Please use this identifier to cite or link to this item: https://ruomo.lib.uom.gr/handle/7000/1371
Title: Scheduling of Heterogeneous Services by Resolving Conflicts
Authors: Skaperas, Sotiris
Ferdosian, Nasim
Chorti, Arsenia
Mamatas, Lefteris
Type: Article
Subjects: FRASCATI::Engineering and technology
FRASCATI::Engineering and technology
Keywords: Time-frequency resource allocation
URLLC traffic
wireless communication
scheduling
Issue Date: 2022
Source: IEEE Access
Volume: 10
First Page: 36576
Last Page: 36591
Abstract: Fifth generation (5G) new radio introduced flexible numerology to accommodate heterogeneous services. However, optimizing the scheduling of heterogeneous services with differing delay and throughput requirements over 5G new radio is a challenging task. In this paper, we investigate near optimal, low complexity scheduling of radio resources for ultra-reliable low-latency communications (URLLC) when coexisting with enhanced mobile broadband (eMBB) services. We demonstrate that maximizing the sum throughput of eMBB services while servicing URLLC users over a fixed length time-frequency grid, is, in the long-term, equivalent to minimizing the number of URLLC placements in the time-frequency grid; this is the consequence of reducing the number of infeasible placements for eMBB, to which we refer to as “conflicts.” To meet this new objective, we evaluate the performance of new, conflict-aware heuristics, consisting of a family of “greedy” and a lightweight heuristic inspired by bin packing optimization, all of near optimal performance. Moreover, having shed light on the impact of conflict in layer-2 scheduling, we investigate non-orthogonal multiple access (NOMA) as a potential approach for conflict resolution leveraging superposition coding. The superior performance of NOMA with respect to OMA, thanks to resolving conflicts, is showcased by extensive numerical results.
URI: https://doi.org/10.1109/ACCESS.2022.3163388
https://ruomo.lib.uom.gr/handle/7000/1371
ISSN: 2169-3536
Other Identifiers: 10.1109/ACCESS.2022.3163388
Appears in Collections:Department of Applied Informatics

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