Prof. Dr. Haider Jabbar Abd, Head of the Department of Communication Engineering Technologies at the College of Engineering Technologies at Al-Mustaqbal University, published a collaborative scientific research paper entitled “Contrastive Self-Supervised Learning Enables Robust and Data-Efficient Automatic Modulation Classification” in the prestigious international journal IET Communications, indexed in Clarivate, with an impact factor of 1.6. The paper appeared in Volume 20, Issue 1, 2026. The research presented an advanced framework based on artificial intelligence and deep learning techniques to improve the accuracy of automatic modulation classification in wireless communication systems and cognitive radio, while reducing the need for large amounts of pre-labelled data. It also addressed challenges associated with noise, interference, and variations in wireless channel conditions. Experimental results demonstrated a classification accuracy of 98.10% at a signal-to-noise ratio of 15 dB. The proposed model also showed strong resilience to interference and variations in signal characteristics, supporting the development of more efficient and reliable intelligent communication systems. This scientific achievement reflects Al-Mustaqbal University’s ongoing commitment to supporting research, advancing technological innovation, and strengthening international scientific engagement. It also aligns with the United Nations Sustainable Development Goals, particularly SDG 9: Industry, Innovation and Infrastructure, and SDG 4: Quality Education. Al-Mustaqbal University, ranked first among private universities in Iraq, continues to support the research contributions of its academic staff and strengthen its presence in reputable international scientific journals, contributing to the advancement of higher education and scientific research.
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