Scheduling alternatives for mobile WiMAX end-to-end simulations and analysis

Valencia, Carlos; Kunz, Thomas

doi:10.1145/1815396.1815483

Cited by 7 publications

(8 citation statements)

References 23 publications

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“…The PF with a window size, t c = 50K achieves higher goodput than t c = 500 since the high t c results in a greedy like performance. The bigger value of t c serves users with good channel longer and delays the users with poor channel and leaves them underserved [9]. The PF with t c =500 has a lower goodput due to the fact that it considers fairness and behaves similarly as WFQ for this specific scenario.…”

Section: B Multiple Sss and Downlink Scheduling Analysismentioning

confidence: 99%

“…The traffic load is calculated as in (7) We then consider 3, 6, 10 and 50 users in a cell at the range supporting 64QAM ¾ STBC for WFQ and PF as well as Greedy independently. We configure a CBR traffic load with the packet size of 1024 bytes whilst the PF has two different t c parameters equals to 500 [13] and 50K [9]. Our aim is to compare the maximum achievable UGS goodput as well as average delay for channel-aware and queue-aware schedulers for a group of users.…”

Section: Scenariosmentioning

confidence: 99%

“…studied in particular for SISO, STBC and SM [6][7][8][9]. UGS is one of the defined QoS class types in the IEEE 802.16 standard.…”

Section: Introductionmentioning

confidence: 99%

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Performance evaluation of MIMO downlink WiMAX for different schedulers

Dziyauddin

Doufexi

Kaleshi

2010

2010 Wireless Advanced 2010

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Abstract-WiMAX performance evaluation considering different scheduling techniques has received considerable attention by WiMAX researchers and also WiMAX operators. The standard does not define MAC scheduling although it affects the overall QoS performance of users as well as the achievable total cell goodput. The primary goal of this paper is to compare the performance of maximum total goodput including the average delay for UGS (Unsolicited Grant Service) users employing channel-aware and queue-aware downlink schedulers for a group of users. The paper initially considers the goodput behaviour and its peak across different modulation and coding schemes for SISO and MIMO (both Space Time Block Code (STBC) and Spatial Multiplexing (SM)) connections for a single user. The achievable maximum goodput is shown to be between 94.5% and 97.0% of the theoretical data rates. The analysis is then expanded to multiple users considering Proportional Fair (PF) with different observation window, t c , Greedy and also Weighted Fair Queuing (WFQ) schedulers to serve downlink QoS flows. The PF with a higher t c = 50K exceptionally outperforms WFQ as well as the PF with a smaller t c = 500 for a higher number of users and shows a greedy like performance. The channelaware scheduler generally performs better than the queueaware scheduler.

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Section: B Multiple Sss and Downlink Scheduling Analysismentioning

confidence: 99%

Section: Scenariosmentioning

confidence: 99%

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Performance evaluation of MIMO downlink WiMAX for different schedulers

Dziyauddin

Doufexi

Kaleshi

2010

2010 Wireless Advanced 2010

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“…A comparison of WFQ, PFS, and MLWDF under several WiMAX application scenarios is provided in [36]. The outcome is that no scheduler is superior to the others in all situations, but the authors suggest that the ideal scheduler could be a hybrid algorithm that incorporates MLWDF and WFQ.…”

Section: Related Workmentioning

confidence: 99%

Game theory and time utility functions for a radio aware scheduling algorithm for WiMAX networks

