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Having a well-managed spectrum is one of the keys to high-efficiency systems of communication. This chapter discusses QCNNs as tools for solving spectrum sharing, interference management and instant frequency hopping in very congested 6G/7G networks. Resorting to quantum superposition and entanglement, QCNNs speed up the process of fitting new information by taking features from high-dimensional spaces at the same time, sacrificing hardly any delay. This chapter looks at QCNN architecture, signal mapping in real time and features an example on spectrum reuse. The chapter ends by examining the results of machine performance and the difficulties faced during its use in post-classical hardware situations.

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Quantum Convolutional Neural Networks for Intelligent Spectrum Management in 6G/7G

  • 章节

  • 发表日期：

    2026年

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  • Inam Ul Haq,
  • Anushikha Singh,
  • Nehul Jain,
  • Mushtaq Ahmad Rather,
  • Faheem Syeed Masoodi

摘要

Having a well-managed spectrum is one of the keys to high-efficiency systems of communication. This chapter discusses QCNNs as tools for solving spectrum sharing, interference management and instant frequency hopping in very congested 6G/7G networks. Resorting to quantum superposition and entanglement, QCNNs speed up the process of fitting new information by taking features from high-dimensional spaces at the same time, sacrificing hardly any delay. This chapter looks at QCNN architecture, signal mapping in real time and features an example on spectrum reuse. The chapter ends by examining the results of machine performance and the difficulties faced during its use in post-classical hardware situations.