  In this letter, we propose a novel tensor-based modulation scheme for massive
unsourced random access. The proposed modulation can be deemed as a summation
of third-order tensors, of which the factors are representatives of subspaces.
A constellation design based on high-dimensional Grassmann manifold is
presented for information encoding. The uniqueness of tensor decomposition
provides theoretical guarantee for active user separation. Simulation results
show that our proposed method outperforms the state-of-the-art tensor-based
modulation.
