Selection of CDMA and OFDM using machine learning in underwater wireless networks

Kim, Yongcheol; Lee, Hojun; Ahn, Jongmin; Chung, Jaehak

doi:10.1016/j.icte.2019.09.002

Cited by 18 publications

(9 citation statements)

References 4 publications

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“…The proposed method utilizes the sequence with a large autocorrelation to solve the orthogonality problem for the zero-slop-like whistles and the short-time unit problem for the high data rate. The sequence with the large autocorrelation performance is widely used in digital communications to detect the exact time-frequency location when multiple signals exist at the same time [ 21 , 22 , 23 , 24 , 25 ]. If the different good and long sequences are multiplied to the multiple whistles, the time location of each whistle is precisely detected when the multiplied sequence at the receiver is the same as that used in the transmitted whistle.…”

Section: Proposed Methodsmentioning

confidence: 99%

“…If the sequence is the vector whose size is

, the sequence (

) is represented as

, where

denotes the

-th element of the sequence with a value of 1 or −1, and

is the length of the sequence, i.e., cardinality. The ideal

satisfies the following property [ 21 , 22 , 23 , 24 , 25 ]:

where

denotes the autocorrelation value of the sequence and

denotes a time-lag. Equation (7) is only satisfied when the sequence length (

) is infinite.…”

Section: Proposed Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Biomimicking Covert Communication by Time-Frequency Shift Modulation for Increasing Mimicking and BER Performances

Ahn

Lee

Kim

et al. 2021

Sensors

Self Cite

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Underwater acoustic (UWA) biomimicking communications have been developed for covert communications. For the UWA covert communications, it is difficult to achieve the bit error rate (BER) and the degree of mimic (DoM) performances at the same time. This paper proposes a biomimicking covert communication method to increase both BER and DoM (degree of mimic) performances based on the Time Frequency Shift Keying (TFSK). To increase DoM and BER performances, the orthogonality requirements of the time- and frequency-shifting units of the TFSK are theoretically derived, and the whistles are multiplied by the sequence with a large correlation. Two-step DoM assessments are also developed for the long-term whistle signals. Computer simulations and practical lake and ocean experiments demonstrate that the proposed method increases the DoM by 35% and attains a zero BER at −6 dB of Signal to Noise Ratio (SNR).

show abstract

Section: Proposed Methodsmentioning

confidence: 99%

“…If the sequence is the vector whose size is

, the sequence (

) is represented as

, where

denotes the

-th element of the sequence with a value of 1 or −1, and

is the length of the sequence, i.e., cardinality. The ideal

satisfies the following property [ 21 , 22 , 23 , 24 , 25 ]:

where

denotes the autocorrelation value of the sequence and

denotes a time-lag. Equation (7) is only satisfied when the sequence length (

) is infinite.…”

Section: Proposed Methodsmentioning

confidence: 99%

Biomimicking Covert Communication by Time-Frequency Shift Modulation for Increasing Mimicking and BER Performances

Ahn

Lee

Kim

et al. 2021

Sensors

Self Cite

View full text Add to dashboard Cite

show abstract

“…The underwater environment is complex, yet reliability and a high data rate are required for reliable communications. OFDM-ML can improve the BER performance in UWA compared to the existing optimization method [15].…”

Section: For Channel Estimationmentioning

confidence: 99%

Future OFDM-based Communication Systems Towards 6G and Beyond: Machine Learning Approaches

Juwono

Reine²

2021

Green Intell. Syst. Appl.

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The vision towards 6G and beyond communication systems demands higher rate transmission, massive amount of data processing, and low latency communication. Orthogonal Frequency Division Modulation (OFDM) has been adopted in the current 5G networks and has become one of the potential candidates for the future communication systems. Although OFDM offers many benefits including high spectrum efficiency and high robustness against the multipath fading channels, it has major challenges such as frequency offset and high Peak to Power Ratio (PAPR). In 5G communication network, there is a significant increase in the number of sensors and other low-power devices where users or devices may create large amount of connection and dynamic data processing. In order to deal with the increasingly complex communication network, Machine Learning (ML) has been increasingly utilised to create intelligent and more efficient communication network. This paper discusses challenges and the impacts of embedding ML in OFDM-based communication systems.

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“…The generated internal interference is the most important factor in characterizing system capacity; moreover, the CDMA systems are used as building blocks for more complicated systems. Refer to Shen and Xu [21] , Kim et al [22] , Ogbodo et al [23] for more details about CDMA.…”

Section: Figurementioning

confidence: 99%

Evaluating the CDMA System Using Hidden Markov and Semi Hidden Markov Models

Kordnoori

Mostafaei

Kordnoori

et al. 2021

JTS

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CDMA is an important and basic part of today's communications technologies. This technology can be analyzed efficiently by reducing the time, computation burden, and cost by characterizing the physical layer with a Markov Model. Waveform level simulation is generally used for simulating different parts of a digital communication system. In this paper, we introduce two different mathematical methods to model digital communication channels. Hidden Markov and Semi Hidden Markov models' applications have been investigated for evaluating the DS-CDMA link performance with different parameters. Hidden Markov Models have been a powerful mathematical tool that can be applied as models of discrete-time series in many fields successfully. A semi-hidden Markov model as a stochastic process is a modification of hidden Markov models with states that are no longer unobservable and less hidden. A principal characteristic of this mathematical model is statistical inertia, which admits the generation, and analysis of observation symbol contains frequent runs.

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Selection of CDMA and OFDM using machine learning in underwater wireless networks

Cited by 18 publications

References 4 publications

Biomimicking Covert Communication by Time-Frequency Shift Modulation for Increasing Mimicking and BER Performances

Biomimicking Covert Communication by Time-Frequency Shift Modulation for Increasing Mimicking and BER Performances

Future OFDM-based Communication Systems Towards 6G and Beyond: Machine Learning Approaches

Evaluating the CDMA System Using Hidden Markov and Semi Hidden Markov Models

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