Tongxin xuebao (Jun 2022)
Resource allocation strategies for improved mayfly algorithm in cognitive heterogeneous cellular network
Abstract
Aiming at the optimization of uplink resource allocation in cognitive heterogeneous cellular networks, a resource allocation algorithm based on improved discrete mayfly algorithm was proposed.In the cognitive heterogeneous cellular network model, the power control strategy was introduced to control the interference suppression of transmitted power, and the improved discrete mayfly algorithm was used to optimize and solve the optimal distribution scheme based on the user’s quality of service (QoS) requirements and interference threshold constraints to maximize the energy efficiency (EE).In order to improve the convergence rate and search ability of the mayfly algorithm, the dynamic adaptive weights of incomplete Gamma and Beta distribution functions and the golden sine position updating strategy were introduced.The simulation results show that the closed-loop power control based on SINR can dynamically adjust the transmitting power of users and effectively restrain the interference between users.The GSWBMA has good optimization efficiency and convergence performance to solve the resource allocation problem, effectively improve the energy efficiency of the system and the transmission rate of users, and ensure the QoS requirements of users.
