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首页> 外文期刊>Wireless Networks >Resource allocation of simultaneous wireless information and power transmission of multi-beam solar power satellites in space-terrestrial integrated networks for 6G wireless systems
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Resource allocation of simultaneous wireless information and power transmission of multi-beam solar power satellites in space-terrestrial integrated networks for 6G wireless systems

机译:用于6G无线系统的空间 - 地面集成网络中多光束太阳能卫星同时无线信息和电力传输的资源分配

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The technique of simultaneous wireless information and power transmission (SWIPT) has been applied to wireless sensor networks, which employ static or mobile base stations (BSs) such as drones and ships to charge passively powered devices. SWIPT can be strongly expanded by solar power satellites (SPSs), which collect solar energy and transmit it to the earth through microwaves to alleviate the power shortage problem. Furthermore, multi-beam SPSs can serve a broader range than terrestrial BSs for information transmission.In 6G networks, satellites are core devices in space-terrestrial integrated networks (STINs) supporting super Internet-of-Things. However, when discussing 6G wireless systems, previous works did not consider SWIPT applied in STINs through multi-beam SPSs. Therefore, this work proposes a novel resource allocation problem for SWIPT performed by multi-beam SPSs in the STIN while optimizing the following two objectives: minimizing deficit or excess of information transmission rate and maximizing power transmission based on two receiving architectures of terrestrial devices for information decoding and energy harvesting. Different from previous works, this problem considers not only assigning power to one of multiple satellite beams but also further allocating power in each beam into two parts for information and power transmission. This problem is NP-hard as it includes an NP-hard problem. Artificial intelligence (AI) algorithms can be used to optimize the network resource management. Hence, this problem with continuous decision variables is further solved by a classical and two recent AI algorithms specially designed for continuous variables, i.e., particle swarm optimization, improved harmony search algorithm, and monkey algorithm. Through simulation, the most appropriate AI algorithms to the concerned problem are analyzed, and the results show that for the two special designed receiving architectures of the terrestrial devices, the power splitting architecture generally outperforms the time switching architecture.
机译:同时无线信息和电力传输(SWIPT)的技术已被应用于无线传感器网络,其采用静态或移动基站(BSS),例如无缸和船舶来充电被动供电的设备。 Swik可以由太阳能卫星(SPSS)强烈扩展,该太阳能卫星(SPSS)收集太阳能并通过微波传输到地球,以减轻电力短缺问题。此外,多光束SPS可以提供​​比地面BS的更宽范围,用于信息传输。在6G网络中,卫星是空间 - 地面集成网络(STINS)中的核心设备,支持超级互联网。但是,在讨论6G无线系统时,之前的作品在通过多光束SPSS中不考虑在标度中应用于SWIPT。因此,该工作提出了一种新的资源分配问题,用于STIN中的多光束SPS执行的SWIPT,同时优化以下两个目标:最小化信息传输速率的缺陷或过量,基于用于信息的两个接收架构的两个接收架构最大化电力传输解码和能量收获。与以前的作品不同,此问题不仅考虑将电力分配给多卫星光束之一,而且还将每个光束的电力进一步分配给两个部分以供信息和电力传输。这个问题是NP - 硬质问题,因为它包括一个难题的问题。人工智能(AI)算法可用于优化网络资源管理。因此,通过专门为连续变量,即粒子群优化,改进的和声搜索算法和猴子算法而被专门设计的经典和两个最近的AI算法进行了连续判定变量的这个问题。通过仿真,分析了对有关问题的最合适的AI算法,结果表明,对于地面设备的两个特殊设计的接收架构,功率分割架构通常优于时间切换架构。

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