Design of computer-optimized pseudorandom maximum length signals for linear identification in the presence of nonlinear distortions

The design of pseudorandom maximum length (PRML) signals for linear identification in the presence of nonlinear distortions is considered. For this application, it is advantageous for the signal to have harmonic multiples of two and three suppressed, in order to minimize the effect of nonlinearity, thus resulting in a better estimate of the underlying linear dynamics. Such signals may be designed through exhaustive search for the sequence-to-signal conversions. However, for signals generated from Galois fields GF(q) with q large, this method is computationally inefficient. An alternative technique is proposed where a primitive version of the signal, the period of which is considerably shorter than that of the required PRML signal, is first generated as a computer-optimized signal. The primitive signal is then used to define the conversions for the generation of the required PRML signal, which is a member of a new class of hybrid signal