Sixteen phase Code Design Using Modified Genetic Algorithm


A Modified Genetic Algorithm (MGA) is proposed as a statistical technique for obtaining approximate solutions to combinatorial optimization problems. The Proposed algorithm is a combination of Genetic Algorithm (GA) and Hamming Scan algorithms. It combines the good methodologies of the two algorithms like global minimum converging property of GA algorithm and fast convergence rate of Hamming scan algorithm. Sequences with low aperiodic autocorrelation sidelobe levels are useful for channel estimation, radar, and spread spectrum communication applications. In this paper MGA is used to design Sixteen-phase sequences, which have good autocorrelation properties. Barker codes up to length 19 with maximum alphabet size of only 16 are found. The sequences of lengths from 24 to 49 have autocorrelation properties better than well known Frank codes. The synthesized 16-phase sequences are promising for practical application to radar and communication. The convergence rate of MGA is shown to be good.

  • Abstract
  • 1 Introduction
  • 2. Sixteen Phase Sequences
  • 3. Discriminating Factor (DF)
  • 4. Hamming Scan Algorithm
  • 5. Genetic Algorithm (GA)
  • 6. Modified Genetic Algorithm (MGA)
  • 7. Sixteen Phase Sequences Design Using MGA
  • 8. Results
  • 9. Conclusions
  • References

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