AI SearchAlgorithms for the selection of Direct Sequence Spread Spectrum Multiple Access (DS/SSMA) signature sequences
Call Number: AIT RSPR no. TC-93-06 Material type:
SeriesSeries: Asian Institute of Technology. Research studies project report ; no. TC-93-06Publication details: Bangkok : Asian Institute of Technology, 1993Description: 56 leaves + 1 online resourceSubject(s): Online resources: Dissertation note: Research Studies Project Report (M.Eng.) - Asian Institute of Technology, 1993 Summary: Sorting algorithms have been proposed for finding subsets of Direct Sequence Spread Spectrum Multiple Access (DS/SSMA) signature sequences with small cross-correlation magnitudes. Two algorithms, the Discarding (DS)-Algorithm and the Enhancing (ES)-Algorithm, have been used to investigate the performance of the subset mean AIP value under worst case interference conditions. Based on an AIP testing criterion, the ES-Algorithm used in conjunction with the Maximum Sidelobe Energy (MSE) initial phase condition has successfully achieved smaller subset mean AIP values when the subset size is small. The Signal-to-Noise Ratio (SNR) is used as a measure at the correlator output. The SNR performance of mean AIP subsets using both algorithms is evaluated and compared with expected values for random binary sequences.
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A research submitted in partial fulfillment of the requirement for the degree of Master of Engineering, School of Engineering and Technology
Research Studies Project Report (M.Eng.) - Asian Institute of Technology, 1993
Sorting algorithms have been proposed for finding subsets of Direct Sequence Spread Spectrum Multiple Access (DS/SSMA) signature sequences with small cross-correlation magnitudes. Two algorithms, the Discarding (DS)-Algorithm and the Enhancing (ES)-Algorithm, have been used to investigate the performance of the subset mean AIP value under worst case interference conditions. Based on an AIP testing criterion, the ES-Algorithm used in conjunction with the Maximum Sidelobe Energy (MSE) initial phase condition has successfully achieved smaller subset mean AIP values when the subset size is small. The Signal-to-Noise Ratio (SNR) is used as a measure at the correlator output. The SNR performance of mean AIP subsets using both algorithms is evaluated and compared with expected values for random binary sequences.
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