the proposed BBOLS algorithm in minimizing maximum SLLs of the radiation beam patterns of LAAs and CAAs,the results show that BBOLS algorithm has a better performance than BBO,firefly algorithm(FA)and particle swarm optimization algorithm(PSO).(2)And then,this paper makes a careful research on the question of the radiation beam patterns correction of the LAAs with element failures and CAAs with element failures,and the optimization mechanism of the invasive weed optimization algorithm(IWO),respectively.From these research results,it can be found that the structure of IWO is very simple,and the reproduction and spatial dispersal operations in this algorithm can avoid the solution falling into local optimal effectively.So,this paper presents use IWO to correct the radiation beam patterns of LAAs with element failures and CAAs with element failures,and to make them with minimized maximum SLLs.The simulation results show that IWO can better correct the radiation beam patterns of LAAs with element failures and CAAs with element failures,and minimize their maximum SLLs compared with cuckoo search algorithm(CS),FA,BBO and PSO.