IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v10y2018i4p1201-d141313.html
   My bibliography  Save this article

A Self-Scrutinized Backoff Mechanism for IEEE 802.11ax in 5G Unlicensed Networks

Author

Listed:
  • Rashid Ali

    (Department of Information and Communication Engineering, Yeungnam University, Gyeongsan 38541, Korea)

  • Nurullah Shahin

    (Department of Information and Communication Engineering, Yeungnam University, Gyeongsan 38541, Korea)

  • Rojeena Bajracharya

    (Department of Information and Communication Engineering, Yeungnam University, Gyeongsan 38541, Korea)

  • Byung-Seo Kim

    (Department of Computer and Information Communication Engineering, Hongik University, Seoul 04066, Korea)

  • Sung Won Kim

    (Department of Information and Communication Engineering, Yeungnam University, Gyeongsan 38541, Korea)

Abstract

The IEEE 802.11ax high-efficiency wireless local area network (HEW) is promising as a foundation for evolving the fifth-generation (5G) radio access network on unlicensed bands (5G-U). 5G-U is a continued effort toward rich ubiquitous communication infrastructures, promising faster and reliable services for the end user. HEW is likely to provide four times higher network efficiency even in highly dense network deployments. However, the current wireless local area network (WLAN) itself faces huge challenge of efficient radio access due to its contention-based nature. WLAN uses a carrier sense multiple access with collision avoidance (CSMA/CA) procedure in medium access control (MAC) protocols, which is based on a binary exponential backoff (BEB) mechanism. Blind increase and decrease of the contention window in BEB limits the performance of WLAN to a limited number of contenders, thus affecting end-user quality of experience. In this paper, we identify future use cases of HEW proposed for 5G-U networks. We use a self-scrutinized channel observation-based scaled backoff (COSB) mechanism to handle the high-density contention challenges. Furthermore, a recursive discrete-time Markov chain model (R-DTMC) is formulated to analyze the performance efficiency of the proposed solution. The analytical and simulation results show that the proposed mechanism can improve user experience in 5G-U networks.

Suggested Citation

  • Rashid Ali & Nurullah Shahin & Rojeena Bajracharya & Byung-Seo Kim & Sung Won Kim, 2018. "A Self-Scrutinized Backoff Mechanism for IEEE 802.11ax in 5G Unlicensed Networks," Sustainability, MDPI, vol. 10(4), pages 1-15, April.
  • Handle: RePEc:gam:jsusta:v:10:y:2018:i:4:p:1201-:d:141313
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/10/4/1201/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/10/4/1201/
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Alaa Omran Almagrabi & Rashid Ali & Yasser Difulah Al-Otaibi & Hadi Mohsen Oqaibi & Tahir Khurshaid, 2021. "Sliding Group Window with Rebacking off for Collision Avoidance in High-Efficiency Wireless Networks," Mathematics, MDPI, vol. 9(19), pages 1-15, October.
    2. Waqas Khalid & Heejung Yu, 2018. "Sum Utilization of Spectrum with Spectrum Handoff and Imperfect Sensing in Interweave Multi-Channel Cognitive Radio Networks," Sustainability, MDPI, vol. 10(6), pages 1-18, May.
    3. Yousaf Bin Zikria & Sung Won Kim & Muhammad Khalil Afzal & Haoxiang Wang & Mubashir Husain Rehmani, 2018. "5G Mobile Services and Scenarios: Challenges and Solutions," Sustainability, MDPI, vol. 10(10), pages 1-9, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:10:y:2018:i:4:p:1201-:d:141313. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.