Abstract: For outdoor visible light communication scenarios,existing blind detection algorithms often fail to fit well with the probability density function of the real channel model at the truncation when approximating the channel model,resulting in errors in finding the optimal decision threshold,thus affecting the system’s average symbol error rate performance.Therefore,aiming at the large-scale MIMO outdoor wireless optical communication system,a maximum likelihood blind detection algorithm based on piecewise Gaussian approximation was proposed.In the case of powerful gas turbulence,the algorithm obtains the equivalent channel model superposed by each sub-channel and obeys the gamma distribution.According to the unique extreme point of the equivalent channel probability density function,the left and right segmentation intervals are determined,and the first and second order statistical information of each sub-channel in two segmentation intervals is obtained.Then,by using the central limit theorem and the large number theorem,the equivalent channel is approximated to a Gaussian distribution in both segmentation intervals.The algorithm compensates for the poor fitting of the probability density function of the equivalent channel model and the real channel model at the truncation,and obtains the optimal decision threshold,thus improving the average symbol error rate performance of the system.In order to verify the superiority of the algorithm,the MATLAB simulation experiment was used to compare the average symbol error rate performance between the proposed algorithm and the existing blind detection algorithm.The experimental results show that the average symbol error rate performance of the proposed algorithm is nearly 10 times higher than that of the existing blind detection algorithm when the number of transmitting and receiving antennas is 4 and the signal to noise ratio is small.At the same time,when the number of receiving antennas is 8,the average symbol error rate performance of the proposed algorithm is close to that of the existing blind detection algorithm when the number of receiving antennas is 16,which 50％ the number of receiving antennas.The experimental datas fully demonstrate that compared with the existing blind detection algorithm,the proposed algorithm can significantly improve the average symbol error rate performance of the system with the increase of the number of transmitting and receiving antennas when only the mathematical model and statistical information of the channel are utilized.

Key words: Exponential distribution, Massive MIMO, Maximum likelihood blind detection, Outdoor wireless optical communication, Piecewise Gaussian approximation, Probability density function