Scheduler Design for Multiple Traffic Classes in OFDMA Networks

Abstract-Interest in broadband wireless access (BWA) has been growing due to increased user mobility and the need for data access at all times. IEEE 802.16e based WiMAX networks promise the best available quality of experience for mobile data service users. Unlike wireless LANs, WiMAX networks incorporate several quality of service (QoS) mechanisms at the Media Access Control (MAC) level for guaranteed services for data, voice and video. The problem of assuring QoS is basically that of how to allocate available resources among users in order to meet the QoS criteria such as delay, delay jitter and throughput requirements. IEEE standard does not include a standard scheduling mechanism and leaves it for implementer differentiation. Scheduling is, therefore, of special interest to all WiMAX equipment makers and service providers. This paper discusses the key issues and design factors to be considered for scheduler designers. In addition, we present an extensive survey of recent scheduling research. We classify the proposed mechanisms based on the use of channel conditions. The goals of scheduling are to achieve the optimal usage of resources, to assure the QoS guarantees, to maximize goodput and to minimize power consumption while ensuring feasible algorithm complexity and system scalability.

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“…Variation of M-LWDF [66], [67], [68], [69] Meet the throughput and delay guarantee with threshold probability ertPS, rtPS and nrtPS…”

Section: Discussionmentioning

confidence: 99%

“…Another modification of M-LWDF has been proposed to support multiple traffic classes [69]. The UEPS is not always efficient when the scheduler provides higher priority to nrtPS and BE traffic than rtPS, which may be near their deadlines.…”

Section: ) Fairnessmentioning

confidence: 99%

Scheduling in IEEE 802.16e mobile WiMAX networks: key issues and a survey

So-In

Jain

Al-Tamimi

2009

IEEE J. Select. Areas Commun.

290

182

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“…However, the authors do not consider the non-real-time data packets. The authors in [21] show that MLWDF provides better QoS and Quality of Experience (QoE) than other scheduling algorithms in terms of packet loss ratio and delay. In [22], an MLWDF based joint scheduling has been proposed with multiple traffic classes, where the priority of traffic class and waiting time in the queue of each packet are considered.…”

Section: Related Workmentioning

confidence: 99%

“…The MLWDF scheduling algorithm has been studied in [20][21][22] to analyze the performance and maximize the QoS of cell user. A delay priority based algorithm is used in [20] where the user gets higher priority if the packet delay is close to the threshold for real-time data.…”

Section: Related Workmentioning

confidence: 99%

Enhanced Quality of Service of Cell-Edge User by Extending Modified Largest Weighted Delay First Algorithm in LTE Networks

et al. 2017

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Long Term Evolution (LTE) is the prominent technology in Fourth Generation (4G) communication standards, which provides higher throughput and better Quality of Service (QoS) to all users. However, users in the cell-edge area are receiving comparatively low QoS due to the distance from eNodeB (eNB) and bad channel conditions. The Conventional Modified Largest Weighted Delay First (MLWDF) algorithm is unable to resolve this issue, as it does not consider the location of the user. This paper proposes an extended MLWDF (EMLWDF) downlink scheduling algorithm to provide better services to the cell-edge user as well as to the cell-center user. The proposed algorithm divides the eNB cell area into inner and outer regions. It includes the distance of the user from attached eNB, received Signal to Interference plus Noise Ratio (SINR) and error probability into the original algorithm. The simulated results are compared with other well-known algorithms and the comparison shows that the proposed algorithm enhances overall 56.23% of cell-edge user throughput and significantly improves the average user throughput, fairness index, and spectral efficiency.

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“…is the HOL packet delay (or queue length on implementations that consider non-delay sensitive BE traffic [24] ) and ) ( k i t r is the channel capacity with respect to flow i. By keeping an eye on queue states, as well as channel conditions, the algorithm optimizes the throughput delivered to certain connections, while still keeping queues from getting into a full congestion state.…”

Section: Opportunistic and Cross-layer Algorithmsmentioning

confidence: 99%