Quantum Intelligence in Beyond 5G Networks: Current Progress, and Open Avenues

Abstract

The emergence of fifth-generation (5G) wireless technologies leads to enlarging network complexity as a result of massive data generation, exhaustive operating costs, time, energy, and the burdens of planning and management. Artificial intelligence (AI) has been demonstrated to have a vital role in improving data analytics and decision-making in massive 5G networks. On the other hand, Quantum Computing is an evolving technology for handling exponential expansion in the data dimensions and calculating linear algebra quicker and more proficiently than traditional computers implying reduced computational costs and energy consumption. The unification between these disciplines engenders the concept of “Quantum Intelligence", which is an innovative and quite promising field with the possibility of unbounded capabilities for the 5G network. Beyond centralized learning, our discussions extend to debate the potentials of quantum intelligence to improve the distributed (federated) learning scenarios over several quantum computers, aiming to drastically enhance computational efficiency and energy consumption. Multiple simulation experiments are performed to evaluate and compare the performance of quantum intelligence on classical and quantum datasets. Finally, this article outlines the major technical and research challenges and open problems for future research on quantum intelligence in 5G wireless networks.