BLIND TENSOR-BASED IDENTIFICATION OF MEMORYLESS MULTIUSER VOLTERRA CHANNELS USING SOS AND MODULATION CODES

In this paper, a channel identification technique using Sec-ond 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 con-straints of the transmitted signals. That constitutes a new applica-tion of modulation codes, aiming to introduce temporal redundancy and ensure some statistical properties. Identifiability conditions for the problem under consideration are addressed and simulation re-sults illustrate the performance of the proposed estimation method. 1