SAFH - Smooth Adaptive Frequency Hopping

Cheikh, Sami Ben; Esemann, Tim; Hellbrück, Horst

doi:10.1109/iwcld.2011.6123078

Cited by 19 publications

(16 citation statements)

References 8 publications

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“…In this paper, "spectrum sharing methods" denote medium access control protocols or mechanisms that an RF system uses to share the same frequency band with neighboring RF systems. In other words, coexistence methods denote specific spectrum sharing techniques, e.g., power control [48]- [50] and adaptive frequency hopping [51]- [53].…”

Section: Overview Of Spectrum Sharing Methodsmentioning

confidence: 99%

“…• Adaptive Frequency Hopping: The idea of Adaptive Frequency Hopping (AFH) is that coexisting systems change their operating channel by hopping between a pre-determined set of channels to reduce congestion on specific channels (e.g., [51], [52]). Notice that AFH is a spectrum sharing method in time and frequency domains.…”

Section: A Classification Of Spectrum Sharing Methodsmentioning

confidence: 99%

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Spectrum sharing methods for the coexistence of multiple RF systems: A survey

et al. 2016

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Section: Overview Of Spectrum Sharing Methodsmentioning

confidence: 99%

Section: A Classification Of Spectrum Sharing Methodsmentioning

confidence: 99%

Spectrum sharing methods for the coexistence of multiple RF systems: A survey

et al. 2016

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“…To alleviate this problem, a number of non-collaborative schemes working regardless of any other systems have been considered [7][8][9][10][11][12]. Most of them consider the use of two fundamental processes; channel classification and adaptive control action.…”

Section: Bluetoothmentioning

confidence: 99%

“…to provide high bandwidth stability at high data rates and lower drop rates for both interfaces under interference. SAFH [7] assigns usage probabilities to all channels based on an exponential smoothing filter for frame error rates to estimate and predict the channel conditions. The application layer can adapt SAFH by parameter settings in a cross-layer approach.…”

Section: Fig 3 Afh Frequency Decision Flowchartmentioning

confidence: 99%

“…It first generate a pseudo-random hop sequence based on its master clock and address, and then maps it into a desired hopping frequency so that each packet is transmitted through a different channel. However, recent works have shown that the performance of the Bluetooth system using pseudorandom FH technique can be heavily degraded due to unavoidable co-existing interferences (e.g., interferences caused by collocated Bluetooth devices or IEEE 802.11x based wireless local area network (WLAN)) in the unlicensed band [2-6].To alleviate this problem, a number of non-collaborative schemes working regardless of any other systems have been considered [7][8][9][10][11][12]. Most of them consider the use of two fundamental processes; channel classification and adaptive control action.…”

mentioning

confidence: 99%

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Interference Avoidance Mechanisms in Bluetooth - A Comparative Study

Sughasiny¹,

Dhanapal²

2013

IJCA

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Bluetooth is a short range operating technology that helps in the exchange of data. Faster and efficient communications using a Bluetooth device is mandatory, since it has resource limitations. Service discovery delays pose a major problem when considering the Bluetooth devices. Our paper provides a comparative study that discusses efficient mechanisms to reduce these delays by providing a better service discovery process. Further, we also discuss mechanisms that help improve the power consumption. KEYWORDS BLUETOOTHBluetooth is a short range wireless system operating in 2.4 GHz industry, society and medical (ISM) unlicensed band, where a number of radio systems share the same resource. The Bluetooth rapidly hops over all the 79 channels to mitigate interferences using a pseudo-random frequency hopping (FH) technique [1]. It first generate a pseudo-random hop sequence based on its master clock and address, and then maps it into a desired hopping frequency so that each packet is transmitted through a different channel. However, recent works have shown that the performance of the Bluetooth system using pseudorandom FH technique can be heavily degraded due to unavoidable co-existing interferences (e.g., interferences caused by collocated Bluetooth devices or IEEE 802.11x based wireless local area network (WLAN)) in the unlicensed band [2-6].To alleviate this problem, a number of non-collaborative schemes working regardless of any other systems have been considered [7][8][9][10][11][12]. Most of them consider the use of two fundamental processes; channel classification and adaptive control action. Channel classification estimates channel conditions to detect the presence of any interference source nearby. Adaptive control action mitigates interference sources by exploiting the channel classification information.

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Decoding and measurement of frequency‐hopping spread spectrum signals using an adaptive algorithm‐based compressive sensing

Ghanem¹

2020

Int J Communication

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Summary Decoding of frequency‐hopping spread spectrum (FHSS) methods to intercept the symbol content in signals and brilliant measurement is presented in this paper. The switching of the frequency channels rapidly using a pseudorandom code makes interception of FHSS signals very difficult. Therefore, a proposed adaptive compressive measurement for decoding the frequency‐hopping receivers that have no prior knowledge of the hopping sequence is the main focus of this work. The proposed methods rely on the instantaneous sparsity of the spectra of FHSS signals, and the transmitted symbols can be recovered from the proposed compressive measurements. Furthermore, the contribution of this work is the design of a proposed adaptive method that is used to design measurement kernels for compressive measurement and decoding based on knowledge enhancement, which includes both prior information enhanced and adaptive methods based on the properties of the intersignals. Simulation results on Gaussian frequency‐shift keying (GFSK) FHSS signals illustrate that the proposed compressive method enhances the detection performance of the received frequencies with acceptable decoding accuracy compared with other techniques such as enhanced orthogonal matching pursuit (EOMP) and an adaptive sampling kernels method with a random compressive ratio. Also, an enhancement of the proposed algorithm is achieved due to enhancement in both the normalized mean square error (NMSE) and the probability of correction error (Pce). The comparison between these algorithms is performed using simulation based on MATLAB and receiver operating characteristic (ROC) curves.

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SAFH - Smooth Adaptive Frequency Hopping

Cited by 19 publications

References 8 publications

Spectrum sharing methods for the coexistence of multiple RF systems: A survey

Spectrum sharing methods for the coexistence of multiple RF systems: A survey

Interference Avoidance Mechanisms in Bluetooth - A Comparative Study

Decoding and measurement of frequency‐hopping spread spectrum signals using an adaptive algorithm‐based compressive sensing

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