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A novel modified ant lion optimizer algorithm: extension to proposed 4D-TC

A novel modified ant lion optimizer algorithm: extension to proposed 4D-TC

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In this chapter, a novel algorithm named as modified ant lion optimizer (MALO) algorithm has been suggested for the improvement of convergence behavior of the existing ALO algorithm. Moreover, a new form of turbo code (TC) termed as 4D-TC has also been projected for the enhancement of the minimum Hamming distance of the existing TCs. Thereafter, the MALO algorithm has been judiciously used for the design of power efficient 4D-TC. From the simulated outcomes, it is obvious that the high-grade act of MALO algorithm is pretty remarkable than the existing ALO as well as other optimization procedures like particle swarm optimization, Cuckoo search and Harmony search in the matter of exactness and confluence standpoint. Additionally, it has been witnessed that the projected modification on ALO algorithm provides the best optimum value close to theoretical limit by adopting fast exploration and exploitation process over the other algorithms. At the same time, it has also been established that the projected 4D-TC offers substantial improvement in BER act over the others like parallel concatenated convolution turbo code (PCCTC), serially concatenated convolution turbo code (SCCTC), and 3D-TC. The supremacy of MALO has been observed for eight states as well as 16 states 4D-TCs over the other variance like PCCTC, SCCTC, 3D-TC and proposed 4D-TC by means of bit error rate (BER) performance by allocating the optimum power to the systematic and parity bits. Analogous enhancements in BER act have been detected with puncturing as well.

Chapter Contents:

  • Abstract
  • 6.1 Introduction
  • 6.2 Literature review
  • 6.3 Algorithms
  • 6.3.1 Particle swarm optimization algorithm
  • 6.3.2 Harmony search optimization algorithm
  • 6.3.3 Cuckoo search (CS) algorithm
  • 6.3.4 Ant lion optimization algorithm
  • 6.3.5 Proposed modified ant lion optimization algorithm
  • 6.4 Results
  • 6.5 Applications
  • 6.5.1 System model
  • 6.5.1.1 Encoder
  • 6.5.1.2 Interleaver
  • 6.5.1.3 Postencoder
  • 6.5.1.4 Decoder
  • 6.5.2 Problem formulation
  • 6.5.3 Pseudo code
  • 6.5.4 Results
  • 6.5.5 Discussion
  • 6.6 Conclusion
  • References

Inspec keywords: convolutional codes; mathematics computing; particle swarm optimisation; turbo codes; error statistics; optimisation; concatenated codes; search problems; evolutionary computation

Other keywords: parallel concatenated convolution turbo code; modified ant lion optimizer algorithm; MALO algorithm; existing ALO algorithm; 3D-TC; optimization procedures; particle swarm optimization; existing TCs; 16 states 4D-TCs; minimum Hamming distance; power efficient 4D-TC; BER act

Subjects: Other topics in statistics; Codes; Optimisation techniques; Optimisation techniques

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