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Hybrid Approach for Improving Slotted ALOHA Based on Capture Effect and ZigZag Decoding Techniques

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Proceedings of the International Conference on Artificial Intelligence and Computer Vision (AICV2021) (AICV 2021)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1377))

Abstract

In wireless environments, simultaneous data transmissions over the same wireless channel lead to the collision problems, which may cause data loss. As a result, the performance of the random access (RA) mechanisms like the Slotted ALOHA is degraded dramatically. Lately, both Capture Effect (CE) and ZigZag Decoding (ZD) techniques have contributed to a huge improvement in Slotted ALOHA performance. These two techniques are based on retrieve packets from collisions. In this paper, we further enhance the Slotted ALOHA performance by combining the useful features of both CE and the ZD techniques. An analysis of the system based on a Markov chain model is presented, allowing us to derive the mathematical expressions of the performance metrics. The numerical results show that the proposed approach substantially improves system performance in terms of throughput and delay compared to other mechanisms reported in the literature.

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Author information

Authors and Affiliations

  1. Faculty of Sciences and Techniques, Computer, Networks, Mobility and Modeling Laboratory: IR2M, Hassan First University of Settat, 26000, Settat, Morocco

    Abdessamad Bellouch, Ahmed Boujnoui & Abdelkrim Haqiq

  2. F.S.J.E.S. Ait Melloul, Complex System and Interactions Research Team, Ibn Zohr University, Agadir, Morocco

    Abdellah Zaaloul

  3. Machine Intelligence Research Labs (MIR Labs), Auburn, WA, USA

    Abdelkrim Haqiq

Authors
  1. Abdessamad Bellouch
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  2. Ahmed Boujnoui
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  3. Abdellah Zaaloul
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  4. Abdelkrim Haqiq
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Corresponding author

Correspondence to Abdessamad Bellouch .

Editor information

Editors and Affiliations

  1. Information Technology Department, Faculty of Computers and Artificial Intelligence, Cairo University, Giza, Egypt

    Aboul Ella Hassanien

  2. Faculty of Sciences and Techniques, Hassan 1st University, Settat, Morocco

    Abdelkrim Haqiq

  3. School of Medicine, University of Missouri, Columbia, MO, USA

    Peter J. Tonellato

  4. ISAE-ENSMA, Futuroscope Chasseneuil Cedex, France

    Ladjel Bellatreche

  5. British University Vietnam, Hung Yen, Vietnam

    Sam Goundar

  6. Faculty of Computers and Artificial Intelligence, Benha University, Benha, Egypt

    Ahmad Taher Azar

  7. NEST Research Group, ENSEM, Hassan II University of Casablanca, Casablanca, Morocco

    Essaid Sabir

  8. High National School for Computer Science and Systems Analysis (ENSIAS), Mohammed V University, Rabat, Morocco

    Driss Bouzidi

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Bellouch, A., Boujnoui, A., Zaaloul, A., Haqiq, A. (2021). Hybrid Approach for Improving Slotted ALOHA Based on Capture Effect and ZigZag Decoding Techniques. In: Hassanien, A.E., et al. Proceedings of the International Conference on Artificial Intelligence and Computer Vision (AICV2021). AICV 2021. Advances in Intelligent Systems and Computing, vol 1377. Springer, Cham. https://doi.org/10.1007/978-3-030-76346-6_20

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