Performance of the IEEE 802.16 MAC Protocol with Varying Request Backoff Start

Bhandari, B. N.; Kumar, R.V.R.; Maskara, S.L.

doi:10.1109/tencon.2006.344141

Cited by 5 publications

(4 citation statements)

References 4 publications

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“…Then, we analyze the collision probability, access delay and network throughput for the analytical model. (17) In WiMAX's TBEB, a request will be dropped when the total number of retransmission times exceeds the specified threshold. However, IEEE 802.16 uses the same retransmission limit for different priorities nodes.…”

Section: Markov Chain Analysesmentioning

confidence: 99%

“…(13)-(14) and the parameter r , the probability of state ( ,, ik-the closed-form feature of the Markov chain model, the sum of all states' probabilities is equal to one, as indicated in Eq (17)…”

mentioning

confidence: 99%

“…times and the backoff window range affect the probability of state (0,0, -), i.e., , can be determined by Eqs (13),(17). and(18), as indicated below.…”

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confidence: 99%

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Adaptive ranging algorithm for fast seamless handoff in WiMAX mobile networks

Chang

Liang

Hsieh

2010

The IEEE Symposium on Computers and Communications

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The WiMAX multicast and broadcast polling modes uses the Truncated Binary Exponential Backoff (TBEB) algorithm as the Contention Resolution Process among distributed mobile nodes while the network traffic load is nearly saturation. TBEB suffers from high collision probability under a high traffic load. TBEB thus significantly degrades the grade of service, especially while considering handoff in the mobile WiMAX network. Thus, this work first proposes an efficient contention resolution algorithm that consists of two key contributions: 1) providing the adaptive minimum-maximum backoff values algorithm (AM 2 ) to partition collision domains and 2) supporting a dynamic waiting-penalty algorithm (DWP) for successful contentions to dynamically decrease CWs while contentions randomly selecting the same CW. Second, we model the proposed approach as a discrete-time Markov chain model, and then mathematically analyze important metrics: collision probability and throughput. Numerical results indicate that the analytical results are very close to the simulation results, which justify the accuracy of the analytical model. Additionally, the proposed algorithm outperforms IEEE 802.16 and all compared approaches in collision probability and network throughput.

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Section: Markov Chain Analysesmentioning

confidence: 99%

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confidence: 99%

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Adaptive ranging algorithm for fast seamless handoff in WiMAX mobile networks

Chang

Liang

Hsieh

2010

The IEEE Symposium on Computers and Communications

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“…Recent studies found in the literature focus on system performance regarding support of Quality of Service (QoS) [4][5][6][7] and cross-layer issues [8][9][10] for the IEEE 802.16 MAC protocol. However, only relatively few studies [11][12][13] explicitly approach the analysis of the Best Effort (BE) service class in comparison to other service classes (UGS, rtPS and nrtPS).…”

Section: Introductionmentioning

confidence: 99%

Performance analysis of best effort support in broadband IEEE 802.16 networks

Rangel

Gómez

Chapa

et al. 2009

2009 Canadian Conference on Electrical and Computer Engineering

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This paper presents a performance analysis of best effort support over the MAC protocol proposed in the IEEE 802.16 standard. We focus on the uplink channel since it is the critical element for efficient delivery of services on demand to individual users (i.e., Best Effort service). We describe a modeling approach and derive the resulting analytical model. Such a model allows us to efficiently compute network throughput. We test this model by means of computer simulations which are also reported in this paper. Simulation results and theoretical computations showed a close agreement, thus validating the model.

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