Downlink cross-layer scheduling strategies for long-term evolution and long-term evolution-advanced systems

The most recent trend in the Information and Communication Technology world is toward an ever growing demand of mobile heterogeneous services that imply the management of different quality of service requirements and priorities among different type of users. The long‐term evolution (LTE)/LTE‐advance...

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Veröffentlicht in:Wireless communications and mobile computing 2015-06, Vol.15 (8), p.1234-1246
Hauptverfasser: Bartoli, Giulio, Fantacci, Romano, Marabissi, Dania, Tarchi, Daniele, Tassi, Andrea
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Sprache:eng
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Zusammenfassung:The most recent trend in the Information and Communication Technology world is toward an ever growing demand of mobile heterogeneous services that imply the management of different quality of service requirements and priorities among different type of users. The long‐term evolution (LTE)/LTE‐advanced standards have been introduced aiming to cope with this challenge. In particular, the resource allocation problem in downlink needs to be carefully considered. Herein, a solution is proposed by resorting to a modified multidimensional multiple‐choice knapsack problem modeling, leading to an efficient solution. The proposed algorithm is able to manage different traffic flows taking into account users priority, queues delay, and channel conditions achieving quasi‐optimal performance results with a lower complexity. The numerical results show the effectiveness of the proposed solution with respect to other alternatives. Copyright © 2013 John Wiley & Sons, Ltd. The most recent trend in the information and communication technology world is toward an ever growing demand of mobile heterogeneous services. For coping with this scenario, the resource allocation problem in long‐term evolution‐advanced standards needs to be carefully considered. Herein, a solution is proposed by resorting to a modified multidimensional multiple‐choice knapsack problem modeling. The proposed algorithm is able to manage different traffic flows taking into account users priority, queues delay, and channel conditions achieving quasi‐optimal performance results with a lower complexity.
ISSN:1530-8669
1530-8677
DOI:10.1002/wcm.2406