An introduction to quantum computing algorithms for the RAN
Management of the #radioaccessnetwork (#RAN) is becoming increasingly efficient – performed by #intuitive #technologies, making optimized decisions in real time under unpredictable circumstances. However, as the volume and complexity of #data processing increases, so too will the demand for increased computing power on the physical layer. To converge to a result within a limited time frame (i.e. execute machine learning algorithms or data processing at the physical layer), RAN management will soon require the #computing #power of a #quantum processor.
In a previous blog post we introduced quantum computer technology and the future need of this type of specialized hardware to execute RAN functions. We foresee several use cases for quantum computing (QC) in the radio access network (RAN) including:
- Physical layer processing of the user data plane in the RAN (quantum Fourier transform and quantum linear solver)
- Clustering for automatic anomaly detection in network design optimization (quantum K-means algorithm)
- Prediction of the quality of user experience for video streaming based on device and network level metrics (quantum support vector machine)
- Database search at the data management layer (Grover’s algorithm)
Comprising quantum gates, specific quantum computing algorithms will be required to perform the RAN user data plane and management plane functionality. As of today, not all the classical algorithms are described in the quantum world and only a few of them have a quantum counterpart. We explore a selection of quantum computing algorithms for the RAN below.
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