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The Journal of Supercomputing

Erschienen in:

01.09.2015

Delay-bounded resource allocation for femtocells exploiting the statistical multiplexing gain

verfasst von: Xin Chen, Yuan Si, Xudong Xiang

Erschienen in: The Journal of Supercomputing | Ausgabe 9/2015

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Abstract

Femtocell is an efficient solution for mobile operators to expand indoor coverage and increase network capacity. In this paper, we study the downlink resource allocation problem of two-tier macrocell–femtocell networks. We first formulate the problem as a Mixed Integer Non-Linear Program (MINLP) which aims to maximize the capacity of clustered femtocell networks subject to hard delay constraints of flows with different priorities. Next, we build \((\rho (\theta ),\sigma (\theta ))\) arrival model for the traffics and apply Stochastic Network Calculus (SNC) to transforming the delay constraints into alternative minimum transmission rate requirements, then we propose a resource allocation algorithm called S-SAPCS to solve the MINLP. Simulation results show that the proposed algorithm has near-optimal performance. We also design a scheme based on deterministic network calculus to show that S-SAPCS is able to exploit the statistical multiplexing gain among multiple flows, which improves the throughput significantly.

Vorheriger Artikel Game theoretic analysis for large-scale networks and traffic data

Nächster Artikel Power control with reinforcement learning in cooperative cognitive radio networks against jamming

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Titel: Delay-bounded resource allocation for femtocells exploiting the statistical multiplexing gain
verfasst von: Xin Chen
Yuan Si
Xudong Xiang
Publikationsdatum: 01.09.2015
Verlag: Springer US
Erschienen in: The Journal of Supercomputing / Ausgabe 9/2015
Print ISSN: 0920-8542
Elektronische ISSN: 1573-0484
DOI: https://doi.org/10.1007/s11227-015-1494-9

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