Design of wireless resource management scheme for network slicing
TL;DR
A dual layer optimization for heterogeneous network user access and energy consumption perception is constructed, while the lower layer uses continuous optimization to handle resource and power allocation, and integrates NSGA-III multi-objective algorithm to achieve Pareto optimization of QoS and energy consumption.
Abstract
This article constructs a dual layer optimization for heterogeneous network user access and energy consumption perception. The upper layer uses mixed integer programming to solve user access decisions, while the lower layer uses continuous optimization to handle resource and power allocation, and integrates NSGA-III multi-objective algorithm to achieve Pareto optimization of QoS and energy consumption. The core innovation of this model includes a heterogeneous resource pool management mechanism, where macro-base stations are configured with 100 resource blocks with a power range of 10-40dBm, and three micro-base stations are each configured with 50 resource blocks and a power range of 10-30dBm, as well as decision-making strategies for energy consumption perception. It integrates a comprehensive energy consumption model of static power consumption, dynamic power consumption, and cooling power consumption. Design robust stochastic differential evolution algorithms at the algorithmic level to handle channel uncertainty and ensure multi-objective convergence mechanisms. The optimization results show that among the optimal access strategies of 70 users, 45% of users choose macro-base station services, 55% of users choose nearby micro-base station services, and the total QoS of the system is 6534.28.