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.
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The authors thank the anonymous referees for comments that improved the content as well as the presentation of this paper. This work has been supported in part by Ministry of Science and Technology, Taiwan, under Grants MOST 106-2221-E-009-101-MY3 and MOST 108-2628-E-009-008-MY3.
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Lin, C., Su, N., Deng, D. et al. Resource allocation of simultaneous wireless information and power transmission of multi-beam solar power satellites in space–terrestrial integrated networks for 6G wireless systems. Wireless Netw 26, 4095–4107 (2020). https://doi.org/10.1007/s11276-020-02314-2
- Multi-beam satellite
- Solar power satellite
- Simultaneous wireless information and power transmission
- Space-terrestrial integrated network
- AI algorithm