Performance analysis for IRS-assisted MEC networks with unit selection

The development of information technology has changed the mode of communication of social information, and this change has put forward new requirements on the contents, methods and even objects of information science research. Knowledge service in the information service process can extract knowledge and information content from various explicit and implicit knowledge resources according to people’s needs, build knowledge networks, and provide knowledge content or solutions for users’ problems. Hence, it is very important to investigate how to analyze and design the advanced standard knowledge service system based on deep learning. To this end, we firstly introduce the typical deep learning networks of convolutional neural network (CNN) for the knowledge service system, and then employ the CNN to implement the knowledge classification based on deep learning. Finally, some simulation results on the knowledge service system are presented to validate the proposed studies in this paper.

Section: System Model Of Deep Learning For Standard Knowledge Service...mentioning

confidence: 99%

Analysis and Design of Standard Knowledge Service System based on Deep Learning

Zhou

Lin

et al. 2022

“…The downlink MIMO NOMA communication system was studied in [23][24][25] to obtain an upper bound of the active wireless transmission latency of the system. Moreover, consistent latency and reliability among receivers by optimizing transmission power allocation can be obtained among multiple users.…”

Section: The Study Of the Latency Of Active Wireless Transmissionmentioning

confidence: 99%

An Overview on Active Transmission Techniques for Wireless Scalable Networks

Tang

Lai

Zhang

et al. 2022

Self Cite

Currently, massive data communication and computing pose a severe challenge on existing wireless network architecture, from various aspects such as data rate, latency, energy consumption and pricing. Hence, it is of vital importance to investigate active wireless transmission for wireless networks. To this end, we first overview the data rate of wireless active transmission. We then overview the latency of wireless active transmission, which is particularly important for the applications of monitoring services. We further overview the spectral efficiency of the active transmission, which is particularly important for the battery-limited Internet of Things (IoT) networks. After these overviews, we give several critical challenges on the active transmission, and we finally present feasible solutions to meet these challenges. The work in this paper can serve as an important reference to the wireless networks and IoT networks.

“…Specifically, we assume that the n * -th KG node KG n * is selected to communicate with the user. Intuitively, we can select the best KG node KG n * by maximizing the instantaneous channel gain, given by [12][13][14][15] n * = arg max 1≤n≤N…”

Section: Multiple Kg Nodesmentioning

confidence: 99%

“…As to multiple KG nodes in the power system, we will also give the definition of the system outage probability and derive the associated closed-form expression of the outage probability under this network. In particular, the outage probability is that the system transmission rate is less than the stated threshold R th , which can be denoted by [24,25]…”

Section: Multiple Kg Nodesmentioning

confidence: 99%

Analysis and Design of Power System Transformer Standard Based on Knowledge Graph

Zhou

Lin

et al. 2022

The transformer can convert one kind of electric energy such as AC current and AC voltage into another kind of electric energy with the same frequency. Knowledge graph (KG) can describe various entities and concepts in the real world and their relationships, and it can be considered as a semantic network for power system transformer. Hence, it is of vital importance to analyze and design the power system transformer standard based on the knowledge graph. To this end, we firstly examine the power system transformer with one KG node and one eavesdropper E, where the eavesdropper E can overhear the network from the source, which may cause physical-layer secure issue and an outage probability event. To deal with the issue, we analyze and design the system secure performance under the eavesdropper and define the outage probability for system security, by providing analytical expression of outage probability. We further investigate the power system transformer with multiple KG nodes which can help strengthen the system security and reliability. For such a system, we analyze and design the system secure performance under the eavesdropper and define the outage probability for system security, by providing analytical expression of outage probability. Finally, we give some simulations to analyze the impact of secure transformer standard on the power system, and verify the accuracy of our proposed analytical expression for the the power system transformer standard based on the knowledge graph.