In order to better improve the quality of English teaching, this paper studies the sharing method of English digital teaching resources combined with modern digital technology. Through the collection and management of English digital teaching resources, it constructs the evaluation index system of teaching resources, so as to comprehensively and objectively evaluate the digital teaching resources and promote the construction and development of digital teaching resource and to effectively promote and improve the teaching effect, and realise the research requirements of effective sharing of massive teaching resources in complex environment.

A Method of Digital English Teaching Resource Sharing Based on Artificial Intelligence

Fifth generation (5G) and beyond fifth generation (B5G) networks are expected to provide more energy efficiency, spectral efficiency, and very high data rate with minimum latency to an ultradense environment. To meet the requirements of 5G and B5G standards, the network infrastructure can be network‐centric approach where the network is modified with respect to new radio signals and waveforms. The other approach is device centric where the existing network infrastructure can be efficiently utilized. Device‐to‐Device (D2D) communication is a key technique in device centric approach that supports 5G and B5G networks. We propose a Sequential Best Throughput Seek Algorithm (SBTSA), to compute the interference threshold for each Cellular User Equipment (CUE), and optimum resource blocks (RBs) are assigned to D2D pairs which provide best throughput to D2D pairs without affecting the Quality of Service (QoS) of the CUEs. The transmit power is optimized using genetic algorithm (GA) to effectively handle the interference between cellular users and D2D pairs. Proposed algorithm is compared with existing methods, and best results are obtained in terms of system throughput, battery utilization and energy efficiency.

Energy optimized resource and power allocation in an uplink‐based underlay device‐to‐device communication for 5G network

In order to promote the rapid transmission of music distance education resources, so that students can obtain more shared data information in unit time. This paper proposes a resource sharing method for music distance education based on the big data platform. According to the connection form of the big data platform architecture, determine the function capability of the virtualization sharing technology. Then, by calculating the shared weight of educational resources, the farthest transmission distance of music distance education resources in the network environment is constrained. Complete the relevant application technology analysis based on the big data platform. On this basis, construct the IaaS resource sharing structure. Combined with the established OpenStack scheduling policy, the statistical numerical indicators of shared access are calculated. To realize the smooth application of the music distance education resource sharing method based on the big data platform. The experimental results show that under the action of this new sharing method, the total value of shared data information obtained by students in unit time increases significantly. The method can promote the rapid transmission of music distance education resources, and meet the needs of practical applications. 

Music Distance Education Resource Sharing Method Based on Big Data Platform

Device-to-device (D2D) communications underlaid massive multiple-input multiple-output (MIMO) systems have been recognized as a promising candidate technology to achieve the challenging fifth-generation (5G) network requirements. This integration enhances network throughput, improves spectral efficiency, and offloads the traffic load of base stations. However, the co/cross-tier interferences between cellular and D2D communications caused by resource sharing is a significant challenge, especially when dense D2D users exist in an underlay mode. In this paper, we jointly optimize the channel assignment and power allocation to maximize the sum data rate while maintaining the interference constraints of cellular links. Due to the lack of network-wide information in large scale networks, resource management and interference coordination is hard to be implemented in a centralized way. Therefore, we propose a three-stage stable and distributed resource allocation and interference management scheme based on local information and requires little coordination and communication between devices. We model the channel allocation optimization problem in the first stage as a many-to-one matching game. In the second stage, the algorithm adopts a cost charging policy to solve each user’s power control problem as a non-cooperative game. In the third stage, the algorithm search for swap blocking pairs until stable matching exist. It is shown in this paper that the proposed algorithm converges to a stable matching and terminates after finite iterations. Simulation results show that the proposed algorithm can achieve more than 86% of the average transmission rate performance of the optimal matching with lower complexity.

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Distributed Joint Channel Assignment and Power Control for Sum Rate Maximization of D2D-Enabled Massive MIMO System

Due to the long response time of the traditional financial management education resource sharing system, a financial management education resource sharing system based on data mining is designed. Firstly, the hardware configuration structure and function of the financial management education resource sharing system are optimized to improve the hardware performance of the system. Then, the massive financial management education resources are effectively stored and classified, and the targeted real-time extraction and sharing of teaching information are carried out. Finally, the experiment proves that the response time of the educational resource sharing system of financial management specialty based on data mining is short, and it has high practicability in the process of practical application. 

Design of Educational Resource Sharing System for Financial Management Specialty Based on Data Mining

With the implementation of device-to-device (D2D) communication in primary cellular networks, there will be notable benefits such as increase in cellular capacity, energy efficiency and spectral efficiency. The interference to the cellular user equipment (CUE), due to D2D pairs is reduced with proper strategies on resource allocation and transmit power assignment to the D2D pairs. This leads to healthier sum rate and battery life of D2D pairs. In this paper, we propose a distance-based interference reduction and power management scheme to reduce the interference on CUEs and evolved NodeB (eNB) and thus improve the sum rate of D2D pairs. The power allocation is based on the D2D pairs distance to the CUEs and eNB, which is estimated based on Haversine formula. The transmit power of D2D transmitter is effectively manipulated with respect to the transmit power of CUEs. The system sum rate, total transmit power of D2D pairs and the battery life of D2D user equipment are analyzed and validated through simulation.

Nandakumar Sendrayan

Papers

Uplink Resource Sharing and Power Management Scheme for an Underlay D2D Communication