An Optimised High Order QAM Soft Demodulation for Wireless Communication

 




 

Tan, Ivan Kai Xi (2019) An Optimised High Order QAM Soft Demodulation for Wireless Communication. Final Year Project (Bachelor), Tunku Abdul Rahman University College.

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Abstract

This paper is targeting on high order QAM soft demodulation for a wireless communication system. Soft bit demodulator is a component that improves turbo decoder performance by performing Log-likelihood-ratios (LLR) which can enhance the function of the turbo decoder. Higher order QAM is preferred in most system as it allows for more bits to be transferred for each symbol especially on 5G communication system as it expected to achieve 20Gbps in data transfer. Therefore, the order of modulation scheme is expected up to 1024 QAM. With a higher number of modulations, the system becomes more complex especially when performing Maximum Likelihood (ML) Log-Map value and performance loss was introduced with the use of Max-Log-Map. Hence, a solution is proposed by developing optimal soft demodulators that improve the performance of the ML Log-Map at lower computational cost. The proposed solution use the Linear Regression algorithm to find the best fit line of the correction function in the Log-MAP Jacobian Algorithm that the Max-Log-MAP ignore. The proposed algorithm has not been done by anyone or any organization before, therefore its totally new idea in the field. The new proposed algorithm would help to improve the accuracy for the system by maintain the computational complexity as well. New proposed Algorithm is proved to have an improvement in performance of 0.028dB. This project will contribute to 5G system in improve the accuracy and stability of the system in future.

Item Type: Final Year Project
Subjects: Technology > Electrical engineering. Electronics engineering
Faculties: Faculty of Engineering > Bachelor of Engineering (Honours) Electrical and Electronics
Depositing User: Library Staff
Date Deposited: 31 Jan 2020 02:34
Last Modified: 31 Jan 2020 02:34
URI: https://eprints.tarc.edu.my/id/eprint/13045