A performance comparison of differential frequency hopping and fast frequency hopping

Mills, D.G.; Egnor, Dianne; Edelson, Geoffrey S.

doi:10.1109/milcom.2004.1493309

Cited by 19 publications

(4 citation statements)

References 5 publications

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“…The introduction of cognitive radio can ensure the user use more frequency points so the frequency set can be adaptive optimization. On this basis, how to allocate the available frequency re-sources and reduce the multiple access interference has become the primary problem [11] [12]. Frequency is used set to partition micro-sets and make the user frequency micro-set of each time slot orthogonal to cancel certain number users' multiple access interference.…”

Section: Allocation Based On Latin Squaresmentioning

confidence: 99%

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A frequency set adaptive optimization algorithm for differential frequency hopping network based on cognitive radio and Latin squares

Cheng¹,

Wang²,

Wang³

et al. 2014

10th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM 2014)

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Differential frequency hopping (DFH) was believed to be an effective FH technique for increasing data rate of FH communication system. Cognitive radio (CR) users can use the CR technology to sense the surrounding RF envi ronment, search for available spectrum resources and ac cess spectrum dynamically. The cognitive radio technol ogy and applied mathematics are introduced in DFH. And the Latin squares based frequency set adaptive optimiza tion (LS-FSAO) algorithm is proposed. In short, the fre quency set is divided into many frequency micro-sets after the spectrum sensing, and the micro-sets are assigned to DFH users with dynamic Latin squares. The users' fre quency micro-sets are dissimilar during a same time slot to cut down the Multiple Access Interference (MAl), Par tial Band Jamming (PBJ) and Multi-Tone Jamming (MTJ). The scenario simulations of the LS-FSAO based DFH network and the traditional DFH are performed, respec tively. The results show that the LS-FSAO DFH can ob tain favorable network performance.

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Section: Allocation Based On Latin Squaresmentioning

confidence: 99%

“…r(t)=aejBs(t)+n(t)+n J (t) (11) n, (t) is partial band jamming. Ni is equivalent uni lateral power spectrum.…”

Section: Detection Symbol By Symbol Dfh Receivermentioning

confidence: 99%

A frequency set adaptive optimization algorithm for differential frequency hopping network based on cognitive radio and Latin squares

Cheng¹,

Wang²,

Wang³

et al. 2014

10th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM 2014)

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“…This design is constituted by Multiplying Unit, BPF and Local waveform generator. The constant intermediate frequency signal, which from the Local waveform generator, will mix the DFH signal with Local intermediate frequency signal [6] , and then, through BPF become into low frequency signal.…”

Section: The Design Of Shortwave Dfh Receivermentioning

confidence: 99%

The Design and Implementation of Shortwave DFH Communication Receiver Based on FPGA

Zhou

Zhao

Feng³

2012

AMM

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Shortwave DFH system is a new type of communication system, and it is widely used in various fields because of its good anti-interference and anti-fading ability performance in anti-interference and anti-fading. A shortwave DFH communication receiver is designed based on Virtex4-sx35 series FPGA development board using Verilog HDL and VHDL language, and the function of this receiver is implemented and simulated. The result of simulating shows that the designed shortwave DFH receiver is effectively.

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“…Generalized DFH waveforms have demonstrated excellent single-user performance in additive white Gaussian noise and Rayleigh fading channels, and robustness to co-channel (multiuser) interference. DFH has been favorably compared to conventional FSK, Fast Frequency Hopped MFSK (FFH/MFSK), and Direct Sequence Spread Spectrum (DSSS) [2]- [4].…”

Section: Background On Dfh Modulationmentioning

confidence: 99%

Improved multipath robustness of DFH modulation in the underwater acoustic channel

Cazzanti

Egnor

Edelson

et al. 2010

Oceans 2010 MTS/Ieee Seattle

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We characterize performance improvement of differential frequency hopping modulation under two techniques that mitigate the multipath effects of the underwater acoustic channel: blind adaptive equalization and beamforming. We report results on data collected at-sea during the RACE08, SPACE08 and WHOI09 experiments, and show that the biterror rate improves with the application of these two techniques. Future improvements may combine joint single-element, blind equalization and beamforming (multi-element) approaches to leverage their respective strengths.

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A performance comparison of differential frequency hopping and fast frequency hopping

Cited by 19 publications

References 5 publications

A frequency set adaptive optimization algorithm for differential frequency hopping network based on cognitive radio and Latin squares

A frequency set adaptive optimization algorithm for differential frequency hopping network based on cognitive radio and Latin squares

The Design and Implementation of Shortwave DFH Communication Receiver Based on FPGA

Improved multipath robustness of DFH modulation in the underwater acoustic channel

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