An Introduction to Spread-Spectrum Communications
An Introduction to Spread-Spectrum Communications
Probability and Random Processes For EE's (3rd Edition)
Probability and Random Processes For EE's (3rd Edition)
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
Proceedings of the 2007 conference on Artificial Intelligence Research and Development
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Pseudonoise (PN) sequence sets must fulfill crosscorrelation properties in order to minimize multiuser interference. These properties are satisfied by the mathematical methods used to design these sets. In multiuser spread spectrum signals working with multiresolutive receivers, the pseudonoise sequences need to have more features for the proper performance of the acquisition scheme. In this paper we present an algorithm inspired by Evolution Strategies to design a set of pseudonoise sequences meeting all the constraints that the receiver demands. The new pseudonoise sequence set accomplishes not only the basic pseudorandom waveform properties but also the new crosscorrelation features required by the multiresolutive structure, obtaining better results in terms of crosscorrelation and stability. This way the acquisition is improved in the spread spectrum receiver.