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    A cooperative online learning scheme for resource allocation in 5G systems

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    5GlearningICC.pdf
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    Type
    Conference Paper
    Authors
    Alqerm, Ismail cc
    Shihada, Basem cc
    KAUST Department
    Computer Science Program
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Date
    2016-07-26
    Online Publication Date
    2016-07-26
    Print Publication Date
    2016-05
    Permanent link to this record
    http://hdl.handle.net/10754/621298
    
    Metadata
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    Abstract
    The demand on mobile Internet related services has increased the need for higher bandwidth in cellular networks. The 5G technology is envisioned as a solution to satisfy this demand as it provides high data rates and scalable bandwidth. The multi-tier heterogeneous structure of 5G with dense base station deployment, relays, and device-to-device (D2D) communications intends to serve users with different QoS requirements. However, the multi-tier structure causes severe interference among the multi-tier users which further complicates the resource allocation problem. In this paper, we propose a cooperative scheme to tackle the interference problem, including both cross-tier interference that affects macro users from other tiers and co-tier interference, which is among users belong to the same tier. The scheme employs an online learning algorithm for efficient spectrum allocation with power and modulation adaptation capability. Our evaluation results show that our online scheme outperforms others and achieves significant improvements in throughput, spectral efficiency, fairness, and outage ratio. © 2016 IEEE.
    Citation
    AlQerm I, Shihada B (2016) A cooperative online learning scheme for resource allocation in 5G systems. 2016 IEEE International Conference on Communications (ICC). Available: http://dx.doi.org/10.1109/ICC.2016.7511617.
    Publisher
    Institute of Electrical and Electronics Engineers (IEEE)
    Journal
    2016 IEEE International Conference on Communications (ICC)
    Conference/Event name
    2016 IEEE International Conference on Communications, ICC 2016
    DOI
    10.1109/ICC.2016.7511617
    Additional Links
    http://www.shihada.com/node/publications/5GlearningICC.pdf
    http://ieeexplore.ieee.org/document/7511617/
    ae974a485f413a2113503eed53cd6c53
    10.1109/ICC.2016.7511617
    Scopus Count
    Collections
    Conference Papers; Computer Science Program; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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