Metric learning is a popular approach for measuring the similarity between samples and is essential for many machine learning tasks. However, its performance may be degraded when the data is corrupted by noise, the fe...
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To adapt to the smooth evolution from 5G to 6G and realize the accurate management of 5G core network elements, this paper proposes a resource management system integrating collection, maintenance, and management. Bas...
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ISBN:
(数字)9798350331387
ISBN:
(纸本)9798350331394
To adapt to the smooth evolution from 5G to 6G and realize the accurate management of 5G core network elements, this paper proposes a resource management system integrating collection, maintenance, and management. Based on 5GC network elements information, several feasible neural network models are constructed to realize real-time classification of 5G virtual elements in the live network. Through our experiments, the paper proves the selected algorithm to be reasonable, convenient and efficient.
The engineering parameters of communication base stations are the core assets of telecommunication operators. It directly determines the quality of the network and the perception of users. The current communication ne...
The engineering parameters of communication base stations are the core assets of telecommunication operators. It directly determines the quality of the network and the perception of users. The current communication network has accumulated a large amount of wireless network big data, and adjusting base station engineering parameters based on user business data is an important scientific issue. This article proposes a technical solution for engineering parameter planning based on simulation iteration and artificial intelligence algorithms. This scheme is based on high-precision simulation, so it can predict the optimization effect in advance. This scheme adopts particle swarm optimization algorithm for intelligent optimization, achieving the goal of effectively improving the optimization effect. At the same time, we combine existing wireless big data to achieve precise engineering parameter planning based on the distribution of user business volume. Therefore, it can achieve the effect of stimulating traffic and maximizing investment return ratio. Furthermore, it is possible to achieve self intelligent network operation and maintenance. Application practice has shown that adopting this technical solution can reduce base station resource investment by 10 % and improve network quality by 19.9%, which is of great significance for actual network operation and maintenance.
In the age of information explosion, the number of network packets generated every day is monotonically increasing. In order to analyze valuable data and improve the storage performance of traffic acquisition systems,...
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ISBN:
(纸本)9781665464222
In the age of information explosion, the number of network packets generated every day is monotonically increasing. In order to analyze valuable data and improve the storage performance of traffic acquisition systems, a high-performance data processing system architecture is needed. In this paper, we propose designing a high-speed data acquisition system based on data characteristics and comparing the features and capabilities of standard memory management methods. In addition, we propose a length-adaptive memory management framework based on a hot-cold domain structure. We conclude that this system architecture is experimentally proven to have reasonable practicality and usability.
Cellular traffic prediction is an important problem in the field of communication management. In this paper, a cellular traffic prediction method CTSTN based on spatio-temporal learning is designed combining Transform...
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ISBN:
(数字)9798350356328
ISBN:
(纸本)9798350356335
Cellular traffic prediction is an important problem in the field of communication management. In this paper, a cellular traffic prediction method CTSTN based on spatio-temporal learning is designed combining Transformer and Conditional Variational Auto-Encoder (CVAE). This paper explores the application of CVAE in the spatial states modeling and generating of cellular traffic data, constructs a spatial states dataset from the raw dataset, and designs an S-CVAE module to learn spatial characteristics of traffic data. Meanwhile, the Transformer is used to model temporal features of cellular traffic data. We conduct experiments and analyses on CTSTN and its sub-modules on real datasets. The results show the effectiveness of applying CVAE to spatial status prediction and validate the accuracy of CTSTN predictions.
Faced with the rapid growth of network traffic in the development of wireless network. To guarantee a better user experience in wireless network, the accurate and timely estimation of traffic is becoming more importan...
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Simultaneous transmitting and reflecting (STAR) reconfigurable intelligent surface (RIS) technique has recently received considerable attention due to its omni-directional radiation capability. In this paper, motivate...
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