Abstract: The sixth generation (6G) of wireless networks, which can meet the various demands of modern communication, heralds a transformative era marked by intelligent, self-configuring networks. This study examines how Quantum Machine Learning (QML), a keystone technology, will influence 6G network architecture in the future. Beyond the constraints of conventional methods, 6G networks can dynamically adapt to changing network states and user requirements in real-time by integrating machine learning (ML), quantum computing (QC), and QML. We perform an extensive review of ML, QC, and QML advancements, highlighting their potential applications and challenges in the context of 6G networks, by leveraging insights from 5G and Beyond 5G (B5G) technologies. In addition, we present a novel framework for 6G communication networks that addresses important issues in air interface design, network infrastructure, edge computing, and user optimization. It incorporates both QC-assisted and QML-based approaches. The transformative potential of quantum and QML-assisted technologies in reshaping wireless communication systems is highlighted in this paper.
Keywords: 6G Communication Networks, Quantum Computing, Machine Learning, Beyond 5G, Parallel processing, Quantum communication, Cutting-Edge Networking, Revolutionary Network Paradigms, Isolated artificial intelligence.
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DOI:
10.17148/IJARCCE.2024.131236
