Wireless Broadband Signal Detection Scheme Based on Quantum Machine Learning

Wireless Broadband Signal Detection Scheme Based on Quantum Machine Learning

연구 분야: Infrastructure

학회: 2023 5th International Conference on Artificial Intelligence and Computer Applications (ICAICA)

The development of wireless communication has entered the stage of B5G/6G, with the birth of terahertz communication and other technologies, signal modulation and channel information have become more complex, so the difficulty of receiving signal detection is also increasing. At present, most researches combine the field of wireless communication with machine learning, and quantum machine learning, as an interdisciplinary subject of quantum computing and machine learning, may become a potential technology of 6G. In this paper, quantum machine learning is applied to signal detection in wireless broadband communication for the first time. Based on tensor network, a quantum-classical hybrid machine model is designed. The model is composed of parametric quantum circuits and neural networks, and is realized through the collaboration of quantum computers and classical computers. In this paper, simulation experiments are conducted on Tensorflow-Quantum platform provided by Google, and according to the bit error rate index, the proposed hybrid model is estimated to reduce the signal detection problem by about 10 percentage points compared with the pure quantum algorithm and the neural network algorithm.