Construction and Simulation Analysis of a QPSK Modulation and Demodulation Model

Guannan Yang

doi:10.54097/3z13p312

Authors

Guannan Yang

DOI:

https://doi.org/10.54097/3z13p312

Keywords:

Frequency shift keying, Bit error rate, Signal to noise ratio, visualization, QPSK.

Abstract

Phase shift keying (PSK) modulation is an important modulation method in signal processing, and it has many advantages compared with other modulation methods. QPSK transmits 2 bits per symbol which means the higher spectral efficiency. QPSK is also good trade-off between complexity and performance. In order to better understand the modulation mode of QPSK, this paper establishes a basic QPSK modulation and demodulation model. With the help of MATLAB simulation software, waveform diagram, spectrum diagram, power spectrum diagram, eye diagram and other graphics are used to visualize the changes of signals in each process of QPSK system. And the simulation results are consistent with the theory, which verifies the validity of the model and compare the advantages of QPSK modulation versus other modulation methods. QPSK modulation has wide applicability and can be applied to a variety of information transmission environments, such as cellular network, Wi-Fi, satellite communication and OFDM-based systems. QPSK is very useful for later research on more complex modulation methods.

Downloads

Download data is not yet available.

References

[1] Sun Huinan, "Simulation and study of the QPSK modulation and demodulation technique [J]", Journal of Changshu Institute of Technology, vol. 38, no. 2, pp. 70 - 78, 2024.

[2] Yuan Honglin, Yan Yan, Zhang Guoan and Bao Zhihua, "Payload symbol-based nonlinear RF fingerprint for wireless QPSK-OFDM devices[J]", China Communications, vol. 20, no. 6, pp. 240 - 248, 2023.

[3] Kokate MD., Wagh AE., Wankhede VA. QPSK Demodulator Based on Wideband Acquisition System.

[4] Ahmed M., Alam MG. A Convolution Neural Network based QPSK and 16QAM Modulations Simulator for a Multiuser MIMO-OFDM Transmission Simulation over a Nakagami-m Fading Channel. In2023 5th International Conference on Sustainable Technologies for Industry 5.0 (STI) pp. 1 - 6, 2023.

[5] Breed G. Analyzing signals using the eye diagram. High Frequency Electronics. 2005, 4 (11): 50 - 3.

[6] Hale PD., Jargon J., Wang CJ., Grossman B., Claudius M., Torres JL., Dienstfrey A., Williams DF. A statistical study of de-embedding applied to eye diagram analysis. IEEE Transactions on Instrumentation and Measurement. 2011, 61 (2): 475 - 88.

[7] Park J., Lee M., Park S., Kim J., Kim J., Kim D. Controller Area Network with Flexible Data Rate (CAN FD) Eye Diagram Prediction. IEEE Transactions on Electromagnetic Compatibility. 2024.

[8] Saeidi Z., Yazdi A., Mashhadi S., Hadian M., Gutub A. High performance image steganography integrating IWT and Hamming code within secret sharing. IET Image Processing. 2024, 18 (1): 129 - 39.

[9] Datta K., Jana B., Singh PK., Chakraborty MD. Robust data hiding scheme for highly compressed image exploiting btc with hamming code. Multimedia Tools and Applications. 2024, 83 (3): 8591 - 628.

[10] Motlagh D., Wiebe N. Generalized quantum signal processing. PRX Quantum. 2024, 5 (2): 020368.

[11] Sharoar Jahan Choyon AK., Chowdhury R. Performance comparison of free-space optical (FSO) communication link under OOK, BPSK, DPSK, QPSK and 8-PSK modulation formats in the presence of strong atmospheric turbulence. Journal of Optical Communications. 2024, 44 (s1): s763 - 9.

[12] Kavitha T., Sonika M., Prathyusha NL., Raj VT. Modelling of OFDM modulation technique in HF radio band using MATLAB. Journal of Optical Communications. 2024, 45 (4): 971 - 6.

[13] Tahraoui K., Burelle R., Vayssade T., Lefevre F., Latorre L., Azaïs F. Digital generation of RF phase-modulated test stimuli: application to BPSK modulation scheme. In2024 IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFT), pp. 1 - 6, 2024.