Tensor-based blind signal recovery for multi-carrier amplify-and-forward relay networks

Cooperative communications have great potentials in performance enhancement via deploying relay nodes. However, these kinds of benefits usually come at the cost of more system parameters to be estimated. This fact definitely reduces the efficiency of wireless systems and then it motivates the research on the blind algorithms for cooperative communications that need fewer parameters. In this paper, we investigate the parallel factors (PARAFAC) decomposition-based blind signal recovery algorithm design for two-hop amplify-and-forward (AF) multi-carrier cooperative networks. In particular, the uniqueness of the PARAFAC decomposition used in the proposed algorithm is first investigated in detail, and then the performance of signal recovery is analyzed. Finally, the simulation results assess the performance of our proposed algorithm.