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Adaptive MCS selection and resource planning for energy-efficient communication in LTE-M based IoT sensing platform

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  • Nhu-Ngoc Dao
  • Minho Park
  • Joongheon Kim
  • Sungrae Cho

Abstract

As an important part of IoTization trends, wireless sensing technologies have been involved in many fields of human life. In cellular network evolution, the long term evolution advanced (LTE-A) networks including machine-type communication (MTC) features (named LTE-M) provide a promising infrastructure for a proliferation of Internet of things (IoT) sensing platform. However, LTE-M may not be optimally exploited for directly supporting such low-data-rate devices in terms of energy efficiency since it depends on core technologies of LTE that are originally designed for high-data-rate services. Focusing on this circumstance, we propose a novel adaptive modulation and coding selection (AMCS) algorithm to address the energy consumption problem in the LTE-M based IoT-sensing platform. The proposed algorithm determines the optimal pair of MCS and the number of primary resource blocks (#PRBs), at which the transport block size is sufficient to packetize the sensing data within the minimum transmit power. In addition, a quantity-oriented resource planning (QORP) technique that utilizes these optimal MCS levels as main criteria for spectrum allocation has been proposed for better adapting to the sensing node requirements. The simulation results reveal that the proposed approach significantly reduces the energy consumption of IoT sensing nodes and #PRBs up to 23.09% and 25.98%, respectively.

Suggested Citation

  • Nhu-Ngoc Dao & Minho Park & Joongheon Kim & Sungrae Cho, 2017. "Adaptive MCS selection and resource planning for energy-efficient communication in LTE-M based IoT sensing platform," PLOS ONE, Public Library of Science, vol. 12(8), pages 1-20, August.
    • Handle: RePEc:plo:pone00:0182527
    DOI: 10.1371/journal.pone.0182527
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    Cited by:

    1. Dao, Nhu-Ngoc & Vu, Duc-Nghia & Masood, Arooj & Na, Woongsoo & Cho, Sungrae, 2020. "Reliable broadcasting for safety services in dense infrastructureless peer-aware communications," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    2. Hai Chien Pham & Nhu-Ngoc Dao & Jung-Ui Kim & Sungrae Cho & Chan-Sik Park, 2018. "Energy-Efficient Learning System Using Web-Based Panoramic Virtual Photoreality for Interactive Construction Safety Education," Sustainability, MDPI, vol. 10(7), pages 1-17, July.

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