Code optimization for direct sequence spread spectrum and SAW-matched filter implementation

Abstract

This paper introduces a new optimization algorithm for the minimization of the time sidelobes of the correlation function of a pseudonoise (PN) sequence by applying dynamic weighting to the sequence. The resulting optimized time sidelobe level sequences are to be used in direct sequence spread spectrum (DS-SS) systems with digital modulations such as BPSK, DPSK, QPSK, etc. The new optimization algorithm starts with a PN sequence. It first optimizes the correlation time sidelobes for the case where the consecutive data bits are identical (11 or 00). It then optimizes the correlation time sidelobes for the case of alternating consecutive data bits (10 or 01). The suppressed time sidelobe level sequences are derived by iterating these algorithms alternately starting from the initial PN sequence. The derived suppressed time sidelobe sequences show excellent correlation characteristics when compared to conventional PN sequences such as maximal length sequences, Gold sequences and Barker codes. Surface acoustic wave (SAW) devices were used to implement the optimized time sidelobe level sequences in a matched filter pair. The design of the apodized SAW-matched filters and their predicted second order effects are presented. The experimental results for the SAW-matched filters for the optimized time sidelobe level sequences derived from a Barker code were found to be in good agreement with the theoretical predictions from this new algorithm.