One of the key building blocks of the newly emerging 5th generation (5G) wireless communication system are ultra dense small cells. In this paper, the system performance of such a deployment is studied for scenarios where there are individual deadlines to serve data packets. A proactive delay-minimizing scheduling method (PDMS) is proposed to minimize the number of dropped packets due to missed deadlines and further reduce the average delay of the served packets. It is assumed that the radio scheduler does not only have information about the packet deadlines, but also has some information on how channel properties will evolve in the future. In practice, such information could be obtained through a prediction of user trajectories or prediction of fading signals, but this is beyond the scope of this paper. The presented results show that the proposed scheduler performs well in high load regimes. It substantially reduces the number of dropped packets and the average delay as compared to a non-deadline-aware one. The good overall performance recommends the proposed scheme as a potential component for 5G systems where there will likely be a wide diversity of applications with more stringent quality of service and latency requirements.


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    Title :

    Proactive Delay-Minimizing Scheduling for 5G Ultra Dense Deployments


    Contributors:


    Publication date :

    2015-09-01


    Size :

    242411 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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