Evidence map›Paper›PMID 40359209›Full record

ArticlePloS one2025

Enhanced hybrid pre-coding and power allocation algorithms for smart irrigation systems using OFDM-based WSNs.

Emad S Hassan

Abstract read
In one paragraph

Article in PloS one, 2025. 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
–field-weighted citation impact
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

1 author.

Emad S HassanDepartment of Electrical and Electronics Engineering, College of Engineering and Computer Science, Jazan University, Jizan, Saudi Arabia.ORCID 0000-0002-1840-4244

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Power allocation combined with pre-coding techniques is still an emerging field, with many challenges yet to be resolved. This paper contributes to filling this gap by proposing and evaluating hybrid algorithms that integrate pre-coding with low-complexity power allocation techniques for Orthogonal Frequency Division Multiplexing (OFDM)-based Wireless Sensor Networks (WSN) in smart irrigation systems. The use of linear pre-coding provides an efficient and simple solution to mitigate channel fading. By exploiting the channel's frequency selectivity, the power allocation algorithms adjust the modulation type and power distribution for each sub-carrier dynamically. As a result, the proposed hybrid algorithms surpass static schemes, offering notable improvements in system performance. These algorithms adjust both the signal constellation size and power distribution based on the Signal-to-Noise Ratio (SNR) values observed across the sub-carriers. Additionally, practical considerations like Rate Maximization (RM) are incorporated to provide flexibility for various application needs. Extensive simulations validate the effectiveness of the proposed algorithms in minimizing power consumption and boosting performance in OFDM-based WSNs for smart irrigation. Numerically, the proposed algorithms can reduce the required SNR by up to 18 dB for a target throughput of 400 bits/symbol and outperforming conventional algorithms in terms of throughput, energy efficiency, and network lifetime, with the pre-coded Greedy power allocation (pre-GPA) algorithm delivering up to 98.5% throughput and the longest system lifespan.

Indexed as

Agricultural IrrigationAlgorithmsComputer Communication NetworksWireless TechnologySignal-To-Noise Ratio

Identifiers

PMID40359209
PMCPMC12074503

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.