5 papers
Reinforcement Learning-Enabled Dynamic Code Assignment for Ultra-Dense IoT Networks: A NOMA-Based Approach to Massive Device Connectivity
Sumita Majhi, Kishan Thakkar, Pinaki Mitra
Ultra-dense IoT networks require an effective non-orthogonal multiple access (NOMA) scheme, yet they experience intense interference because of fixed code assignment. We suggest a…
Enhancing NOMA Handover Performance Using Hybrid AI-Driven Modulated Deterministic Sequences
Sumita Majhi, G Vasantha Reddy, Pinaki Mitra
Non-Orthogonal Multiple Access (NOMA) is an information-theoretical approach used in 5G networks to improve spectral efficiency, but it is prone to interference during handovers. I…
A Deep-SIC Channel Estimator Scheme in NOMA Network
Sumita Majhi, Kaushal Shelke, Pinaki Mitra
In 5G and next-generation mobile ad-hoc networks, reliable handover is a key requirement, which guarantees continuity in connectivity, especially for mobile users and in high-densi…
Improving Channel Estimation Through Gold Sequences
Sumita Majhi, Kaushal Shelke, Pinaki Mitra +1
This study evaluates Non-Orthogonal Multiple Access (NOMA) systems using Gold coding and Conventional-V-BLAST (C-V-BLAST). Superimposed signals on shared subcarriers make NOMA user…
A PDD-Inspired Channel Estimation Scheme in NOMA Network
Sumita Majhi, Pinaki Mitra
In 5G networks, non-orthogonal multiple access (NOMA) provides a number of benefits by providing uneven power distribution to multiple users at once. On the other hand, effective p…