Research On Polar Codes With Low-Complexity Encoding And Decoding In Wireless Optical Communication

Wireless optical communication is a wireless communication technology that uses laser as the information carrier and the atmosphere as the transmission medium.It has the advantages of high transmission rate,large communication capacity,good confidentiality,and convenient installation.However,due to the susceptibility to the atmospheric environment,the laser signal transmission in the atmosphere lacks stability and reliability.Channel coding technology can reduce the influence of atmospheric channels on laser signals without changing the structure of transmitters and receivers.Currently,channel coding technologies used in wireless optical communications include RS codes,Turbo codes,and LDPC codes.As an emerging channel coding technology,polar code is the only channel coding technology that has been strictly mathematically proven to reach the Shannon limit under the B-DMC channel,and has been applied to 5G communications.The application of polar codes in wireless optical communications is still in its infancy and has great research value and room for improvement.This thesis takes this as a starting point to carry out further research on the coding and decoding technology of polar codes in wireless optical communications.This article first introduces the current status of wireless optical communications at home and abroad and the channel coding technology in wireless optical communications,and expounds the development of polar codes and the current research status at home and abroad.After that,it analyzes the influence of atmospheric environment on wireless optical communication,mainly including atmospheric attenuation effect and atmospheric turbulence effect,briefly introduces the influence of atmospheric absorption and atmospheric scattering on optical signal in atmospheric attenuation effect,and focuses on atmospheric turbulence effect and atmospheric turbulence effect.Its statistical characteristics,and the principle of light intensity scintillation are studied and analyzed,and the log-normal distribution channel model and Gamma-Gamma distribution channel model similar to the atmospheric turbulence channel are given.Then,the channel polarization principle,information bit selection method and decoding algorithm of the polar code are studied and analyzed in detail,and several commonly used information bit selection methods and decoding algorithms are given.Based on the research and analysis of wireless optical communications and polar codes,a method for selecting information bits of polar codes for atmospheric turbulence channels is proposed,including the turbulence partial sequence method for selecting information bits of polar codes in weak turbulence channels and The segmented turbulence partial order method for the selection of information bits of the polar code in the strong turbulence channel,and the specific information bit selection schemes are respectively given;after that,the simulation analysis of different code lengths and code rates is carried out in the turbulent channel,and the simulation analysis is carried out with Monte Carlo.Comparing the Carlo method,the results show that the two information bit selection methods can obtain the error performance similar to Monte Carlo method in the suitable turbulence section,which reduces the complexity of the polar code information bit selection in wireless optical communication and improves In order to improve the transmission efficiency,compared with Monte Carlo method,the two information bit selection methods proposed in this paper are more suitable for wireless optical communication systems.Finally,the pruning algorithm is introduced into the polar code decoding,and the tree graph pruning-segmented cyclic redundancy check auxiliary SCL decoding algorithm is proposed,and the performance and decoding complexity of the algorithm are simulated and analyzed in a turbulent channel.The simulation results show that the error performance of the algorithm is better than that of the SCL decoding algorithm,and with less loss,it can obtain a smaller decoding complexity than the SCL decoding algorithm.