Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/4031
Title: A Survey of Non-Orthogonal Multiple Access for Internet of Things and Future Wireless Networks
Authors: Panda, Bibekananda
Senanayake, Dhayan Dhananjaya
Gunathilake, S Athukoralalage Manuli Thisara
Singh, Poonam
Keywords: NOMA
IoT
Massive MIMO
mm-Wave communication
Issue Date: 22-Jun-2023
Publisher: IEEE
Citation: 2nd International Conference on Machine Learning Deep learning and Computational Intelligence (MDCWC2023), Tiruchirappalli, Tamil Nadu, India, 22 June 2023
Abstract: Non-orthogonal multiple access (NOMA) is an effective multiple access technique for future generations of wireless networks. It has large spectral efficiency, enabling high connectivity, which is essential for Internet of Things (IoT) applications. IoT applications initiate an industrial and user revolution era with massive connected devices. The paper discusses various NOMA schemes for IoT applications and their implementation for massive IoT networks. It also describes the current limitations of NOMA for IoT, including security, successive interference cancellation (SIC), power allocation, and channel estimation. Various deep learning applications along with a comprehensive study of several promising technologies for massive wireless connectivity, millimeter-wave (mm-Wave), massive multiple-input multiple-output (mMIMO), and unmanned aerial vehicles (UAV) communication are also illustrated based on NOMA-IoT applications.
Description: Copyright belongs to proceedings publisher
URI: http://hdl.handle.net/2080/4031
Appears in Collections:Conference Papers

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