Single Carrier Frequency Domain Detectors for Internet of Underwater Things Article Swipe
YOU?
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· 2022
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2203.12599
This paper proposes low complexity detection for internet of underwater things (IoUT)s communication. The signal is transmitted from the source to the destination using several sensors. To simplify the computational operations at the transmitter and the sensory nodes, a single carrier frequency domain equalizer (SC-FDE) is proposed and amplify-and-forward (AF) protocols are employed. Fast Fourier transform (FFT) and use of cyclic prefix (CP) are also proposed to simplify these algorithms when compared to time-domain equalization. As precise channel data is difficult to capture in underwater communications, the adaptive implementation of FDE is proposed as a solution that can be employed when the channel experiences a fast doppler shift. The two adaptive detectors are based on the least mean-square (LMS) and recursive least square (RLS) principles. Numerical simulations show that the performance of the bit error rate (BER) performance of the proposed detectors is close to that of the ideal minimum mean square error (MMSE).
Related Topics
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2203.12599
- https://arxiv.org/pdf/2203.12599
- OA Status
- green
- Cited By
- 1
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4221162233
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4221162233Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.48550/arxiv.2203.12599Digital Object Identifier
- Title
-
Single Carrier Frequency Domain Detectors for Internet of Underwater ThingsWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-03-18Full publication date if available
- Authors
-
Amer Aljanabi, Osama Alluhaibi, Qasim Zeeshan Ahmed, Fahd Ahmed Khan, Waqas-Bin-Abbas, Pavlos I. LazaridisList of authors in order
- Landing page
-
https://arxiv.org/abs/2203.12599Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2203.12599Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2203.12599Direct OA link when available
- Concepts
-
Computer science, Cyclic prefix, Fast Fourier transform, Minimum mean square error, Frequency domain, Channel (broadcasting), Underwater acoustic communication, Detector, Algorithm, Bit error rate, Adaptive equalizer, Transmitter, Equalization (audio), Electronic engineering, Orthogonal frequency-division multiplexing, Real-time computing, Underwater, Telecommunications, Mathematics, Statistics, Engineering, Estimator, Computer vision, Geology, OceanographyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
-
2024: 1Per-year citation counts (last 5 years)
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.to | 20, 66, 72, 81, 144 |
| abstract_inverted_index.FDE | 90 |
| abstract_inverted_index.The | 13, 108 |
| abstract_inverted_index.and | 34, 47, 57, 119 |
| abstract_inverted_index.are | 51, 63, 112 |
| abstract_inverted_index.bit | 133 |
| abstract_inverted_index.can | 97 |
| abstract_inverted_index.for | 6 |
| abstract_inverted_index.low | 3 |
| abstract_inverted_index.the | 18, 21, 28, 32, 35, 86, 101, 115, 129, 132, 139, 147 |
| abstract_inverted_index.two | 109 |
| abstract_inverted_index.use | 58 |
| abstract_inverted_index.(AF) | 49 |
| abstract_inverted_index.(CP) | 62 |
| abstract_inverted_index.Fast | 53 |
| abstract_inverted_index.This | 0 |
| abstract_inverted_index.also | 64 |
| abstract_inverted_index.data | 78 |
| abstract_inverted_index.fast | 105 |
| abstract_inverted_index.from | 17 |
| abstract_inverted_index.mean | 150 |
| abstract_inverted_index.rate | 135 |
| abstract_inverted_index.show | 127 |
| abstract_inverted_index.that | 96, 128, 145 |
| abstract_inverted_index.when | 70, 100 |
| abstract_inverted_index.(BER) | 136 |
| abstract_inverted_index.(FFT) | 56 |
| abstract_inverted_index.(LMS) | 118 |
| abstract_inverted_index.(RLS) | 123 |
| abstract_inverted_index.based | 113 |
| abstract_inverted_index.close | 143 |
| abstract_inverted_index.error | 134, 152 |
| abstract_inverted_index.ideal | 148 |
| abstract_inverted_index.least | 116, 121 |
| abstract_inverted_index.paper | 1 |
| abstract_inverted_index.these | 68 |
| abstract_inverted_index.using | 23 |
| abstract_inverted_index.cyclic | 60 |
| abstract_inverted_index.domain | 42 |
| abstract_inverted_index.nodes, | 37 |
| abstract_inverted_index.prefix | 61 |
| abstract_inverted_index.shift. | 107 |
| abstract_inverted_index.signal | 14 |
| abstract_inverted_index.single | 39 |
| abstract_inverted_index.source | 19 |
| abstract_inverted_index.square | 122, 151 |
| abstract_inverted_index.things | 10 |
| abstract_inverted_index.(IoUT)s | 11 |
| abstract_inverted_index.(MMSE). | 153 |
| abstract_inverted_index.Fourier | 54 |
| abstract_inverted_index.capture | 82 |
| abstract_inverted_index.carrier | 40 |
| abstract_inverted_index.channel | 77, 102 |
| abstract_inverted_index.doppler | 106 |
| abstract_inverted_index.minimum | 149 |
| abstract_inverted_index.precise | 76 |
| abstract_inverted_index.sensory | 36 |
| abstract_inverted_index.several | 24 |
| abstract_inverted_index.(SC-FDE) | 44 |
| abstract_inverted_index.adaptive | 87, 110 |
| abstract_inverted_index.compared | 71 |
| abstract_inverted_index.employed | 99 |
| abstract_inverted_index.internet | 7 |
| abstract_inverted_index.proposed | 46, 65, 92, 140 |
| abstract_inverted_index.proposes | 2 |
| abstract_inverted_index.sensors. | 25 |
| abstract_inverted_index.simplify | 27, 67 |
| abstract_inverted_index.solution | 95 |
| abstract_inverted_index.Numerical | 125 |
| abstract_inverted_index.detection | 5 |
| abstract_inverted_index.detectors | 111, 141 |
| abstract_inverted_index.difficult | 80 |
| abstract_inverted_index.employed. | 52 |
| abstract_inverted_index.equalizer | 43 |
| abstract_inverted_index.frequency | 41 |
| abstract_inverted_index.protocols | 50 |
| abstract_inverted_index.recursive | 120 |
| abstract_inverted_index.transform | 55 |
| abstract_inverted_index.algorithms | 69 |
| abstract_inverted_index.complexity | 4 |
| abstract_inverted_index.operations | 30 |
| abstract_inverted_index.underwater | 9, 84 |
| abstract_inverted_index.destination | 22 |
| abstract_inverted_index.experiences | 103 |
| abstract_inverted_index.mean-square | 117 |
| abstract_inverted_index.performance | 130, 137 |
| abstract_inverted_index.principles. | 124 |
| abstract_inverted_index.simulations | 126 |
| abstract_inverted_index.time-domain | 73 |
| abstract_inverted_index.transmitted | 16 |
| abstract_inverted_index.transmitter | 33 |
| abstract_inverted_index.computational | 29 |
| abstract_inverted_index.equalization. | 74 |
| abstract_inverted_index.communication. | 12 |
| abstract_inverted_index.implementation | 88 |
| abstract_inverted_index.communications, | 85 |
| abstract_inverted_index.amplify-and-forward | 48 |
| cited_by_percentile_year.max | 94 |
| cited_by_percentile_year.min | 90 |
| countries_distinct_count | 0 |
| institutions_distinct_count | 6 |
| citation_normalized_percentile.value | 0.42832738 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |