This paper discusses a single-channel speech enhancement method for cochlear implant listeners. It is assumed that the Fourier Transform coefficients of speech and background noise have different statistical distributions. A statistical-model-based method is adopted to update the signal-to-noise ratio and estimate the background noise so that the musical noise and speech distortion induced by traditional spectral subtraction method can be effectively reduced. This enhancement method was evaluated on seven postlingually deaf Chinese cochlear implant listeners in comparison with other two speech enhancement methods. Test materials were Mandarin sentences corrupted by three different types of background noise. Experimental results showed that the proposed speech enhancement method could benefit the speech intelligibility of Chinese cochlear implant listeners. The results suggest that different noise types may affect the performance of different speech enhancement algorithms.