In this paper, we present a tensor MIMO-GFDM system model that is based on the double contraction operator. Based on the derived system model, we propose an iterative tensor based MIMO-GFDM receiver, that is initialized with the channel estimation obtained via pilots transmitted in the first data frame. The proposed algorithm exploits the tensor structure by using several unfoldings of the received signal sequentially to obtain estimates of the transmitted symbols and the channel. Simulation results show the tensor gain for the proposed algorithm in addition to the improved channel estimation. Numerical results confirm that the receiver requires the same amount of pilots as the Zero Forcing (ZF) receiver, while having a better symbol error rate (SER) performance and a better channel estimation accuracy.