On the Delay-Fairness through Scheduling for Wireless OFDMA Networks

Sharifian, Alireza; Yanıkömeroğlu, Halim

doi:10.1109/vetecs.2011.5956739

Cited by 2 publications

(5 citation statements)

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“…This frugality constraint ensures that the service rate to be less than the backlog and prevents resources being wasted on a flow without a sufficient backlog. As derived in [12], the constants ζ…”

Section: A Translating Mac Constraints To Frame Rate Constraintsmentioning

confidence: 94%

“…The translation in this section forms our second major contribution, discussed in Section II-B. We note that, unlike many of the related works, our problem in (12) is not convex (due to dynamic interference coordination and dynamic user association). As such, in the next section, we combine several techniques in order to devise an effective solution.…”

Section: Summary Of Translationmentioning

confidence: 99%

“…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 evolution (conservation on arrivals and departures), and estimating the arrival through its empirical expected value, the mean-delay can be approximated as (see [12]):…”

Section: A Translating Mac Constraints To Frame Rate Constraintsmentioning

confidence: 99%

“…In the previous section, we provided the guideline solving the translated per-frame optimization problem in (12): Dual iterations form an outer loop using updates as per (22); Primal iterations form an inner loop updating the primal variables as per (20). In this section, we use the guideline, in the previous section, and devise our proposed QOS AWARE INTERFERENCE COORDINATION (QOSAIC) algorithm.…”

Section: Algorithms: Qosaic Ilm and Inter-frame Qosaicmentioning

confidence: 99%

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

Sharifian

Adve

2018

IEEE Trans. Wireless Commun.

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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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Section: A Translating Mac Constraints To Frame Rate Constraintsmentioning

confidence: 94%

Section: Summary Of Translationmentioning

confidence: 99%

Section: A Related Work and Identifying The Research Gapmentioning

confidence: 99%

“…), queue evolution (conservation on arrivals and departures), and estimating the arrival through its empirical expected value, the mean-delay can be approximated as (see [12]):…”

Section: A Translating Mac Constraints To Frame Rate Constraintsmentioning

confidence: 99%

Section: Algorithms: Qosaic Ilm and Inter-frame Qosaicmentioning

confidence: 99%

See 3 more Smart Citations