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Review
. 2025 Oct 3;25(19):6110.
doi: 10.3390/s25196110.

Adaptive Antenna for Maritime LoRaWAN: A Systematic Review on Performance, Energy Efficiency, and Environmental Resilience

Martine Lyimo  1 , Bonny Mgawe  1 , Judith Leo  1 , Mussa Dida  1 , Kisangiri Michael  1
Affiliations
Review

Adaptive Antenna for Maritime LoRaWAN: A Systematic Review on Performance, Energy Efficiency, and Environmental Resilience

Martine Lyimo et al. Sensors (Basel). .

Abstract

Long Range Wide Area Network (LoRaWAN) has become an attractive option for maritime communication because it is low-cost, long-range, and energy-efficient. Yet its performance at sea is often limited by fading, interference, and the strict energy budgets of maritime Internet of Things (IoT) devices. This review, prepared in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines, examines 23 peer-reviewed studies published between 2019 and 2025 that explore adaptive antenna solutions for LoRaWAN in marine environments. The work covered four main categories: switched-beam, phased array, reconfigurable, and Artificial Intelligence or Machine Learning (AI/ML)-enabled antennas. Results across studies show that adaptive approaches improve gain, beam agility, and signal reliability even under unstable conditions. Switched-beam antennas dominate the literature (45%), followed by phased arrays (30%), reconfigurable designs (20%), and AI/ML-enabled systems (5%). Unlike previous reviews, this study emphasizes maritime propagation, environmental resilience, and energy use. Despite encouraging results in signal-to-noise ratio (SNR), packet delivery, and coverage range, clear gaps remain in protocol-level integration, lightweight AI for constrained nodes, and large-scale trials at sea. Research on reconfigurable intelligent surfaces (RIS) in maritime environments remains limited. However, these technologies could play an important role in enhancing spectral efficiency, coverage, and the scalability of maritime IoT networks.

Keywords: IoT; LoRaWAN; SNR; adaptive antennas; beamforming; energy efficiency; maritime environment; systematic review.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
Maritime LoRaWAN architecture.
Figure 2
Figure 2
FSPL model.
Figure 3
Figure 3
Maritime two-ray propagation model.
Figure 4
Figure 4
Control and integration of adaptive antennas in LoRaWAN.
Figure 5
Figure 5
Systematic literature review flow diagram.
Figure 6
Figure 6
Number of selected research studies per year (2019–May 2025).
Figure 7
Figure 7
PAS transmit or receive [109].
Figure 8
Figure 8
LoRa protocol stack: PHY and MAC layers, adapted from [167].
Figure 9
Figure 9
Summary of the most frequently occurring technical terms in this review.
Figure 10
Figure 10
Estimated distribution of adaptive antenna types identified in this review.
Figure 11
Figure 11
Key antenna parameters in LoRaWAN.
See this image and copyright information in PMC

References

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