The modulation recognition problem of subcarriers in the universal filter multi-carrier (UFMC) system for non-cooperative communication needs to be addressed. Therefore, a modulation recognition algorithm based on feature fusion is proposed for the UFMC system. Firstly, the receiver signal of the UFMC system is obtained and input features such as in-phase and quadrature sequence and amplitude phase sequence are extracted. Subsequently, a neural network module is constructed by connecting a convolutional neural network with a long short-term memory network in series, while also incorporating a gated recurrent unit in parallel. Finally, modulation recognition of UFMC system subcarriers is performed. The experimental results demonstrate that the constructed neural network effectively identifies five signals (BPSK, 4QAM, 8QAM, 16QAM, 64QAM) with a recognition accuracy reaching 100% when signal to noise ratio greater than or equal to 6 dB.