et al. 2011

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In WiMAX systems the Base Station scheduler plays a key role as it controls the sharing of the radio resources among the users. The goal of the scheduler is multiple: achieve fair usage of the resources, satisfy the QoS requirements of the users, maximize goodput, and minimize power consumption, and at the same time ensuring feasible algorithm complexity and system scalability. Since most of these goals are contrasting, scheduler designers usually focus their attention on optimizing one aspect only. In this scenario, we propose a scheduling algorithm (called GTS(N)) whose goal is to contemporaneously achieve efficiency and fairness, while also taking into account the QoS requirements and the channel state. GTS(N) exploits the properties of Time Utility Functions (TUFs) and Game Theory. Simulations prove that the performance of GTS(N); when compared to that of several well-known schedulers, is remarkable. GTS(N) provides the best compromise between the two contrasting objectives of fairness and efficiency, while QoS requirements are in most cases guaranteed. However, the exponential complexity introduced by the game theory technique makes it rather impractical and not computationally scalable for a large number of users. Thus we developed a suboptimal version, named sub-GTS(N): We show that this version retains most of the features and performance figures of its brother, but its complexity is linear with the number of users

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“…The multiple-carrier PHY spectrum works under the 2-11 GHz range for the fixed and mobile stations and has the Line of Sight (LOS) and Non LOS features [4,5]. The WiMAX MAC layer is designed and implemented with some advanced features to provide efficiency, flexibility, encryption, error correction, link adaptation, power control, security, Automatic Retransmission Request (ARQ) and QoS for Uplink (UL) and Downlink (DL) traffic [6,7]. The MAC layer comprises of three sub-layers which are the service specific Convergence Sub-layer (CS), the Common Part Sub-layer (CPS) and the Security Sub-layer [8,9].…”

Section: Introductionmentioning

confidence: 99%

Enhanced uplink scheduling algorithm for efficient resource management in IEEE 802.16

Oad

Subramaniam

Zukarnain

2015

J Wireless Com Network

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Worldwide interoperability for Microwave Access (WiMAX) is based on the IEEE 802.16 standard. This technology provides broadband wireless last-mile access in a Metropolitan Area Network (MAN). The IEEE 802.16-2004 standard (i.e. Fixed WiMAX) provides specification for the Medium Access Control (MAC) and Physical (PHY) layers for WiMAX. A critical part of the MAC layer specification is scheduling, which resolves contention for bandwidth and determines the transmission order of users. The algorithms are researched under different mixes of traffic and for various characteristics of the IEEE 802.16 MAC layer. In this research the focus is on the WiMAX uplink traffic scheduling. A scheduling algorithm's task in a multi-class network is also to categorize the users into one of the pre-defined classes. In this research, the algorithms are tailored at enhancing the collective performance of hybrid algorithms in the WiMAX domains which complement the assigned priorities. The spectrum of constraints which have been extracted from the hybrid Earliest Deadline First(EDF) + Weighted Fair Queuing (WFQ) + First in First out (FIFO) EDF+WFQ+FIFO algorithm include the static nature by which priorities are assigned and maintained during the entire duration of a transmission time and the core attributes of absolute dependence on deadline. The second constraint is embedded within the EDF scheduling algorithm and the perseverance of pursuing deadline associated weightages. In this research, the reengineering of the scheduling mechanics governing the EDF algorithms has been pursued. The dominance of the pre-stipulated deadline of the EDF algorithm is indeed acknowledged in the proposed and developed enhanced algorithm. The simulation results indicate that the legacy algorithms are not suitable for the multi-class traffic systems of WiMAX. This is because these algorithms do not explicitly incorporate the WiMAX QoS parameters into their mechanisms and are highly static. Extensive discrete -event simulation experiments have been done for the purpose of performance analysis. The performance metrics used are average throughput, average delay, missed deadline ratio and average queue size utilization ratio. The acquired results have proven that the proposed algorithms have successfully enhanced the static constrained algorithm.

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Scheduling alternatives for mobile WiMAX end-to-end simulations and analysis

Cited by 7 publications

References 23 publications

Performance evaluation of MIMO downlink WiMAX for different schedulers

Performance evaluation of MIMO downlink WiMAX for different schedulers

Game theory and time utility functions for a radio aware scheduling algorithm for WiMAX networks

Enhanced uplink scheduling algorithm for efficient resource management in IEEE 802.16

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