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SNR-Based TDMA Scheduling with Continuous Energy Transfer for Wireless Powered Communication Networks

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Intelligent Algorithms in Software Engineering (CSOC 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1224))

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Abstract

This paper studies SNR-based TDMA scheduling for a Wireless Powered Communication Network (WPCN). It is composed of a single Hybrid-Access Point (H-AP) which transfers energy wirelessly and collects data, and multiple terminal nodes. For H-AP operating in a half-duplex mode, it is not possible to do data collection from nodes and Wireless Energy Transfer (WET) simultaneously. Since only the first time slot is used for WET, the order of allocation of nodes to TDMA time slots does not affect the performance. On the other hand, for H-AP operating in a full-duplex mode that uses two antennas, one for continuous WET and the other for data collection, the scheduling order affects the performance and fairness. The reason is that a node allocated in a later time slot of the TDMA frame can harvest more energy than the nodes allocated in earlier time slot. Therefore, which order the node should be allocated in is an important issue. In this paper, we investigate the performance and fairness of WPCN when we change the scheduling order that is based on the SNR values of terminal nodes. The simulation results show that scheduling in descending order has maximum fairness, while scheduling in ascending order has maximum sum-throughput but less fairness. Considering the most important problem of WPCN, doubly near-far phenomenon, we conclude that the descending scheduling order can improve fairness significantly because nodes with lower SNR values harvest more energy compared to nodes with higher SNR values.

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Acknowledgement

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. NRF-2019R1A2C1009894).

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Correspondence to Inwhee Joe .

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Yoon, D., Joe, I. (2020). SNR-Based TDMA Scheduling with Continuous Energy Transfer for Wireless Powered Communication Networks. In: Silhavy, R. (eds) Intelligent Algorithms in Software Engineering. CSOC 2020. Advances in Intelligent Systems and Computing, vol 1224. Springer, Cham. https://doi.org/10.1007/978-3-030-51965-0_26

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