2023
DOI: 10.51537/chaos.1314803
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Estimating Optimal Synchronization Parameters for Coherent Chaotic Communication Systems in Noisy Conditions

Abstract: It is known, that coherent chaotic communication systems are more vulnerable to noise in the transmission channel than conventional communications. Among the methods of noise impact reduction, such as extended symbol length and various digital filtering algorithms, the optimization of the synchronization coefficient may appear as a very efficient and simple straightforward approach. However, finding the optimal coefficient for the synchronization of two chaotic oscillators is a challenging task due to the high… Show more

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Cited by 6 publications
(5 citation statements)
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“…The recovery of the message M * (t) is done by using the root mean square (RMS). In our previous work [49], we found that using RMS leads to the lowest BER values. A block diagram of the variable center point signal modulation communication system is shown in Figure 9.…”
Section: Investigation Of Chaotic Communication System With α-Based S...mentioning
confidence: 74%
See 1 more Smart Citation
“…The recovery of the message M * (t) is done by using the root mean square (RMS). In our previous work [49], we found that using RMS leads to the lowest BER values. A block diagram of the variable center point signal modulation communication system is shown in Figure 9.…”
Section: Investigation Of Chaotic Communication System With α-Based S...mentioning
confidence: 74%
“…Using the approach reported in [47,49], we have determined that variable Y is the most optimal for synchronization and has a nearly optimal synchronization coefficient of k = 4.…”
Section: Investigation Of Chaotic Communication System With α-Based S...mentioning
confidence: 99%
“…It can be seen that during the transient behavior, one can see a pretty small difference between V(V I N) and V(OUT), but after about 0.6 µs, the error is almost zero, indicating that the recovered signal is the same as the transmitted one, while the encrypted one is masked in the chaotic time series. Further research can be performed considering the secrecy analysis of the proposed communication system, as done in the recent works [37][38][39], showing resistance to various attacks.…”
Section: Chaotic Masking Using Ota-c Filtersmentioning
confidence: 99%
“…Such systems provide secure communication channels for transmitting images across IoT sensing systems to domains like smart healthcare [31,32], where security and privacy are crucial. Ongoing efforts involve developing and studying communication systems based on analog chaos oscillators [33][34][35].…”
Section: Introductionmentioning
confidence: 99%