Opportunistic packet loss fair scheduling for delay-sensitive applications over LTE systems

Self Cite

The scarcity of the available radio spectrum coupled with the growing popularity of bandwidth intensive mobile video applications poses a huge challenge to network operators. The solution of over-provisioning the network is not economical; hence, an appropriate strategy for scheduling and resource allocation among the users in the system is of crucial importance. This work focuses on scheduling multiple video flows on the downlink of a wireless system based on orthogonal frequency division multiple access (OFDMA), such as Long-Term Evolution (LTE) and LTE-A (LTE-Advanced) standards. We propose a joint multi-user scheduling and multi-user rate adaptation strategy providing an appropriate trade-off between efficiency and fairness, while ensuring high quality of experience (QoE) for the end users. We consider Scalable Video Coding (SVC) which facilitates the truncation of bit streams, thus allowing graceful degradation of video quality in the event of wireless channel variations or network congestion. The proposed scheduler utilizes QoE-aware priority marking, where video layers are mapped to priority classes and targets at minimizing delay bound violations for the most important priority classes under congestion. In order to reduce congestion, we propose multi-user rate adaptation at the MAC layer via a novel dynamic filtering policy for QoE-based priority classes. Simulation results show that the proposed approach delivers to the end users a similar QoE as delivered by the stateof-the-art cross-layer approaches, where extensive cross-layer signaling, additional video rate adaptation modules at the core network, and frequent link probing from the wireless access network to the rate adaptation modules are required. The latter approaches are not implemented in real systems due to the aforementioned drawbacks, while our approach can be implemented without major modifications in the standard behavior of existing networks and equipment. The proposed framework can deliver delay-sensitive traffic as well as delay-tolerant best-effort traffic.

Section: Algorithm 1 Packet Priority Schedulermentioning

confidence: 99%

QoE-driven multi-user scheduling and rate adaptation with reduced cross-layer signaling for scalable video streaming over LTE wireless systems

Khan

Martini

2016

Self Cite

“…LTE schedulers that use define opportunity in the form of channel conditions or data queue have also been studied for LTE in addition to schemes adopting service attribute like priority and scheduling delay [20][21][22][23][24][25][26]. Opportunistic scheduling exploits channel statistics and user traffic loads to define opportunities related to resource allocation and scheduling while improving overall throughput of the network.…”

Section: Related Workmentioning

confidence: 99%

A capacity and minimum guarantee-based service class-oriented scheduler for LTE networks

Salman

Zeeshan

Anjum

2013

Quality-of-service (QoS) requirements have always posed a challenge from scheduling perspective and it becomes more complicated with the emergence of new standards and applications. Classical techniques like maximum throughput, proportional fair, and exponential rule have been used in common network scenarios but these techniques fail to address diverse service requirements for QoS provisioning in long-term evolution (LTE). These QoS requirements in LTE are implemented in the form of delay budgets, scheduling priorities, and packet loss rates. Scheduler design for LTE networks therefore requires handling service class attributes but preciously proposed scheduling methods ignored service class-based design and focused more on single network prospect. To address service class requirements in LTE, we propose a modified radio resource management-based scheduler with minimum guarantee in the downlink following network capacity and service class attributes defined in LTE standard. The scheduler takes advantage of best available channel conditions while maintaining data rates corresponding to minimum resources guaranteed for all major classes including the best effort class. A method is proposed to determine the scheduling resource capacity of active users in LTE networks with an admission control to limit the number of users according to available resources. In addition to closely matched theoretical and simulated active users that can be accommodated in the system, promising results are provided for system delay, throughput, and user mobility.

“…Thus, it can be implemented in real time. However, for delay-sensitive traffic, these scheduling rules cannot provide fairness for users with relatively low signal-to-interference noise ratio (SINR) [14].…”

Section: Introductionmentioning

confidence: 99%

QoS-aware composite scheduling using fuzzy proactive and reactive controllers

Khan

Martini

Staehle

2014

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We consider in this paper downlink scheduling for different traffic classes at the MAC layer of wireless systems based on orthogonal frequency division multiple access (OFDMA), such as the recent 3rd Generation Partnership Project (3GPP) long-term evolution (LTE)/LTE-A wireless standard. Our goal is to provide via the scheduling decisions quality of service (QoS), but also to guarantee fairness among the different users and traffic classes (including delay-sensitive and best-effort traffic). QoS-aware scheduling strategies, such as modified largest weighted delay first (M-LWDF), exponential (EXP), exponential proportional fair (EXP-PF), and the log-based scheduling rules, prioritize delay-sensitive traffic by considering rules based on the head-of-line (HoL) packet delay and the tolerated packet loss rate, whereas they serve best-effort traffic by considering the classical proportional fair (PF) rule. These scheduling rules do not prevent resource starvation for best-effort traffic. On the other side, if both traffic types are scheduled according to the PF rule, then delay-sensitive flows suffer from delay bound violations. In order to fairly distribute the resources among different service classes according to their QoS requirements and channel conditions, we employ the concept of fuzzy logic in our scheduling framework. By employing the fuzzy logic concept, we serve all the traffic classes with one priority rule. Simulation results show better intra-class and inter-class fairness than state-of-the-art scheduling rules. The proposed scheduling framework enables to appropriately balance delay requirements of traffic, system throughput, and fairness.