Unconstrained Quantum Genetic Algorithm for Massive MIMO System

Abstract

There are plenty of real-world applications that require finding extreme value in an unsorted database. This database can be enormously large, such that there is no available quantum computer or classical supercomputer that can execute the search process. We proposed a new unconstrained quantum genetic algorithm (QGA) in order to increase the probability of finding the global solution and escaping from local minima. This algorithm exploits the features provided by blind quantum computation (BQC), which holds the promise to handle this computation issue by delegating computation to quantum remote devices. Massive multiple-input multiple-output (MIMO) systems are used as a toy example for demonstrating the effectiveness of the developed quantum genetic method.