Evidence map›Paper›PMID 42102155›Full record

ArticlePloS one2026

Outage performance of UAV-NOMA networks over rician faded channel with hardware impairments, channel estimation error, and SIC imperfection.

Sk Thaherbasha, S D Nageena Parveen, Sivasubramanyam Medasani, Suman Turpati, Tathababu Addepalli, Manish Sharma, Sameena Pathan

Abstract read
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Sk ThaherbashaDepartment of Electronics and Communication Engineering, SR University, Warangal, Telangana, India.
S D Nageena ParveenDepartment of Electronics and Communication Engineering, SR University, Warangal, Telangana, India.
Sivasubramanyam MedasaniDepartment of CSE, K. S. School of Engineering and Management, Bengaluru, India.
Suman TurpatiDepartment of Electronics and Communication Engineering, Dr. K V Subba Reddy Institute of Technology, Kurnool, Andhra Pradesh, India.
Tathababu AddepalliDepartment of ECE, Aditya University, Surampalem, India.
Manish SharmaDepartment of Electrical, Electronics and Communication Engineering, Galgotias University, Greater Noida, Uttar Pradesh, India.
Sameena PathanManipal Institute of Technology, Manipal Academy of Higher Education, Manipal, India.ORCID https://orcid.org/0000-0002-9867-4382

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The escalating demand for enhanced coverage and high data rates in wireless networks is driving the adoption of advanced technologies like unmanned aerial vehicles (UAVs). Integrating UAVs with non-orthogonal multiple access (NOMA) has emerged as a promising solution to boost spectral efficiency and user connectivity. However, the practical performance of these UAV-assisted NOMA systems is critically constrained by real-world imperfections, including hardware impairments, inaccurate channel state information (CSI), and non-ideal successive interference cancellation (SIC). To address this, a reliable system design necessitates a precise outage probability analysis, which quantifies the impact of these impairments on both reliability and user experience. This work derives closed-form expressions for the outage probability of a multi-user UAV-assisted NOMA system operating over Rician fading channels, explicitly incorporating the effects of the aforementioned impairments. Analytical results are obtained for a two-user UAV-assisted NOMA system by considering the detrimental effect of hardware impairments along with imperfect CSI and SIC on system performance. These analytical results are further validated by simulated results.

Indexed as

Computer Communication NetworksUnmanned Aerial DevicesWireless TechnologyAlgorithmsModels, Theoretical

Identifiers

PMID42102155
PMCPMC13155593

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.