Rate-range for an FH-FSK acoustic modem

Parrish, Nathan; Roy, Sumit; Fox, Warren L. J.; Arabshahi, P.

doi:10.1145/1287812.1287832

Cited by 7 publications

(5 citation statements)

References 8 publications

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“…The allocation of frequencies in FH-FSK which is taken from [6] is very similar to the representation in [2]. In the M FH hops one of two possible frequencies f m FH ,0 or f m FH ,1 is transmitted, where 0 ≤ m FH ≤ M FH − 1.…”

Section: Fh-fsk a Fh-fsk Frequency Designmentioning

confidence: 99%

“…In underwater acoustic communication, FH-FSK [1], [2] is often used as a modulation scheme, due to its simplicity of transmitter and receiver implementation, as well as its robustness to multipath propagation in the rough underwater acoustic channel. A disadvantage of FH-FSK is the low bandwidth efficiency, since the hops are only reused after the so-called channel clearing time and two frequencies are allocated per hop.…”

Section: Introductionmentioning

confidence: 99%

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Convolutionally Coded Hopping Pattern for MFSK Modulation in Underwater Acoustic Communication

Wolff

Badri-Hoeher

2019

IEEE Access

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A convolutionally coded M -ary frequency shift keying (MFSK) modulation scheme for underwater acoustic communication is introduced. It uses a rate 1/ log 2 M inner convolutional code, whose coded symbols are used as transmission symbols. An interleaver in the frequency domain is applied to improve the average channel clearing time. It thereby achieves almost the same data rate as a comparable uncoded frequency hopped frequency shift keying (FH-FSK) modulation scheme, but obtains the error correcting properties of the convolutional code. Bit and packet error rates are evaluated on the additive white Gaussian noise (AWGN) channel and the so-called Watermark channel model, which is a benchmark for underwater acoustic modulation schemes based on sea trial measurements. The JANUS standard which uses convolutionally coded FH-FSK is used for comparison. On the AWGN channel, the proposed scheme achieves a gain of 4 dB with respect to the required E b /N 0 for a given packet error rate (PER) compared with JANUS. In the Watermark scenarios, the best proposed-scheme achieves a PER < 10 −3 at more than 10 dB lower E b /N 0 than the JANUS implementation.INDEX TERMS Underwater acoustics, underwater communication, frequency shift keying, convolutional codes.

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Section: Fh-fsk a Fh-fsk Frequency Designmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Convolutionally Coded Hopping Pattern for MFSK Modulation in Underwater Acoustic Communication

Wolff

Badri-Hoeher

2019

IEEE Access

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“…A spreading factor ≈ 1.5 is often considered to be a suitable choice [13] in empirical channel models without multipath propagation modeling. However, with multipath propagation every arrival can be assumed to underlie spherical spreading loss ( = 2) individually.…”

Section: B Spreading Lossmentioning

confidence: 99%

Acoustic Underwater Channel and Network Simulator

Wolff

Szczepanski

Badri-Hoeher

2012

2012 Oceans - Yeosu

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Today research interests in underwater (UW) communication and navigation technologies are steadily growing. However, the design of robust UW communication and navigation systems demands a deep knowledge of the transmission medium. Acoustic UW (AUW) communication is widely used due to the good propagation characteristics of sound waves in water compared to electromagnetic waves that are highly attenuated. Besides its advantage -the low attenuation compared to electromagnetic waves -AUW communication suffers from multipath propagation, severe Doppler spread due to the low propagation speed of sound, and shadow zones, to name some of the most challenging effects. Evaluation of new communication devices under realistic conditions in sea trials is expensive and time-consuming. Therefore, a simulator modeling the AUW communication channel accurately is a valuable tool for development and evaluation of AUW communication devices. In this paper an Acoustic Underwater Channel and Network Simulator is proposed that uses ray tracing to model the AUW channel. It uses channel impulse responses (CIRs) generated by theBELLHOP ray tracing model to simulate multipath propagation. These CIRs for static constellations of receiver and transmitter are post-processed to be in agreement with the mobility of transmitters and receivers. Thereby, Doppler spread is introduced into the channel model. An empirical noise model is used to superimpose received signals with noise. Different modulation schemes can be evaluated using this AUW channel model in laboratory before expensive sea trials are conducted. In this paper a frequency hopping and an OFDM implementation are realized besides the channel model. Multiple mobile transmitters and receivers can be considered to simulate UW networks.

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“…Modifying the transmitter power appears to be a good control of error rates in the channel but the trade-off with the energy consumption will be an issue. Changing frequency bands in response to changing channel conditions can also improve performance as was shown for FSK working at longer ranges by Parrish [30] but a tradeoff with complexity of hardware and software in the acoustic transducer will need to be considered. There are minor changes in range for error free transmission with increases in depth but temperature changes can change the error free range by up to 25 m. It is clear to see at the bit level the range dependency on frequency, wind, and the various absorption coefficient parameters for short range underwater acoustic communication systems.…”

Section: B Rate-rangementioning

confidence: 99%

Investigation of a short-range underwater acoustic communication channel for MAC protocol design

Burrowes

Khan

2010

2010 4th International Conference on Signal Processing and Communication Systems

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Mobile swarms of autonomous underwater vehicles (AUV) have exciting potential for extending current AUV applications and adding new possibilities to the working environment of the oceans. For swarm operations to occur, fast reliable communication between all vehicles within the swarm is needed. The challenge for underwater communication is the very different and unique characteristics of the channel compared to the terrestrial environment. Acoustic communication has been the typical physical layer technology used for underwater operations and has experienced significant research and progress over the last few decades, however this focus has been predominately on longer range acoustic channels. The work presented in this paper is to determine the critical parameters of an underwater acoustic communication channel for the evaluation and development of a new MAC Protocol designed for short range communication between vehicles operating within a swarm. This paper provides a review of the essential channel characteristics and the modelling currently in use for this purpose, highlighting the difference for short range operations. It then assesses the electro-acoustic interface with investigation into the parametric relationship between digital modulation requirements and short range channel characteristics.

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Rate-range for an FH-FSK acoustic modem

Cited by 7 publications

References 8 publications

Convolutionally Coded Hopping Pattern for MFSK Modulation in Underwater Acoustic Communication

Convolutionally Coded Hopping Pattern for MFSK Modulation in Underwater Acoustic Communication

Acoustic Underwater Channel and Network Simulator

Investigation of a short-range underwater acoustic communication channel for MAC protocol design

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