Convergence of Proportional-Fair Sharing Algorithms Under General Conditions

Kushner, Harold J.; Whiting, Philip

doi:10.1109/twc.2004.830826

Cited by 399 publications

(374 citation statements)

References 8 publications

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“…The connection is not unexpected given the fact that both our approach and [13] use the same utility functions to achieve fairness. However, unlike those approaches, which find longterm fair rates, our algorithm can find either long-term or short-term fair rates.…”

Section: Mixed Time-scale γ-Fair Af Relay Schedulingmentioning

confidence: 73%

“…For ǫ = 1/2, the algorithm is similar to the procedures proposed for single channel, single-hop, TDMA networks [13] and for conventional single-hop OFDMA networks [14]. The connection is not unexpected given the fact that both our approach and [13] use the same utility functions to achieve fairness.…”

Section: Mixed Time-scale γ-Fair Af Relay Schedulingmentioning

confidence: 85%

“…However, unlike those approaches, which find longterm fair rates, our algorithm can find either long-term or short-term fair rates. Also, note that, unlike [13], [14], our algorithm is for two-hop AF relay. For ǫ = 1, the algorithm is similar to the algorithm allocating short-term fair rates [5].…”

Section: Mixed Time-scale γ-Fair Af Relay Schedulingmentioning

confidence: 99%

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Mixed Time-Scale Generalized Fair Scheduling for Amplify-and-Forward Relay Networks

Sharifian

Djukic

Yanıkömeroğlu

et al. 2010

2010 IEEE Global Telecommunications Conference GLOBECOM 2010

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Abstract-We devise an optimization framework for generalized proportional fairness (GPF) under different time scales for amplify-and-forward (AF) relay networks. In GPF scheduling, a single input parameter is used to change the fairness from throughput optimal, to proportionally fair and asymptotically to max-min fair. We extend the GPF scheduling to include a new input parameter, which determines the time-scale of fairness from short-term GPF to long-term GPF. We devise a low-complexity near-optimal algorithm to find schedules satisfying the given fairness criteria in a given time-scale. Simulations show that the proposed algorithm indeed allows the flexibility to change the fairness and its time-scale. To the best of our knowledge, this paper is the first to provide a multi-user scheduling framework for AF relays with both flexible fairness and flexible time-scales.Index Terms-Long-term fairness, generalized fairness, amplify-and-forward relays.

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Section: Mixed Time-scale γ-Fair Af Relay Schedulingmentioning

confidence: 73%

Section: Mixed Time-scale γ-Fair Af Relay Schedulingmentioning

confidence: 85%

See 1 more Smart Citation

Mixed Time-Scale Generalized Fair Scheduling for Amplify-and-Forward Relay Networks

Sharifian

Djukic

Yanıkömeroğlu

et al. 2010

2010 IEEE Global Telecommunications Conference GLOBECOM 2010

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“…This ensures that A i [t] remains roughly constant over time under stationary channel conditions. Under reasonably general conditions, PF maximizes the sum of the logarithms of per-AT throughput [11] when the channel conditions of ATs are independent. Moreover, if their channel conditions are identically distributed, PF ensures that all ATs are allocated equal number of slots in the long term.…”

Section: The Pf Algorithm and Starvationmentioning

confidence: 99%

Beyond Proportional Fair: Designing Robust Wireless Schedulers

Bali

Machiraju

Zang

2007

NETWORKING 2007. Ad Hoc and Sensor Networks, Wireless Networks, Next Generation Internet

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“…Obviously, the performance of the considered system not only depends on node cooperation, it also depends on the metric used to select the (m, r) pair. Originally from Kelly's work [15], the proportionally fair scheduling (PFS) algorithm [16][17][18][19][20][21] has spurred the development of a large number of network utility maximization (NUM) algorithms since 1997 [22][23][24][25][26], and is implemented in current 3G networks [27] as the most-cited NUM method. Being a promising scheme for fair resource allocation, PFS has shown excellent balance between throughput and fairness via multi-user diversity and game-theoretic equilibrium.…”

Section: Introductionmentioning

confidence: 99%

Proportionally Fair Selective Cooperation for Cellular Networks: Algorithm, Simulation and Analysis

Liu

Zhang

Leung

2012

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Abstract. We consider the problem of 2-node cooperation for cellular networks. In the considered system, a node and a cooperative relay are selected in a proportionally fair (PF) manner to transmit to the base station (BS), which uses the maximal ratio combining (MRC) for reception. The proposed scheme integrates the PF criterion in selective cooperation to maximize the overall utility of all 2-node cooperative transmissions, and is called proportionally fair selective cooperation (PFSC). This technique does not require distributed space-time coding algorithms and its simplicity allows for immediate implementation in existing hardware. In this research, we further provide a mathematical framework to analyze the performance of PFSC under a Rayleigh flat fading channel. We also present an analytical expression for quantifying the throughput gain of a PFSC-enabled cellular network over a traditional PFS-enabled cellular network without node cooperation. Using simulations, we show that our model is very accurate. To our knowledge, it is the first time that a closed-form expression is obtained for the throughput of 2-node cooperative communication in a cellular network with the PF constraint.

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Convergence of Proportional-Fair Sharing Algorithms Under General Conditions

Cited by 399 publications

References 8 publications

Mixed Time-Scale Generalized Fair Scheduling for Amplify-and-Forward Relay Networks

Mixed Time-Scale Generalized Fair Scheduling for Amplify-and-Forward Relay Networks

Beyond Proportional Fair: Designing Robust Wireless Schedulers

Proportionally Fair Selective Cooperation for Cellular Networks: Algorithm, Simulation and Analysis

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