Published Paper Details:

As we see communication systems transform at an incredible rate of change there is a great demand for smart, secure and scalable solutions. In steps Quantum Machine Learning (QML) which is that which we see as a very powerful new approach which puts together what quantum computing has to offer with traditional machine learning thus bringing in a new age of communication networks. This paper looks at how QML may put forward solutions to some of the main issues in the next generation of networks which include 6G and beyond in terms of improving channel estimation, enhancing error correction, and optimising resource management. Also included in the picture are what QML's features of quantum parallelism and entanglement bring to the table which in turn have the promise of QML out performing classical models in areas such as signal processing, predicting network traffic, and improving in the field of cybersecurity. Also we see a report on the present state of quantum hardware and algorithm development as they pertain to how this may play out in real world network settings. At the same time we look at present issues which include hardware limitations, quantum noise, and the issue of developing very efficient algorithms which we also put forward possible solutions to. As a whole the report puts forth that QML may in fact play a very transforming role in the future of communication technologies in which we see networks becoming smarter, faster and more secure.