Volterra kernel estimation for nonlinear communication channels using deterministic sequences

We present a new exact method for the identification of communication channels with nonlinearities. The channel is modelled as a third-order discrete Volterra filter and the Volterra kernels are measured using deterministic input sequences and the corresponding channel outputs. The solutions are in closed form, exact and kernels are estimated in a nonrecursive manner, thus eliminating error propagation. Complex inputs and complex kernels are allowed, which permits the use of PSK or QAM modulated signals for the identification of the bandpass Volterra channel. Simulation examples and comparison with other methods in the literature are provided to verify the method.