BER ANALYSIS OF CHANNEL CODING TECHNIQUES FOR 5G NETWORKS

Project Code :TMMACO145

Objective

The objective is to analyze and evaluate low-complexity error correction coding techniques, focusing on LDPC and convolutional codes, for enhancing Bit Error Rate (BER) performance in next-generation 5G wireless communication systems.

Abstract

Everybody since wireless technology serves as the foundation for dependable communication, achieving error-free communication is the main problem. However, because wireless channels are impaired, it is almost impossible to communicate without errors. A channel coding approach is the workable choice for dependable communication with a low error rate. In different wireless communication generations, RS, convolutional codes, turbo codes, and other channel encoding techniques are employed. A new kind of channel coding strategy that prioritizes low complexity and decreased bit error rate is required for the more advanced 5G technologies. The bit error rate and complexity of potential error correction coding techniques for 5G technology are examined in this system. Convolutional and LDPC codes are the two channel coding algorithms that are the primary emphasis of this suggested system. The viability of using LDPC codes with 5G wireless communication is assessed in terms of BER performance and complexity, and it is contrasted with both coded and uncoded convolutional codes. LDPC codes are currently utilized in 4G technologies. According to the results, LDPC codes perform better than other coded systems in terms of BER and complexity. They also help the MIMO-OFDM system reach a channel capacity that is closer to the Shannon limit. It is clear from the research that have been done that LDPC codes perform exceptionally well in terms of BER, making them suitable for use in next-generation wireless communication.

Keywords: MIMO-OFDM system, Convolutional codes, LDPC codes, turbo codes, Bit Error Rate (BER).

NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.

Block Diagram

Specifications

Software: Matlab 2020a or above

Hardware:

Operating Systems:

  • Windows 10
  • Windows 7 Service Pack 1
  • Windows Server 2019
  • Windows Server 2016

Processors:

Minimum: Any Intel or AMD x86-64 processor

Recommended: Any Intel or AMD x86-64 processor with four logical cores and AVX2 instruction set support

Disk:

Minimum: 2.9 GB of HDD space for MATLAB only, 5-8 GB for a typical installation

Recommended: An SSD is recommended A full installation of all MathWorks products may take up to 29 GB of disk space

RAM:

Minimum: 4 GB

Recommended: 8 GB

 

Learning Outcomes

·         Introduction to Matlab

·         What is EISPACK & LINPACK

·         How to start with MATLAB

·         About Matlab language

·         Matlab coding skills

·         About tools & libraries

·         Application Program Interface in Matlab

·         About Matlab desktop

·         How to use Matlab editor to create M-Files

·         Features of Matlab

·         Basics on Matlab

·         What is Communication?

·         About Communication

·         Introduction to Communication

·         How Communication Works?

·         Importing the System Design, Characterization and Visualization

·         Analyzing of BER tool

·         Analyzing of Error Rate Test Console

·         Generation of WSN

·         WSN network creation

·         Nodes Communication

·         Clustering

·         Routing

·         Convolutional

·         Equalization and Synchronization etc.,

·         How to extend our work to another real time applications

·         Project development Skills

               o    Problem analyzing skills

               o    Problem solving skills

               o    Creativity and imaginary skills

               o    Programming skills

               o    Deployment

               o    Testing skills

               o    Debugging skills

               o    Project presentation skills

               o    Thesis writing skills

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