Maximizing network revenue through resource management in heterogeneous wireless networks

Khloussy, Elissar; Xu, Jie; Kim, A. N.; Jiang, Yuming

doi:10.1109/iscc.2011.6024143

Cited by 2 publications

(2 citation statements)

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“…However, the proposed CRRM strategy, based on a fuzzy neural network, is complex for implementation in real networks. In our early work [9], CRRM strategies based on call admission control and vertical handover were presented and compared. It was shown that a significant increase of revenue could be incurred by the adoption of CRRM policies.…”

Section: Introductionmentioning

confidence: 99%

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A Revenue-Maximizing Scheme for Radio Access Technology Selection in Heterogeneous Wireless Networks with User Profile Differentiation

Khloussy¹,

Gelabert

Jiang³

2013

Lecture Notes in Computer Science

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Abstract. In this paper, the problem of radio access technology (RAT) selection in heterogeneous wireless networks (HWNs) is tackled from an operator's perspective, with the objective of maximizing the generated revenue. Two user profiles are considered with different priority levels. An integrated 3GPP Long Term Evolution (LTE) and Wireless Fidelity (WiFi) network is considered as an example of HWN, where LTE is used mainly for the high-priority class, while a portion of its resources, defined by a load threshold, can be shared by the low-priority class. A Markovian model is defined and validated by simulation. Subsequently, the value of the load threshold for resource sharing in LTE is investigated, and an optimization problem is formulated to find the optimal threshold for which the revenue is maximized.

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Section: Introductionmentioning

confidence: 99%

“…It was shown that a significant increase of revenue could be incurred by the adoption of CRRM policies. However, the evaluation in [9] was only based on simulation. Other admission control where decisions are taken dynamically to maximize the operator's revenue can also be found in the literature [10,11].…”

Section: Introductionmentioning

confidence: 99%