Modern Permutation Decoding Methods: Energy Efficiency, Cognitive Maps and Innovative Algorithms in Telecommunications

Aqeel L. Khudhair Attaby; Ghufran Abdulqader Alhaddad; Shamam Kadhim

doi:10.26706/ijceae.7.1.20260110

Abstract

This review article provides a comprehensive overview of ten research papers related to permutation decoding (PD) techniques and their implementation in communication systems. The primary objective is to optimize energy efficiency, minimize computational complexity, and enhance transmission reliability at low signal-to-noise ratio (SNR) levels. Applications of permutation decoding for Hamming, BCH, and Reed-Solomon codes are discussed, incorporating cognitive maps, clustering algorithms, fast matrix transformations, and neural network techniques. Cognitive maps are proposed as alternatives to resource-intensive matrix operations, while machine learning approaches demonstrate effectiveness for non-binary codes. Experimental results indicate significant reductions in processing time, improvements in energy efficiency up to 4.5 dB, and reduced error probability levels. The study also identifies limitations, including limited experimental scope and insufficient comparison with modern coding schemes. The findings contribute to advancements in noise-resistant coding, energy-efficient communications, Internet of Things (IoT) systems, and modern telecommunication network design.

Keywords

Permutation Decoding Signal-to-Noise Ratio Energy Efficiency Cognitive Maps Noise-Resistant Coding Internet of Things Wireless Sensor Networks Telecommunication Systems

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