A Multimodal Machine Learning Framework and Cost-Effective Adaptive Receiver for Improving QPSK Bit Error Rate

Authors

  • Hasanain A. Hasan Al-Behadili College of Engineering, University of Misan.
  • Maab Alaa Hussien College of Engineering, University of Misan.
  • Nasif Jassim Hadi College of Engineering, University of Misan.

DOI:

https://doi.org/10.70917/ijcisim-2026-5779

Keywords:

QPSK, Rayleigh fading channel, adaptive signal processing, bit error rate (BER), MATLAB Simulink, wireless communication systems

Abstract

The study focuses on improving the reliability of QPSK digital communication systems in Rayleigh fading channels through adaptive intelligent signal processing. A conventional QPSK system is first modeled and analyzed in MATLAB Simulink to establish a baseline BER. To mitigate multipath fading and AWGN, the receiver is enhanced with adaptive gain control and adaptive noise suppression. Simulation results show a significant BER reduction for the adaptive system compared with the conventional one across an SNR range of 0 to 30 dB. Notably, the improvement is more pronounced at moderate to high SNR values, highlighting the robustness of the adaptive approach in realistic fading scenarios. Overall, the findings confirm that adaptive intelligent processing provides an effective, low-complexity solution for enhancing wireless communication performance.

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Published

2026-09-04

How to Cite

Hasanain A. Hasan Al-Behadili, Maab Alaa Hussien, & Nasif Jassim Hadi. (2026). A Multimodal Machine Learning Framework and Cost-Effective Adaptive Receiver for Improving QPSK Bit Error Rate. International Journal of Computer Information Systems and Industrial Management Applications, 18(22s), 1804–1815. https://doi.org/10.70917/ijcisim-2026-5779

Issue

Vol. 18 No. 22s (2026)

Section

Original Articles