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Optimal and approximation algorithms for joint routing and scheduling in millimeter-wave cellular networks

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Optimal_and_Approximation_Algorithms.pdf (7.770Mb)
Identifiers
URI: http://hdl.handle.net/20.500.12761/835
ISSN: 1063-6692
DOI: DOI: 10.1109/TNET.2020.3006312
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Author(s)
Yuan, Dingwen; Lin, Hsuan-Yin; Widmer, Joerg; Hollick, Matthias
Date
2020-10
Abstract
Millimeter-wave (mmWave) communication is a promising technology to cope with the exponential increase in 5G data traffic. Such networks typically require a very dense deployment of base stations. A subset of those, so-called macro base stations, feature high-bandwidth connection to the core network, while relay base stations are connected wirelessly. To reduce cost and increase flexibility, wireless backhauling is needed to connect both macro to relay as well as relay to relay base stations. The characteristics of mmWave communication mandates new paradigms for routing and scheduling. The paper investigates scheduling algorithms under different interference models. To showcase the scheduling methods, we study the maximum throughput fair scheduling problem. Yet the proposed algorithms can be easily extended to other problems. For a fullduplex network under the no interference model, we propose an efficient polynomial-time scheduling method, the scheduleoriented optimization. Further, we prove that the problem is NPhard if we assume pairwise link interference model or halfduplex radios. Fractional weighted coloring based approximation algorithms are proposed for these NP-hard cases. Moreover, the approximation algorithm parallel data stream scheduling is proposed for the case of half-duplex network under the no interference model. It has better approximation ratio than the fractional weighted coloring based algorithms and even attains the optimal solution for the special case of uniform orthogonal backhaul networks.
Share
Files
Optimal_and_Approximation_Algorithms.pdf (7.770Mb)
Identifiers
URI: http://hdl.handle.net/20.500.12761/835
ISSN: 1063-6692
DOI: DOI: 10.1109/TNET.2020.3006312
Metadata
Show full item record

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