Maximum likelihood approaches for noncoherent communications with chaotic carriers

Kisel, A.; Dedieu, H.; Schimming, T.

doi:10.1109/81.922456

Cited by 37 publications

(51 citation statements)

References 17 publications

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“…Hence the only remaining option is to examine the second alternative. Some estimation techniques for orbits and initial conditions based on maximizing likelihood functions Kisel et al, 2001) have been proposed recently, yielding results better than those presented in this section. The rest of the chapter is devoted to these techniques.…”

Section: Systemmentioning

confidence: 61%

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Applying Estimation Techniques to Chaos-Based Digital Communications

Eisencraft¹,

Baccalá²

2011

Chaotic Systems

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Section: Systemmentioning

confidence: 61%

“…as in (Kisel et al, 2001). Note, however, the central role played by the choice of the partition in obtaining this result as recently pointed out by .…”

Section: Modified Viterbi Algorithmmentioning

confidence: 76%

Applying Estimation Techniques to Chaos-Based Digital Communications

Eisencraft¹,

Baccalá²

2011

Chaotic Systems

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“…Our proposed system can achieve the same AWGN performance as that of the DCSK system, so it has better AWGN performance than those noncoherent CSK systems, such as those in [11], [13], [15].…”

Section: B Comparison With Existing Noncoherent Csk Systemsmentioning

confidence: 99%

“…The AWGN performance of other noncoherent CSK systems proposed in [11], [13], [15], which do not possess any adaptive algorithm like those in [21], are all inferior to that of the DCSK system. Our proposed system can achieve the same AWGN performance as that of the DCSK system, so it has better AWGN performance than those noncoherent CSK systems, such as those in [11], [13], [15].…”

Section: B Comparison With Existing Noncoherent Csk Systemsmentioning

confidence: 99%

“…Despite being inferior to coherent schemes in terms of bit-error performance, noncoherent schemes still inherit the advantages of carrying information using chaotic signals and being simple. A number of modulation schemes have been proposed, e.g., the maximum likelihood scheme [11], the tracker-based scheme [12], [13], the extended Kalman filter (EKF) scheme with channel equalization [14], the return-map-based scheme [15], the generalized maximum likelihood scheme for the detection of frequency modulated differential chaos shift keying (FM-DCSK) signals [10], optimal [16], [17] and suboptimal [18] noncoherent detection method for CSK, and so on. In this paper, we consider a general weighted noncoherent CSK communication system and evaluate its performance in additive white Gaussian noise (AWGN) and multipath channel environments.…”

Section: Introductionmentioning

confidence: 99%

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A General Noncoherent Chaos-Shift-Keying Communication System and its Performance Analysis

Chen

Feng

Tse

2007

2007 IEEE International Symposium on Circuits and Systems (ISCAS)

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Abstract-A general noncoherent chaos-shift-keying (CSK) communication system with adjustable weights is proposed in this paper. The performance of the system under additive white Gaussian noise (AWGN) and multipath channel conditions are evaluated. Analytical expressions of the bit error rates are derived. The performance of the system is compared with that of the DCSK system and existing noncoherent CSK systems. The results show that the general CSK system can achieve the same performance as that of the DCSK system. A detailed analysis is presented to show that the DCSK system is the optimal form of such noncoherent systems.

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Reconstruction of chaotic signals with application to channel equalization in chaos‐based communication systems

Feng

Tse

Lau

2004

Int J Communication

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SUMMARYA number of schemes have been proposed for communication using chaos over the past years. Regardless of the exact modulation method used, the transmitted signal must go through a physical channel which undesirably introduces distortion to the signal and adds noise to it. The problem is particularly serious when coherent-based demodulation is used because the necessary process of chaos synchronization is difficult to implement in practice. This paper addresses the channel distortion problem and proposes a technique for channel equalization in chaos-based communication systems. The proposed equalization is realized by a modified recurrent neural network (RNN) incorporating a specific training (equalizing) algorithm. Computer simulations are used to demonstrate the performance of the proposed equalizer in chaos-based communication systems. The H! e enon map and Chua's circuit are used to generate chaotic signals. It is shown that the proposed RNN-based equalizer outperforms conventional equalizers as well as those based on feedforward neural networks for noisy, distorted linear and non-linear channels.

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Maximum likelihood approaches for noncoherent communications with chaotic carriers

Cited by 37 publications

References 17 publications

Applying Estimation Techniques to Chaos-Based Digital Communications

Applying Estimation Techniques to Chaos-Based Digital Communications

A General Noncoherent Chaos-Shift-Keying Communication System and its Performance Analysis

Reconstruction of chaotic signals with application to channel equalization in chaos‐based communication systems

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