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    Self-Organized Scheduling Request for Uplink 5G Networks: A D2D Clustering Approach

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    08491334.pdf
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    Type
    Article
    Authors
    Gharbieh, Mohammad
    Bader, Ahmed
    Elsawy, Hesham cc
    Yang, Hong-Chuan
    Alouini, Mohamed-Slim cc
    Adinoyi, Abdulkareem
    KAUST Department
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Electrical Engineering Program
    Date
    2018-10-16
    Online Publication Date
    2018-10-16
    Print Publication Date
    2019-02
    Permanent link to this record
    http://hdl.handle.net/10754/629962
    
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    Abstract
    In one of the several manifestations, the future cellular networks are required to accommodate a massive number of devices; several orders of magnitude compared to today’s networks. At the same time, the future cellular networks will have to fulfill stringent latency constraints. To that end, one problem that is posed as a potential showstopper is extreme congestion for requesting uplink scheduling over the physical random access channel (PRACH). Indeed, such congestion drags along scheduling delay problems. In this paper, the use of self-organized device-to-device (D2D) clustering is advocated for mitigating PRACH congestion. To this end, the paper proposes two D2D clustering schemes, namely; Random-Based Clustering (RBC) and Channel-Gain-Based Clustering (CGBC). Accordingly, this paper sheds light on random access within the proposed D2D clustering schemes and presents a case study based on a stochastic geometry framework. For the sake of objective evaluation, the D2D clustering is benchmarked by the conventional scheduling request procedure. Accordingly, the paper offers insights into useful scenarios that minimize the scheduling delay for each clustering scheme. Finally, the paper discusses the implementation algorithm and some potential implementation issues and remedies.
    Citation
    Gharbieh M, Bader A, El Sawy H, Yang H-C, Alouini M-S, et al. (2018) Self-Organized Scheduling Request for Uplink 5G Networks: A D2D Clustering Approach. IEEE Transactions on Communications: 1–1. Available: http://dx.doi.org/10.1109/TCOMM.2018.2876008.
    Sponsors
    The work of the KAUST team was supported in part by STC under grant RGC/3/2374-01-01
    Publisher
    Institute of Electrical and Electronics Engineers (IEEE)
    Journal
    IEEE Transactions on Communications
    DOI
    10.1109/TCOMM.2018.2876008
    arXiv
    arXiv:1810.06235
    Additional Links
    https://ieeexplore.ieee.org/document/8491334
    ae974a485f413a2113503eed53cd6c53
    10.1109/TCOMM.2018.2876008
    Scopus Count
    Collections
    Articles; Electrical Engineering Program; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

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