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The Journal of Supercomputing

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01-09-2015

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

Authors: Xin Chen, Yuan Si, Xudong Xiang

Published in: The Journal of Supercomputing | Issue 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.

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Title: Delay-bounded resource allocation for femtocells exploiting the statistical multiplexing gain
Authors: Xin Chen
Yuan Si
Xudong Xiang
Publication date: 01-09-2015
Publisher: Springer US
Published in: The Journal of Supercomputing / Issue 9/2015
Print ISSN: 0920-8542
Electronic ISSN: 1573-0484
DOI: https://doi.org/10.1007/s11227-015-1494-9

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