In order to improve the receiving sensitivity of the wireless optical communication system, an AdaBoost weak-light signal detection algorithm based on the improved base classifier coefficient was adopted to solve the signal detection problem of multi-pixel photon counter (MPPC) under weak-light conditions. In this algorithm, k-nearest neighbor (KNN) was used as the base classifier to build a strong classifier. A W-AdaBoost algorithm based on the weights of incorrect and correct classification samples was proposed to solve the problem of that the traditional AdaBoost algorithm’s base classifier coefficients are only related to the error rate, which causes redundant base classifiers to consume system resources. The W-AdaBoost algorithm transforms the issue of signal demodulation into classification, a 450 nm semiconductor laser and MPPC photoelectric conversion device are used to build a wireless optical communication system. The experimental results show that the sensitivity of the improved W-AdaBoost-KNN algorithm is about 1.6 dB and 4.8 dB higher than that of the traditional AdaBoost-KNN algorithm and the single KNN algorithm respectively, when the communication rate of the system is 2 Mbit/s and the bit error rate is 3.8×10-3. The research results show that W-AdaBoost-KNN algorithm can improve the signal detection efficiency under weak-light conditions and improve the receiving sensitivity of the wireless optical communication systems.