A method for maximizing throughput of energy collecting type wireless relay network based on deep multi-network learning

A wireless relay network and multi-network technology, applied in the field of energy-collecting wireless relay network, can solve the problems of huge energy consumption and greenhouse gas emissions, and achieve the effects of increasing profits, increasing transmission rates, and increasing user reputation

Active Publication Date: 2018-12-11
ZHEJIANG UNIV OF TECH
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[0003] However, the energy consumption generated by densely deploying relay base stati

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  • A method for maximizing throughput of energy collecting type wireless relay network based on deep multi-network learning
  • A method for maximizing throughput of energy collecting type wireless relay network based on deep multi-network learning
  • A method for maximizing throughput of energy collecting type wireless relay network based on deep multi-network learning

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Embodiment Construction

[0048] The present invention will be further described in detail below in conjunction with the accompanying drawings.

[0049] Refer to figure 1 , An energy-intensive wireless relay network throughput maximization method based on deep multi-network learning, in other words, through joint power allocation and time scheduling to achieve end-to-end maximum throughput to maximize system benefits. The present invention is based on an energy-collecting wireless relay network system (such as figure 1 Shown). In the energy-intensive wireless relay network system, the power allocation and time scheduling are optimized through deep multi-network learning to reach the maximum transmission rate. The invention proposes a renewable energy optimization method for maximizing throughput under the condition of limited data buffering and energy storage battery, aiming at the time scheduling and power control problems in the energy-collecting wireless relay network, the method includes the follo...

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Abstract

A method for maximizing the throughput of an energy collecting type relay network based on deep multi-network learning comprises the following steps: 1) maximizing the throughput in the centralized wireless relay network through regenerative energy optimization management, wherein, the optimization problem is described as a multivariable optimization problem; 2) decomposing the problem P1 into twoparts of optimization: power sub-optimization and time slot sub-optimization, i. e., optimizing variables pi and taui by deep multi-network learning to obtain the optimal ri. A method for maximizingsystem efficiency with maximum throughput in a centralized radio relay network by combining time scheduling and power allocation is provided.

Description

Technical field [0001] The invention relates to the technical field of energy-intensive wireless relay networks, in particular to a method for maximizing the throughput of energy-intensive wireless relay networks based on deep multi-network learning. Background technique [0002] Due to the proliferation of wireless devices and emerging multimedia services, mobile data traffic has been increasing exponentially. Due to channel losses such as path loss, shadows and small-scale fading, more and more indoor and edge users may experience poor service performance. To overcome this obstacle, relay-assisted access technology has been proposed as a valuable solution to develop energy efficiency and spatial diversity to improve the quality of service for indoor and cell edge users. The relay base station will serve as a relay station for communication between edge users and macro cell base stations. [0003] However, the energy consumption of densely deploying relay base stations and the a...

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Application Information

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IPC IPC(8): H04W52/26H04W52/46H04W72/04G06N3/08G06N3/04
CPCH04W52/267H04W52/46H04W72/0446H04W72/0473G06N3/08G06N3/045Y04S10/50Y02E40/70Y02D10/00
Inventor 钱丽萍冯安琪冯旭黄玉蘋黄亮吴远
Owner ZHEJIANG UNIV OF TECH
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