Blind tensor-based identification of memoryless multiuser Volterra channels using SOS and modulation codes

In this paper, a channel identification technique using Second Order Statistics (SOS) is proposed for memoryless multiuser Volterra communication channels. The Parallel Factor (PARAFAC) decomposition of a third order tensor formed from spatio-temporal covariance matrices of the received signals is considered by using the Alternating Least Squares (ALS) algorithm. Modulation codes (constrained codes) are used to ensure some orthogonality constraints of the transmitted signals. That constitutes a new application of modulation codes, aiming to introduce temporal redundancy and ensure some statistical properties. Identifiability conditions for the problem under consideration are addressed and simulation results illustrate the performance of the proposed estimation method.