An improved quantum artificial fish swarm algorithm for resource allocation in multi-user system

Abstract

Through in-depth research and application, it is found that with the increasing number of artificial fish, the required storage space is also increasing, which finally leads to the increasing difficulty of calculation, and the ability to obtain accurate solutions is seriously insufficient, and only satisfactory solution domains can be obtained for the system. Since the development of multi-user systems, there are still some problems in resource allocation, such as poor user fairness, low system throughput, and low system security. In view of the appeal problem, we can design a multi-user system resource allocation scheme based on quantum artificial fish swarm algorithm. Firstly, it is necessary to analyze the working principle of resource allocation in multi-user system, and establish a mathematical model according to its working principle; Furthermore, through the research and in-depth research on the artificial fish swarm algorithm, we integrate the quantum phase concept fish artificial fish swarm algorithm, introduce quantum evolutionary algorithm into the algorithm, and use quantum phase to code and improve it; Then, through simulation experiments, we compare other types of resource allocation schemes in the market, and process and analyze the experimental results; Finally, according to the experimental data, the conclusion is drawn that the improved quantum artificial fish school algorithm can accurately and quickly obtain the optimal allocation scheme, and to a certain extent, ensure user fairness, improve the communication ability of the multi-user system. Compared with other multi-user system resource allocation schemes, its overall performance is also more outstanding.