Interference Management and QoS Enhancement in 5G NOMA Networks

dc.contributor.authorMajhi, Sumita
dc.date.accessioned2026-07-31T10:55:40Z
dc.date.issued2025
dc.descriptionMitra, Pinaki
dc.description.abstractFifth-generation (5G) wireless networks promise ultra-high data speeds, low latency, and massive connectivity, revolutionizing mobile communications. However, accommodating diverse user demands—from low-power sensors to high-bandwidth video—within limited spectrum resources remains challenging. Non-Orthogonal Multiple Access (NOMA), particularly power-domain NOMA, enhances spectral efficiency by allowing multiple users to share the same resources, unlike traditional Orthogonal Multiple Access (OMA). As 5G networks expand, multi-objective optimization (MOO) becomes crucial to balance competing metrics like spectral efficiency (SE) and energy efficiency (EE). While prior work focused on single or dual objectives, this study addresses their limitations, including local minimization. NOMA’s power-domain approach improves SE, but challenges such as intra-cluster interference persist. Successive Interference Cancellation (SIC), a key NOMA technique, relies on perfect channel state information (CSI), which is impractical in dynamic environments. Few studies explore leveraging partially decoded data alongside CSI for improved channel estimation. This work makes four key contributions:
dc.identifier.otherROLL NO.176101013
dc.identifier.urihttps://gyan.iitg.ac.in/handle/123456789/3364
dc.language.isoen
dc.relation.ispartofseriesTH-3725
dc.rightshttps://creativecommons.org/licenses/by-nc-sa/4.0/
dc.rights.urihttps://creativecommons.org/licenses/by-nc-sa/4.0/
dc.subjectNOMA
dc.subjectChannel Estimation
dc.subjectML
dc.subjectMulti-objective optimization
dc.titleInterference Management and QoS Enhancement in 5G NOMA Networks
dc.typeThesis

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