305 / 2017-02-13 16:21:07
Interleaver with High Dimensional Encoding Principle using Hybrid Group Search Optimizer
12802,12803,12804,9283,12805
Draft Accepted
Rutuja Deshmukh / D. Y. patil College of Engineering
Handling high dimensional data and an effective error correcting code with low complexity are the two main challenges in the communication system. In the first paper, we focused on the second problem of error correcting code and introduced a turbo encoder with an interleaver which uses a hybrid meta-heuristic search algorithm by combining renowned Genetic Algorithm (GA) and Group Search Optimizer (GSO) in the name of hybrid GSO (HGSO) and that performs the high dimensional data transmission. Such a high dimensional data has transformed to low dimensional data by introducing a new high dimension interleaver in the conventional design in which data transformation and optimal pattern generation has taken place using the recent meta-heuristic search algorithm. The performance of the proposed system has compared with the existing GSO, GA, FA, ABC and random interleaver design in terms of signal to noise ratio (SNR), BER and FER and also the computation time is computed for each component of both existing and proposed system. Finally, the experimental results shows that the proposed high dimension interleaver design using HGSO approach performs well than any other methods.
Important Date
  • Conference Date

    Mar 22

    2017

    to

    Mar 24

    2017

  • Feb 15 2017

    Draft paper submission deadline

  • Feb 20 2017

    Draft Paper Acceptance Notification

  • Feb 22 2017

    Final Paper Deadline

  • Mar 24 2017

    Registration deadline