Disputation: Ashish Rauniyar
Doctoral candidate Ashish Rauniyar at the Department of informatics, Faculty of Mathematics and Natural Sciences, is defending the thesis “Exploring and Enhancing Spectral and Energy Efficiency of Non-Orthogonal Multiple Access in Next-Generation IoT Networks” for the degree of Philosophiae Doctor.
The University of Oslo is closed. The PhD defence and trial lecture will therefore be fully digital and streamed directly using Zoom. The host of the session will moderate the technicalities while the chair of the defence will moderate the disputation.
Ex auditorio questions: the chair of the defence will invite the audience to ask ex auditorio questions either written or oral. This can be requested by clicking 'Participants -> Raise hand'.
“Analysis of 5G backbone as fibre replacement in rural areas”
Main research findings
- The next generation of Internet of Things (IoT) networks is expected to meet the capacity demand of billions of IoT devices. Moreover, to provide massive connectivity requirements of IoT sensors and devices and to ameliorate their capacity demands, Non-Orthogonal Multiple Access (NOMA) has been considered as a potential candidate for the 5G and future network. Another key objective of the next generation of IoT network is also to maximize the energy-efficiency. To this end, Simultaneous Wireless Information and Power Transfer (SWIPT) has been contemplated as a viable solution to self-sustainable communication in IoT networks.
In this dissertation, different from the state-of-the-art methods and architectures, we propose and investigate several spectral and energy-efficient NOMA-SWIPT architectures for future IoT networks. We also discuss user pairing issues in NOMA. We propose an adaptive user pairing scheme that shows the capacity enhancement of NOMA systems. Since NOMA is fragile to interference, an energy-efficient distributed power control in NOMA using Reinforcement Learning (RL) based Game Theoretic approach is also proposed. Finally, this dissertation proposes and investigates different models by consolidating direct links to enhance the cooperative NOMA-SWIPT systems' performance significantly. We believe that the study and results presented in this dissertation might be potentially useful to network operators, researchers, and scientists in the wireless networking community who want to assess NOMA characteristics to design next-generation IoT networks.
Contact information to Department: Mozhdeh Sheibani Harat