Intelligent Optimization Algorithm For Wavefront Correction Technology Of Free Space Optical Communication

Free Space Optical Communication（FSOC）is an essential supplement to traditional wireless communication and optical fiber communication due to its advantages of high confidentiality,strong anti-electromagnetic interference ability,higher channel utilization rate,and faster transmission rate.It has become a hot topic for researchers at home and abroad.Compared with the traditional intensity modulation/direct detection communication mode,coherent FSOC communication has the advantages of higher sensitivity and better-receiving effect,which has attracted wide attention.However,the beam phase and intensity of the FSOC system are distorted and attenuated by the atmospheric turbulence effect,which seriously restricts the development of coherent FSOC technology.How to compensate for the atmospheric channel has become one of the key problems to be solved urgently to promote the development of FSOC technology.Adaptive Optics（AO）is widely used in FSOC systems to mitigate the effects of atmospheric turbulence.Among them,the AO system without wavefront sensing uses a small hardware volume,lightweight,and avoids the traditional wavefront sensor due to multiple splitters caused by power overhead.This thesis uses the AO technology without wavefront sensing in the FSOC system to compensate for the atmosphere effectively.In an AO system without wavefront sensing,the effect of the algorithm directly determines the quality of wavefront correction and directly affects the communication performance of the FSOC system,so an efficient optimization algorithm is very important.This thesis studies two wavefront free sensing algorithms for coherent FSOC systems in AO systems.The first is Stochastic Parallel Gradient Descent-Simulated Annealing（SPGD-SA）mixed blind optimization algorithms.The second is Black Widow Optimization（BWO）algorithm.The main content of this thesis is as follows:（1）SPGD-SA hybrid blind optimization algorithm for FSOC wavefront correction.Although the Stochastic Parallel Gradient Descent（SPGD）algorithm of existing non-wave front sensing technologies has a good convergence effect,it can’t meet the stochastic requirements of FSOC systems as it is slow to converge and is easy to enter the local optimal trap.In this thesis,combining SPGD algorithms with Simulated Annealing（SA）algorithms,a hybrid blind optimization algorithm of SPGD-SA has been proposed,which has the advantages of a fast convergence rate during the initial cooling stage,reducing the number of algorithm iterations and also restraining the tendency of entering into local optimization.In order to verify the feasibility of the algorithm,this thesis fitted atmospheric space channels with different turbulence intensities according to several groups of Zernike data with different strengths.Under different channel conditions,the performance of the hybrid algorithm,traditional SPGD algorithm,and SA algorithm in the FSOC system was analyzed,and the MATLAB software platform was used to conduct simulation experiments on the hybrid algorithm.The experimental results show that the Bit Error Rate（BER）of the wavefront-less AO system controlled by the proposed hybrid algorithm is lower than that of the traditional SPGD algorithm in the FSOC system,regardless of the intensity of atmospheric turbulence.The SA and hybrid algorithms show similar BER in strong atmospheric turbulence,while the hybrid algorithm always has a lower BER in weak atmospheric turbulence.（2）BWO algorithm for FSOC wavefront correction.BWO algorithm is a new swarm intelligent optimization algorithm,including linear and spiral optimization.Compared with the traditional genetic algorithm,it has the advantages of fast convergence speed and good convergence effect.This thesis analyzes the advantages and disadvantages of different swarm intelligent optimization algorithms.On this basis,the BWO algorithm is applied to compensate for the atmospheric channel of the FSOC system to reduce the BER of the system and improve the performance of FSOC system.The simulation results show that the wavefront-free AO system controlled by the BWO algorithm has good stability in different channel conditions and can reduce the influence of wavefront distortion caused by atmospheric turbulence.Within 20 iterations,the BWO algorithm can reduce the communication BER to about1×10^-10,ensuring the communication ability of the system.In this thesis,the performance of the FSOC system based on the blind optimization algorithm and swarm intelligent optimization algorithm is analyzed.Two kinds of intelligent algorithms for FSOC wavefront correction are proposed,providing a choice scheme for improving the performance of FSOC system channel compensation performance.The research content of this thesis has a certain reference value for the design of a coherent FSOC system algorithm without a wavefront sensor and provides a theoretical basis for the development of FSOC technology.