On Backoff in Fading Wireless Channels

Han, Seon-Yeong; Abu-Ghazaleh, Nael

doi:10.1007/978-3-540-85209-4_20

Cited by 4 publications

(3 citation statements)

References 10 publications

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“…Combing (35), (36) and (37), we have detailed balance equation (34) hold. The Markov chain is hence time-reversible and has the stationary distribution given in (17).…”

Section: F Proof Of Lemmamentioning

confidence: 99%

“…The application of such a homogeneous model, however, is quite restricted, since users typically have heterogenous channel contention probabilities in wireless systems. For example, users of heterogeneous wireless channel conditions may have heterogeneous packet transmission error rates, which in turn result in heterogeneous channel contention window sizes at the equilibrium according to the distributed coordination function (DCF) of IEEE 802.11 networks [17]. This implies that users would have heterogeneous channel contention probabilities if they have heterogeneous equilibrium contention window sizes.…”

Section: Introductionmentioning

confidence: 99%

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Distributed Spectrum Access with Spatial Reuse

Chen

Huang

2013

IEEE J. Select. Areas Commun.

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Efficient distributed spectrum sharing mechanism is crucial for improving the spectrum utilization. The spatial aspect of spectrum sharing, however, is less understood than many other aspects. In this paper, we generalize a recently proposed spatial congestion game framework to design efficient distributed spectrum access mechanisms with spatial reuse. We first propose a spatial channel selection game to model the distributed channel selection problem with fixed user locations. We show that the game is a potential game, and develop a distributed learning mechanism that converges to a Nash equilibrium only based on users' local observations. We then formulate the joint channel and location selection problem as a spatial channel selection and mobility game, and show that it is also a potential game. We next propose a distributed strategic mobility algorithm, jointly with the distributed learning mechanism, that can converge to a Nash equilibrium. Numerical results show that the Nash equilibria achieved by the proposed algorithms have only less than 8% performance loss, compared with the centralized optimal solutions.

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“…Combing (35), (36) and (37), we have detailed balance equation (34) hold. The Markov chain is hence time-reversible and has the stationary distribution given in (17).…”

Section: F Proof Of Lemmamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Distributed Spectrum Access with Spatial Reuse

Chen

Huang

2013

IEEE J. Select. Areas Commun.

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“…Experiments show a better behavior of the NBA scheme in comparison to the BEB scheme. Yeong Han and Abu-Ghazaleh (2008) have proposed three algorithms that aim to distinguish between collisions and transmission errors. When a failure of transmission due to transmission error occurs, it is not necessary to wait for backoff time before retransmission.…”

Section: Related Workmentioning

confidence: 99%

An Adaptive Backoff Algorithm for Mobile Ad-Hoc Networks

Khamayseh

Yassein

Badran

et al. 2011

International Journal of Mobile Computing and Multimedia Communications

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Collision is a common problem in Mobile Ad Hoc Networks (MANETs). There are several backoff algorithms that have been proposed to avoid this problem. This paper proposes a new backoff algorithm called the Square Root Backoff (SRB). Moreover, it identifies that no algorithm can perform the best in all cases. Therefore, an adaptive strategy is proposed to choose the best backoff mechanism from a set of mechanisms based on network density and mobility parameters. The proposed adaptive algorithm is implemented in two phases, the offline phase and the online phase. Such design aims at reducing the time complexity of the algorithm by performing some of the computations prior to the actual deployment and of the network. Results from simulations demonstrate that the SRB algorithm achieved better performance than BEB and LB. Moreover, the adaptive backoff algorithm obtains the best throughput and end-to-end delay performance over the other backoff algorithms.

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