The Realization Of Network Optimization Intelligent Decision-making

In recent years,with the rapid development of wireless networks,competition among operators has become increasingly fierce.In addition,users have become more and more demanding on wireless networks.Wireless network optimization has become a major operator to improve network quality.One of the important tasks.The network optimization work is to collect and analyze the data in the wireless network that is currently running,to find out the factors that affect the quality of the wireless network,and to adjust the network quality by using relevant technical means and operations.Wireless network optimization includes: coverage optimization,interference troubleshooting,neighboring area planning and optimization,and PCI rational planning.Artificial wireless network optimization is a long-term,arduous,and continuous system engineering with large workload and low efficiency.The intelligent decision of network optimization is an auxiliary system for daily wireless network optimization work.It not only enables the wireless network resources to be allocated reasonably,but also makes the network operation in the best state.At the same time,the existing reasonable network optimization intelligent decision can be Future network maintenance and planning provide accurate recommendations.In this paper,the current research on network power optimization is studied.The wireless network power is analyzed and explained in detail by three intelligent optimization algorithms: ant colony algorithm,particle swarm optimization and simulated annealing algorithm.In this paper,based on the basic principles of the above three algorithms,in order to improve the network coverage rate,three optimized intelligent algorithms are used to completely configure the power of the wireless network,and the target coverage rate is calculated.Intelligent decision making for LTE wireless network power optimization.Finally,the data simulation experiments are carried out by using the above three intelligent optimization algorithms,and the three intelligent optimization algorithms are compared and analyzed vertically by coverage.This paper realizes the network optimization intelligent decision.In terms of workload,it solves the problem that a problem needs multiple network adjustments to solve,which makes the workload much less and improves the efficiency of network optimization.In terms of network adjustment accuracy,Since the intelligent algorithm is applied to make the decision of the optimization scheme,the accuracy of the power adjustment is improved,and the network coverage is better than the result of the artificial network optimization adjustment.