World Academy of Science, Engineering and Technology
Published September 29, 2007 | Version 15117
Journal article Open

Spread Spectrum Code Estimation by Genetic Algorithm

Description

In the context of spectrum surveillance, a method to recover the code of spread spectrum signal is presented, whereas the receiver has no knowledge of the transmitter-s spreading sequence. The approach is based on a genetic algorithm (GA), which is forced to model the received signal. Genetic algorithms (GAs) are well known for their robustness in solving complex optimization problems. Experimental results show that the method provides a good estimation, even when the signal power is below the noise power.

Files

15117.pdf

Files (118.2 kB)

Name Size
md5:3594d68c78d0ca1f2d560f1f5fd512d2
118.2 kB Preview Download

Additional details

References

  • D. Thomas Magill, Francis D. Natali, Gwyn P. Edwards, "Spread Spectrum Technology for Commercial Applications," Proceeding of the IEEE, vol. 82, pp. 572-584, April. 1994.
  • Raymond. L. Picholtz, Doland L. Schilling, Laurence B. Milstein, "Theory of Spread Spectrum Communications - A Tutorial," IEEE Transactions on Communications, vol. COM-30, pp. 855-884, May. 1982.
  • John G. Proakis, Digital communication, Third Edition, Mac Graw Hill International Editions, 1995.
  • Dilip V. Sarwate, Michael B. Pursley, "Crosscorrelation Properties of Pseudo-random and Related Sequences," Proceeding of the IEEE, vol. 68, pp. 593-619, May. 1980.
  • Michail K. Tsatsanis, Georgios B. Giannakis, "Blind Estimation of Direct Sequence Spread Spectrum Signals in Multipath," IEEE Transactions on Signal Processing, vol. 45, pp. 1241-1252, May. 1997.
  • J.-M. Renders and S. P. Flasse, "Hybrid methods using genetic algorithms for global optimization," IEEE Trans. Systems, Man, CyberneticsÔÇöPart B: Cybernetics, vol. 26, pp. 243-258, April. 1996.
  • J. H. Holland, Adaptation in Natural and Artificial Systems, Ann Arbor, MI: Univ. Michigan Press, 1975.
  • M. Mitchell, An Introduction to Genetic Algorithms. Cambridge, MA: MIT Press, 1996.
  • D. E. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning. Reading, MA: Addison-Wesley, 1989.r publication.