Application of Quantum Computing to Accurate Positioning in 6G Indoor Scenarios

Abstract

[EN] 6G will lay its foundations on new paradigms and requirements. This new technology is expected to provide global coverage, exploring a huge spectral chunk (sub-6 GHz, mmWave, THz and optical frequency bands) to further increase data rates and connection density. In addition, 6G networks will enable a new range of smart applications with the aid of Artificial Intelligence, Big Data technologies and the emerging paradigms of Quantum Computing and Quantum Machine Learning. This paper focuses on these new paradigms and proposes an indoor location method based on the well known Euclidean Distance in its quantum version. Specifically, an example of this use case is shown, which is executed in one quantum computer from IBM Quantum Experience. The paper analyses the obtained results while exploring new challenges and fields of application of the technology. Results show that the quantum approach is accurate enough to calculate Euclidean Distance between two vectors while outperforming classical computation if the vector size is big enough.