Energy-Efficient Data Transmission in a Three-Hop Cooperative Cellular NB-IoT Network Using Double Auction Srinivasa Rao Patri and L. Nithyanandan Abstract A narrowband IoT (NB-IoT) device’s battery life is vibrant for the future evolution of networks being wireless. The efficiency of energy for cooperative cellular NB-IoT networks is explored in this paper. In this context, the three-hop assignment problem is proposed; the theory of a double auction is used for its construction. The three-hop assignment aims to increase the battery life of a cell edge narrowband IoT users (CENUs) along with concentrating on energy-efficiency enhancement. In the proposed model, to get maximum battery life, the transmis- sion power of NB-IoT user (NU) is taken into consideration and is decreased to the possible lowest magnitude. Also, to increase the battery life of CENU, an energy- efficient narrowband IoT user–maximum weight matching method (EENU–MWM) is recommended. Lastly, EENU–MWM performance is assessed in terms of capacity, EE, transmission time, which demonstrates that EENU–MWM can significantly enhance the efficiency of the cooperative NB-IoT cellular network. Keywords NB-IoT · Cooperative communication · Double auction · Three-hop 1 Introduction As of late, the world has seen a great deal of IoT based items in the market, for example, smart healthcare, smart agriculture, smart home, smart grid, etc. [1, 2]. These applications aid people in various aspects of their life. Narrowband Internet of Things (NB-IoT) unconfined by Third-Generation Partnership Project (3GPP), an important branch of IoT, is the emerging and sustainable 5G radio access technology that has the ability to support large number of devices with low power characteristics: S. R. Patri (B ) VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad, India e-mail: srinivasarao.patri@gmail.com L. Nithyanandan Pondicherry Engineering College, Pudhucherry, India e-mail: nithi@pec.edu © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 C. Kiran Mai et al. (eds.), Proceedings of International Conference on Advances in Computer Engineering and Communication Systems, Learning and Analytics in Intelligent Systems 20, https://doi.org/10.1007/978-981-15-9293-5_22 251