Contents I. Introduction
The Quantum Internet [1], [2] is ushering in a new paradigm of quantum processing and networking, where quantum processing techniques can be considered as an alternative to or utilized in combination with classical processing to solve different problems in systems. Such problems can include search or optimization tasks, leveraging quantum search [3]–[5] or quantum optimization [6], [7] techniques. Such processing in the quantum domain can result in faster processing times to obtain the same search result [3] or can result in higher quality and more optimal solutions [7] for equivalent execution times and perhaps even lower execution times relative to classical processing. This paper explores possibilities to utilize quantum processing techniques to enable optimization in emerging edge access networks. A range of optimization problems are considered in this paper including dynamic load balancing, proportional fair scheduling, and network-energy minimization, and these problems are presented in a quantum-inspired problem formulation. Digital twin network models are utilized to study possibilities for closed-loop optimization utilizing such techniques. One can expect that the results for such processing on a classical processor would be similar to previous classical probabilistic techniques to solve such problems. The goal of this paper is to introduce a quantum-inspired formulation for such problems. In the future, as quantum processors mature, such problems could be mapped to true-quantum processing environments, where one could expect performance and quality improvements in the overall solution over classical processing techniques for network optimization.
