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首页> 外文期刊>International journal of communication systems >Energy-efficient resource allocation model for device-todevice communication in 5G wireless personal area networks
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Energy-efficient resource allocation model for device-todevice communication in 5G wireless personal area networks

机译:Energy-efficient resource allocation model for device-todevice communication in 5G wireless personal area networks

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摘要

In general, there are several many devices that can overload the network andreduce performance. Devices can minimize interference and optimize bandwidthusage by using directional antennas and by avoiding overlapping communicationranges. In addition, devices need to carefully manage their use ofresources, such as bandwidth and energy. Bandwidth is limited in wireless personalarea networks (WPANs), so devices need to carefully select which datato send and receive. In this paper, an intelligent performance analysis ofenergy-efficient resource optimization model has been proposed for device-todevice(D2D) communication in fifth-generation (5G) WPAN. The proposedenergy-efficient resource allocation in D2D communication is importantbecause it helps reduce energy consumption and extend the lifespan of devicesthat are communicating with each other. By allocating resources in an efficientmanner, communication between two devices can be optimized for maximumefficiency. This helps reduce the amount of energy needed to power the communication,as well as the amount of energy needed to power the device thatis communicating with another device. Additionally, efficient resource allocationhelps reduce the overall cost of communication, as the use of fewerresources results in a lower overall cost. The proposed efficient resource allocationhelps reduce the environmental impact of communication, as less energyis used for communication. The proposed energy-efficient resource allocationmodel (EERAM) has reached 92.97% of energy allocation, 88.72% of powerallocation, 87.79% of bandwidth allocation, 87.93% of spectrum allocation,88.43% of channel allocation, 25.47% of end-to-end delay, 94.33% of networkdata speed, and 90.99% of network throughput.

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