IEEE Global Telecommunications Conference, 2004. GLOBECOM '04. 2004
DOI: 10.1109/glocom.2004.1378493
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Scheduling algorithms for quality of service aware OFDMA wireless systems

Abstract: Abstract-In this paper, we investigate scheduling in multiuser OFDMA systems. The objective is to maximize the resource utilization in a network, while a required Quality of Service (QoS) per user is satisfied. A notion of revenue maximization is used to determine the optimal OFDMA subcarrier allocation to different users based on their required QoS. The optimal solution for the problem is presented and its performance and complexity are studied. An iterative low complexity algorithm is also proposed to achiev… Show more

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Cited by 14 publications
(7 citation statements)
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“…QoS-aware packet schedulers are studied in [1] and [2], however, these solutions do not consider LTE-specific requirements. In LTE, the resources that can be assigned to a UE have both time and frequency dimensions.…”
Section: Introductionmentioning
confidence: 99%
“…QoS-aware packet schedulers are studied in [1] and [2], however, these solutions do not consider LTE-specific requirements. In LTE, the resources that can be assigned to a UE have both time and frequency dimensions.…”
Section: Introductionmentioning
confidence: 99%
“…While time domain multiplexing radio access system like High Speed Downlink Packet Access (HSDPA) allows time domain user diversity packet scheduling [2], OFDMA also provides the possibility of performing frequency domain packet scheduling and thereby obtain significant gains in cell throughput and coverage thanks to multiuser frequency diversity [3]. QoS aware packet schedulers for OFDMA are studied in [4] and [5]. Those algorithms do not consider practical aspects and restrictions that will be met in an actual system like LTE.…”
Section: Introductionmentioning
confidence: 99%
“…In [15], Aniba and Aissa presented a similar approach for adaptive PF. Other approaches by Hosein [10] and Farrokhi [9] has been proposed and they aims to define a network revenue function which allow capacity maximization and QoS fulfilment.…”
Section: Introductionmentioning
confidence: 99%