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Performance Evaluation of Different QAM Techniques Using Matlab/Simulink Submitted by VENKATARAJ R Under the Guidance of D. VIJAYALAKSHMI Assistant Professor Department of Electronics & Communications Engineering
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Page 1: Performance evaluation of different qam

Performance Evaluation of Different QAM Techniques Using Matlab/Simulink

Submitted byVENKATARAJ R

Under the Guidance of D. VIJAYALAKSHMI

Assistant ProfessorDepartment of Electronics & Communications Engineering

Page 2: Performance evaluation of different qam

Brief Overview

Compares different Quadrature Amplitude Modulation (QAM) techniques at different bit rates (8,16, 32, 64 and 256) based on the Bit Error Rate (BER) versus the Ratio of Bit Energy to Noise Power Spectral Density (Eb/No).

Comparison between the resulting transmission errors in the received signal at different noise or Eb/No levels.

Model simulates the impact of changing the power of the applied noise (AWGN) during the transmission process.

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Bit error rate, BER is applicable to radio data links as well as fiber optic data systems, Ethernet.

Any system that transmits data over a network of some form where noise, interference, and phase jitter may cause degradation of the digital signal.

AWGN is commonly used to simulate background noise of the channel under study.

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General QAM modulation/demodulation Simulink model

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Table 1: Parameter Setting for Random Integer

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Table 2: Parameter Setting for General QAM Modulator/Demodulator

is the data symbol chosen from a I × J rectangular QAM constellation.

2d is the Euclidean distance between two adjacent signal points

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• 8-QAM: (I=4*J=2) [-2.13-.71i -2.13+.71i -.71-.71i -.71+.71i 2.13-.71i

2.13+.71i .71-.71i .71+.71i]

• 16-QAM: (I=4*J=4) [-1.89-1.89i -1.89-.63i -1.89+.63i -1.89+1.89i -.63-1.89i -.63-.63i -.63+.63i

-.63+1.89i 1.89-1.89i 1.89-.63i 1.89+.63i 1.89+1.89i .63-1.89i .63-.63i .63+.63i .63+1.89i]

• 32-QAM: (I=8*J=4) [-3.08-1.32i -3.08-.44i -3.08+.44i -3.08+1.32i -2.2-1.32i -2.2-.44i -2.2+.44i

-2.2+1.32i -1.32-1.32i -1.32-.44i -1.32+.44i -1.32+1.32i -.44-1.32i -.44-.44i -.44+.44i -.44+1.32i 3.08-1.32i 3.08-.44i 3.08+.44i 3.08+1.32i 2.2-1.32i 2.2-.44i 2.2+.44i 2.2+1.32i 1.32-1.32i 1.32-.44i 1.32+.44i 1.32+1.32i .44-1.32i .44-.44i .44+.44i .44+1.32i ]

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Table 3: Parameter Setting for AWGN Channel

Table 4: Parameter Setting for Error Rate Calculation

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Table 4: Parameter Setting for Error Rate Calculation

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Table 5: To workspace Block

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The main interface of the BERTool

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Plots of the BER of the Simulated QAM techniques

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Plots of the BER of the Simulated 8-QAM at different levels of the noise power spectral density (Eb/No)

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Plots of the BER of the Simulated 8-QAM at different levels of the input signal power

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Conclusion• It demonstrates the utilization of the BERTool in

evaluating and comparing the performance of the different QAM techniques.

• Discusses the proportional relation between the power of the input signal and the noise variance implemented by the added white Gaussian noise component.

• It provides a way to simulate the performance of these communication techniques along with using the BERTool in performing the evaluation phase in this model.

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[1] Sam, W. Ho, "Adaptive modulation (QPSK, QAM), " www.intel.com/netcomms/technologies/wimax/303788.pdf, December 30, 2007.

[2] Xiaolong Li, “Simulink-based Simulation of Quadrature Amplitude Modulation (QAM) System”, Proceedings of The 2008 IAJC-IJME International Conference.

[3] “Exact BER Analysis of an Arbitrary Square/ Rectangular QAM for MRC Diversity with ICE in Non-identical Rayleigh Fading Channels” (2005 IEEE) by Laleh Najafizadeh, Chintha Tellambura.

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Thank you