Performance analysis of FFH-FDMA satellite communication system using partial processing Dehop-Rehop Transponder (DRT) under jamming

Kim, Junghwan; Kim, Suil; Orra, Mike; Raorane, Pooja

doi:10.1109/milcom.2009.5380028

Cited by 3 publications

(2 citation statements)

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“…Another study pertaining to DSSS versus FHSS efficacy with onboard processing satellite suggests FHSS to be a better choice for SATCOM antijamming applications when the interference is narrow band with high PSD 10 . In another study, the performance of partial OBP dehop‐rehop transponder (DRT) under partial band and multitone jamming is discussed 11 . In the said article, it was suggested that, as frequency division multiplexing (FDM)‐based FHSS is prone to traveling‐wave tube (TWT) amplifier's nonlinearity, a noncoherent multiple frequency shift keying (MFSK) modulation scheme with time diversity and convolutional encoding is considered more effective for countering the partial band and multitone jamming against satellites with DRT technology.…”

Section: Introductionmentioning

confidence: 99%

“…10 In another study, the performance of partial OBP dehop-rehop transponder (DRT) under partial band and multitone jamming is discussed. 11 In the said article, it was suggested that, as frequency division multiplexing (FDM)-based FHSS is prone to traveling-wave tube (TWT) amplifier's nonlinearity, a noncoherent multiple frequency shift keying (MFSK) modulation scheme with time diversity and convolutional encoding is considered more effective for countering the partial band and multitone jamming against satellites with DRT technology. A blind source separation-based technique has also been employed to mitigate repeater jamming targeting downlink SATCOM signals.…”

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confidence: 99%

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A smart reactive jamming approach to counter reinforcement learning‐based antijamming strategies in GEO SATCOM scenario

Arif

Hashmi

Khan

et al. 2021

Satell Commun Network

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Summary Reinforcement learning (RL) is being considered for future SATCOM systems due to its inherent capability to self‐learn the optimum decision‐making policy under different scenarios. This capability enables SATCOM systems to manage their resources judiciously and mitigate jamming attacks autonomously without prior jammer type classification. We propose a novel smart reactive SATCOM jamming approach that would not only counter these RL based anti‐jamming strategies but would also be effective against conventional anti‐jamming schemes, that is, FHSS and DSSS. The proposed jamming approach exploits the limitations in learning patterns of Q‐learning‐based RL agent and achieves effective jamming while conserving considerable amount of jamming power. To achieve this, we propose an intelligent jamming engine (IJE) along with few potent jamming algorithms and evaluate their performance in terms of throughput degradation of victim SATCOM link, jamming power conservation, and design complexity of the jammer. Software simulations successfully demonstrate the effectiveness of our proposed smart reactive jamming approach which outperforms the standard reactive jammer against RL‐based antijamming schemes.

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Section: Introductionmentioning

confidence: 99%

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confidence: 99%