Combined Reed-Solomon and Convolutional codes for IWSN based on IDWPT/DWPT Architecture

Khalil, Aamre; Saadoui, Safa; Tabaa, Mohamed; Chehaitly, Mouhamad; Monteiro, Fabrice; Oukaira, Aziz; Dandache, Abbas

doi:10.1016/j.procs.2019.08.095

Cited by 4 publications

(3 citation statements)

References 12 publications

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“…Based on the effect of channel fading due to delay propagation in addition to AWGN noise for the LOS and NLOS configurations, it is clear that the multipath effect disturbs the signals of the different users and thus causes interference between them. The proposed architecture allows signal detection at reception for all users as shown in Figure 15 for a SNR (Signal to Noise Ratio) greater than 20 dB [27][28][29][30][31][32][33].…”

Section: Simulations and Resultsmentioning

confidence: 99%

“…For a fading channel with industrial noise, the signal-to-noise ratio is reduced by 8 dB for an architecture with 16 users using a convolutional code and by 5 dB for 32 users using an RS code, as shown in Figure 20. For a better illustration, Table 1 shows the different SNR values for a fixed linear bit error rate of 0.1 with or without error-correcting coding [31,32].…”

Section: Performances: Eccmentioning

confidence: 99%

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Industrial IoT Using Wavelet Transform

Tabaa¹,

Saadaoui²,

Chehaitly³

et al. 2021

Wavelet Theory

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For many years now, communication in the industrial sector has been characterized by a new trend of integrating the wireless concept through cyber-physical systems (CPS). This emergence, known as the Smart Factory, is based on the convergence of industrial trades and digital applications to create an intelligent manufacturing system. This will ensure high adaptability of production and more efficient resource input. It should be noted that data is the key element in the development of the Internet of Things ecosystem. Thanks to the IoT, the user can act in real time and in a digital way on his industrial environment, to optimize several processes such as production improvement, machine control, or optimization of supply chains in real time. The choice of the connectivity strategy is made according to several criteria and is based on the choice of the sensor. This mainly depends on location (indoor, outdoor, …), mobility, energy consumption, remote control, amount of data, sending frequency and security. In this chapter, we present an Industrial IoT architecture with two operating modes: MtO (Many-to-One) and OtM (One-to-Many). An optimal choice of the wavelet in terms of bit error rate is made to perform simulations in an industrial channel. A model of this channel is developed in order to simulate the performance of the communication architecture in an environment very close to industry. The optimization of the communication systems is ensured by error correcting codes.

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Section: Simulations and Resultsmentioning

confidence: 99%

Section: Performances: Eccmentioning

confidence: 99%

Industrial IoT Using Wavelet Transform

Tabaa¹,

Saadaoui²,

Chehaitly³

et al. 2021

Wavelet Theory

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“…Looking at the two coding techniques, one can see that they share many common or similar computational steps. Based on this interesting similarity, a coding block and a decoding block combining the two techniques are proposed that can correct these two divergent types of errors [50].…”

Section: Combination Of Reed Solomon and Convolutional Codesmentioning

confidence: 99%

Error Correcting Codes Analysis for Wireless Industrial Communication based on Wavelet Packet Architecture.

Chehaitly,

Tabaa,

Borras

et al. 2024

Preprint

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With the evolution of applications, the implementation of processing algorithms has become more difficult due to the requirements in terms of throughput and complexity, which make the existing coding/decoding architectures unsuitable due to their insufficient computing capacity. Our objective in this paper is to analyze/study the integration of error-correcting codes into a functional digital architecture based on the inverse discrete wavelet packet transform (IDWPT) in transmission, and the discrete wavelet packet transform (DWPT) in reception (known as discrete wavelet packet modulation). In our proposed architecture, we have exploited two transmission strategies: (i) one-to-many (OtM) for transmission between a single transmitter and multiple sensors, (ii) and a many-to-one (MtO) mode for transmission between multiple users and a single receiver. To improve the transmission quality with the same configuration, we have integrated corrective codes, in particular the different families of Reed Solomon and convolutional codes. This architecture offers a very high processing power and a versatility in terms of flexibility and configurability adapted to very noisy environments, especially industrial ones. The use of error-correcting codes improves the quality of the transmission compared to the state of the art. Where we have achieved a gain of 4 to 6dB for Reed Solomon coding and convolutional codes used individually, 5 to 10dB with the combination of these two codes and 2 to 4dB more for shortened Reed Solomon codes.

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