Performance Specifications for the Roll-Off Factor and Filter Order for Filtered Multitone Modulation in the Maritime VHF Data Exchange System

In this paper, we propose a long short-term memory-based deep learning (DL) architecture for signal detection in uplink and downlink rate-splitting multiple access systems with multi-carrier modulation, over Nakagami-m fading and generalized Gaussian noise (GGN). The proposed DL detector completely eliminates the need for the use of successive interference cancellation (SIC), which suffers from disadvantages such as error propagation. In an orthogonal frequency division multiplexing setting, we show that the proposed DL detector outperforms the standard SIC receivers such as the least squares detector and the minimum mean-squared error receiver, and attains the performance of the optimal maximum likelihood detector, in terms of the symbol error rate (SER). Furthermore, we study the effects of the shaping parameter of GGN, hyperparameters of the DL network such as batch size and learning rate on the SER performance. INDEX TERMS Deep learning (DL), generalized Gaussian noise (GGN), long short-term memory (LSTM), non-orthogonal multiple access (NOMA), rate-splitting multiple access (RSMA).ANAGHA K. KOWSHIK (Graduate Student Member, IEEE) received the bachelor's degree (B.

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“…This trend is similar to the observation that a single carrier system performs better than a multi-carrier system as shown in Fig. 8 of [106].…”

Section: F Comparison With Mbdl Receiversupporting

confidence: 88%

Deep Learning-Based Signal Detection for Rate-Splitting Multiple Access Under Generalized Gaussian Noise

Kowshik

Raghavendra

Gurugopinath

et al. 2023

IEEE Open J. Veh. Technol.

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“…VHF terminals have been widely used on merchant ships, fishing boats, official ships, yachts, and lifeboats. It is the most popular communication equipment for marine vessels [32]- [34].…”

Section: State-of-the-art Maritime Communicationsmentioning

confidence: 99%

Hybrid Satellite-Terrestrial Communication Networks for the Maritime Internet of Things: Key Technologies, Opportunities, and Challenges

Wei

Feng

Chen

et al. 2021

IEEE Internet Things J.

196

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“…With (6), the average data rate (4) for a given set of antennas |C i | that constitutes the service cloud for ship i can be written as following lemma.…”

Section: Performance Analysis a Average Data Rate And Outage Prmentioning

confidence: 99%

“…For many decades, very high frequency-and high frequency-based communication systems have been integrated into maritime networks because they can cover a wide area [3]- [6]; however, they have small capacities and are unavailable for popular internet applications in maritime environments. As an alternative, satellite communications can provide such services [7]- [10], but it is not cost-effective for the ever-increasing level of human activity in the ocean.…”

Section: Introductionmentioning

confidence: 99%

Hierarchical Maritime Radio Networks for Internet of Maritime Things

2019

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Despite the potential benefits of a maritime Internet of Things, a number of issues hinder its realization, including the need for wide area coverage and cost-effectiveness. Toward these needs, a model is first presented for uplink maritime radio communications that hierarchically employ Wi-Fi and cellular links for data transmission from marine user equipments (MUEs) on a ship to a cellular base station with distributed antennas (DAs) along a coastline. Then, the performances are evaluated given in terms of average data rate and outage probability in the hierarchical maritime radio networks. When evaluating the performances, heterogeneous channel characteristics of the hierarchical networks are taken into account in which Rayleigh fading is considered for the MUE-ship links, whereas shadowed-Rician fading is considered for the ship-DA links. Moreover, the effects due to various transmission errors that can be occurred at different communication layers are reflected in determining the quality of service (QoS) requirements of a ship. With the help of authors' analysis, an antenna selection algorithm is proposed under which the minimum size of a service cloud can be found to support the QoS requirements of MUEs with a ship. The numerical evaluations demonstrate the validity of the proposed algorithm. INDEX TERMS Cellular networks, distributed antenna (DA), data minimization, Internet of maritime thing (IoMT), hierarchical networks, maritime communications, quality of service (QoS), wireless communication. YUJAE SONG (S'12-M'17) received the Ph.D. degree in electrical engineering from the Korea Advanced Institute of Science and Technology (KAIST), South Korea, in 2016. He was a Visiting Scholar in communication systems with the KTH Royal Institute of Technology, Sweden, in 2015. Since 2016, he has been a Senior Researcher with the Maritime ICT R&D Center, Korea Institute of Ocean Science and Technology. His research interests include design, analysis, and optimization of various wireless communication systems including 5G, maritime/underwater, and smart grid communications. SUNG HOON LIM (S'08-M'12) received the B.S. degree (Hons.

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Performance Specifications for the Roll-Off Factor and Filter Order for Filtered Multitone Modulation in the Maritime VHF Data Exchange System

Cited by 5 publications

References 24 publications

Deep Learning-Based Signal Detection for Rate-Splitting Multiple Access Under Generalized Gaussian Noise

Deep Learning-Based Signal Detection for Rate-Splitting Multiple Access Under Generalized Gaussian Noise

Hybrid Satellite-Terrestrial Communication Networks for the Maritime Internet of Things: Key Technologies, Opportunities, and Challenges

Hierarchical Maritime Radio Networks for Internet of Maritime Things

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