Joint Realtime and Nonrealtime Flows Packet Scheduling and Resource Block Allocation in Wireless OFDMA Networks

Sharifian, Alireza; Schoenen, Rainer; Yanıkömeroğlu, Halim

doi:10.1109/tvt.2015.2425883

Cited by 19 publications

(9 citation statements)

References 63 publications

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“…Those techniques can provide guidelines for network design, simplify parametrization, and assess compounded optimization criteria for heterogeneous networks. The network designer must establish resource allocation strategies to conciliate conflicted objectives, keeping in mind that the ultimate goals are user experience, satisfaction, and operators' interest [301].…”

Section: Discussion and Future Directionsmentioning

confidence: 99%

An Overview on Resource Allocation Techniques for Multi-User MIMO Systems

Castañeda

Silva

Gameiro

et al. 2017

IEEE Commun. Surv. Tutorials

179

123

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Abstract-Remarkable research activities and major advances have been occurred over the past decade in multiuser multipleinput multiple-output (MU-MIMO) systems. Several transmission technologies and precoding techniques have been developed in order to exploit the spatial dimension so that simultaneous transmission of independent data streams reuse the same radio resources. The achievable performance of such techniques heavily depends on the channel characteristics of the selected users, the amount of channel knowledge, and how efficiently interference is mitigated. In systems where the total number of receivers is larger than the number of total transmit antennas, user selection becomes a key approach to benefit from multiuser diversity and achieve full multiplexing gain. The overall performance of MU-MIMO systems is a complex joint multi-objective optimization problem since many variables and parameters have to be optimized, including the number of users, the number of antennas, spatial signaling, rate and power allocation, and transmission technique. The objective of this literature survey is to provide a comprehensive overview of the various methodologies used to approach the aforementioned joint optimization task in the downlink of MU-MIMO communication systems.

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Section: Discussion and Future Directionsmentioning

confidence: 99%

An Overview on Resource Allocation Techniques for Multi-User MIMO Systems

Castañeda

Silva

Gameiro

et al. 2017

IEEE Commun. Surv. Tutorials

179

123

View full text Add to dashboard Cite

show abstract

“…1 -QoS without interference awareness: This set of works studies the sub-problem of queue scheduling and resource allocation addressing only QoS and fairness without adequate attention to interference. Examples include maximizing average utilities balancing efficiency and fairness [6], analysis of generalized proportional fairness [7], scheduling for elastic traffic using convex optimization [8], single cell throughput maximization with rate guarantees [2], utility maximization with rate constraints through a token counter [9], minimum rate guarantees using a Lagrangian approach [10], joint channel-and queue-aware scheduling for mean-delay utility maximization [11], mean-delay fairness via gradient method [12], joint real-time and non-real-time packet scheduling and resource allocation [13], mean-delay guarantees through time-coupling constraints and Lagrange dual-based solutions [14], maximizing goodput for multihop networks through dual solutions [15], utility maximization and routing with probabilistic delay requirements [16], adapting rates with delay constraints to increase network video capacity [17], QoS-aware routing and subchannel allocation in time-slotted realy networks, without interference coordination, and dynamic user association [18], and, in single AP, single frequency networks, optimizing secondary users' delay based on interference [19].…”

Section: A Related Work and Identifying The Research Gapmentioning

confidence: 99%

Queue-Aware Joint Dynamic Interference Coordination and Heterogeneous QoS Provisioning in OFDMA Networks

Sharifian

Adve

2018

IEEE Trans. Wireless Commun.

Self Cite

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We propose algorithms for cloud radio access networks that not only provide heterogeneous quality of-service (QoS) for rate-and, importantly, delay-sensitive applications, but also jointly optimize the frequency reuse pattern. Importantly, unlike related works, we account for random arrivals, through queue awareness and, unlike majority of works focusing on a single frame only, we consider QoS measures averaged over multiple frames involving a set of closed loop controls. We model this problem as multi-cell optimization to maximize a sum utility subject to the QoS constraints, expressed as minimum mean-rate or maximum mean-delay. Since we consider dynamic interference coordination jointly with dynamic user association, the problem is not convex, even after integer relaxation. We translate the problem into an optimization of frame rates, amenable to a decomposition into intertwined primal and dual problems. The solution to this optimization problem provides joint decisions on scheduling, dynamic interference coordination, and, importantly, unlike most works in this area, on dynamic user association. Additionally, we propose a novel method to manage infeasible loads. Extensive simulations confirm that the design responds to instantaneous loads, heterogeneous user and AP locations, channel conditions, and QoS constraints while, if required, keeping outage low when dealing with infeasible loads. Comparisons to the baseline proportional fair scheme illustrate the gains achieved.Index Terms-Heterogeneous QoS, finite backlog, dynamic interference coordination, dynamic user association.

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“…However, applying such strict admission control in a public WMN is undesirable due to network resources underutilization. Because the QoS requirement of an application usually can be specified based on its peak usage, guaranteeing QoS for the application can be overprovisioning QoS, which leads to inefficient network resource utilization [5][6][7]. Moreover, due to the mobility of mesh clients transiting multiple mesh routers, the amount of traffic to be guaranteed with a specific QoS requirement will vary over time.…”

Section: Introductionmentioning

confidence: 99%

An Efficient Local Repair‐Based Multi‐Constrained Routing for Congestion Control in Wireless Mesh Networks

Shin

Lee

2018

Wireless Communications and Mobile Computing

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Multi-constrained routing is a key driver to support quality-of-service (QoS) for real-time multimedia applications in wireless mesh networks (WMNs). Due to the difficulty of applying strict admission control into a public WMN, it is inevitable to accommodate multiple application flows with different QoS requirements exceeding the capacity of a certain link shared by multiple flows. However, existing multi-constrained routing protocols under such an environment find the QoS degradation based on end-to-end path quality probing and trigger flooding-based route discovery from a scratch for resolving the QoS degradation, which incurs a longer recovery time and much routing overhead. In this paper, we propose a novel multi-constrained routing protocol for WMNs that finds problematic links that may affect QoS degradation to end-to-end paths and replaces them with a detour path using a local repair principle. We model congestion threshold estimation for finding problematic links and design algorithms for quickly finding detour paths and selecting an optimal path by minimizing the negative effect on existing flows nearby the detour path. Simulation results show that the proposed routing protocol achieves up to 19.6% more goodput of live video streaming applications with up to 33% reduced routing overhead compared with an existing work.

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Joint Realtime and Nonrealtime Flows Packet Scheduling and Resource Block Allocation in Wireless OFDMA Networks

Cited by 19 publications

References 63 publications

An Overview on Resource Allocation Techniques for Multi-User MIMO Systems

An Overview on Resource Allocation Techniques for Multi-User MIMO Systems

Queue-Aware Joint Dynamic Interference Coordination and Heterogeneous QoS Provisioning in OFDMA Networks

An Efficient Local Repair‐Based Multi‐Constrained Routing for Congestion Control in Wireless Mesh Networks

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