In this paper, we investigate an unsourced random access protocol for massive machine-type communications (mMTC) in the sixth-generation (6G) wireless networks with sporadic data traffic. Firstly, a universal framework of massive unsourced random access, including a two-layer signal coding, i.e., an outer code and an inner code, is provided to achieve efficient massive access with low complexity. Then, considering Rician fading in the scenario of mMTC, we design a novel algorithm for codeword activity detection in unsourced random access based on the distribution of the received signal by exploiting the maximum likelihood (ML) estimation. Finally, simulation results validate the effectiveness of the proposed algorithm.